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Machine learning is helping unsigned artists make Spotify pay

Usually only artists that are already quite successful can access an advance on royalties, but Swedish startup Amuse wants to help level the playing field.

In 1997, David Bowie partnered with an insurance company to create Bowie bonds – a kind of asset-backed bond that gave him (and investors) a share of the current and future royalties of his music. Bowie correctly predicted that his music would only become more popular, but he didn’t want to wait years into the future to reap the rewards.

But maneuvers like this are pretty much only open to superstars, like Bowie. For a struggling musician hoping to break into the industry, the way that it’s all set up can be a massive headache. When musicians get signed to a record label, they can get an advance on future royalties, in order to finance renting equipment or studio space, or even shooting music videos. An advance effectively functions as a loan – financed by revenue from other, successful artists – and the artist has to pay it back if and when their music starts to bring in money too. But this is only open to comparatively few artists.

Amuse, a Swedish music distribution startup founded by former Universal Music Group label heads and other industry experts, is trialling a new service that aims to let more artists access future royalties before they earn them, using machine learning to predict what those royalties could be. Here’s how it works: artists upload their tracks onto Amuse, and those tracks are distributed onto streaming platforms such as Apple Music and Spotify. Then, a team of experts at Amuse analyse where the streams are coming from, what kind of stream they are (for example, if they come from premium users), and how many streams different artists get.

A program that Amuse has developed in-house assigns each of those characteristics a value. It then calculates how much an artist could expect to make in future royalties and offers a corresponding upfront payment, called a Fast Forward Advance. An artist who has 300 followers, all of whom are from Brazil, will be offered a lower Fast Forward Advance than someone who has 5,000 followers that are spread out throughout the world or are in the country the artist comes from (so far, the bulk of the artists that use Amuse are Scandinavian, partially because Amuse is headquartered in Stockholm).

Although Amuse is also a record label with some artists signed to it, the major difference is that it’s also a free distribution service, so an artist simply has to sign up to use it (without signing to the label) in order for their data to come into Amuse’s hands and for them to be offered an advance. In order to finance the system, Amuse charges a fee between 10 to 20 percent of the payment it offers. In terms of risk, the artist only pays back the royalties that they are expected to make.

Currently, the commercial music industry works on a large scale – moving big sums of money around to advance artists, but keeping them in debt for years if they fail. Amuse envisages its tool being used for something more quotidian – a smaller artist might use it to finish filming a music video or to rent some equipment for a last minute gig, for example. The company says that the smallest advance it has given out so far is $400 dollars and the largest $100,000.

If an artist becomes more popular while using the service, then that’s factored in and they get a new offer from Amuse. “If they become more popular, then they earn back that money much quicker, and then we’re done with that transaction,” explains Diego Farias, one of the founders of Amuse. “Then, they’re eligible for a new Fast Forward advance, and then their valuation has increased.” If they don’t make the money that they were predicted to, then nothing happens – they don’t have to pay it back.

Although it’s early days, Amuse says that nearly 100 artists offered the Fast Forward Advance have so far accepted, out of roughly 400. Paul Allen, who is the head of Data and Insights at Amuse, says the Fast Forward Advance was a natural move as the company was already using similar streaming data and tools to identify artists it might be interested in. “Now, we’re just taking it one step further.”

 

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8 Top eLearning Trends For 2019

eLearning Trends For 2019: Which Form The Top 8?

Let’s look at the top eLearning trends for 2019 that will become stronger as we move forward:

1. Adaptive Learning Going To The Next Level

In my last year article on eLearning trends for 2018, I had predicted that adaptive learning will become stronger with greater adoption. It seems to head that way, as many new players are emerging. Adaptive learning, supported by confidence-based assessments and strong analytics and measurement of training effectiveness, is taking learning to the next level.

Very soon, in 2019, adaptive learning will make further strides in the eLearning marketspace. Organizations and learners will benefit as organizations ensure that there are better competition rates, and learners will enjoy the learning process as they get to see only that content that is personalized to them. Using effective assessments, learners can skip the content that they are completely confident about.

LMSs are slowly gearing up to compete with platforms that are offering adaptive learning. Hence it will be an important and interesting trend to watch out for in the coming year. My gut feeling is, adaptive learning is here to stay and the experimentation phase is over, and it will all about action in 2019.

2. Microlearning

Microlearning was a strong trend in 2018. I have seen that organizations are increasingly looking at microlearning as an important solution. It is a great method of implementing learning in small chunks that are objective driven and can be easily and quickly deployed within organizations.

Organizations that are looking to take advantage of microlearning will continue to benefit from this interesting and innovative mode of learning.

Learners benefit too as they get through the modules quickly and can repeat the learning many times as well. Retention is better, and they are less fussy about going through a boring hour-long module.

Microlearning can be implemented as videos, small games, quizzes, and infographics.

The great advantage of microlearning is that it can be implemented on any device. I feel microlearning will continue to be a strong trend in the year 2019 and beyond.

3. Artificial Intelligence And Learner Assistance

Artificial Intelligence assistance has picked up in the eLearning space. Organizations are now offering innovative solutions where bots are able to guide learners both on the learning path, as well as during the courses.

Artificial Intelligence will be used to predict learner behavior, as well as help personalize the learning. Based on the modules that were taken by learners and the difficulties or challenges faced, better personalization will be brought about. Voice-guided bots will also help learners to search for key content in modules. As I see it, organizations will be implementing newer methods of Artificial Intelligence support for their learners in both the learning process and during the moment of need. An example of this could be an intelligent chatbot that can act as support for technical queries.

Added to the mix is the use of robots for helping kids and people with special needs to learn new skills, and help them in the moment of need.

My take is that Artificial Intelligence will continue to be a very strong trend, and that it is something that will change the learning landscape in 2019 and beyond.

4. Gamification And Game-Based Learning

Gamification and game-based learning were strong trends in 2018. Organizations are increasingly looking at investing in game-based learning to empower and engage their learners better. It has been observed that gamification has improved retention rates and better application of the subject matter learned at work.

Organizations will look to implement more game-based solutions, as they see them as value adders for the organization-wide learning. Games that are well thought out, well designed and address the needs of learners engage them effectively. It has been proven through numerous implementations that games help in releasing happy hormones, such as dopamine and serotonin.

A learning organization is one that takes advantage of game-based learning.

In my opinion, game-based learning is here to stay, and will continue to be a strong trend in the year 2019 and beyond.

5. AR/VR/MR

Virtual Reality and Augmented Reality are both growing rapidly as important modes of implementing learning content. It has been observed that K-12 has adopted Augmented Reality in a rapid way to teach various subjects, such as Science and Math.

The great thing about Augmented Reality is that it can augment the existing content through interesting overlays of graphics and images that can pop out and thrill the learners. More than the thrill, it is the experience itself that helps learners connect to the content better.

Virtual Reality continues to grow as it is used in teaching various safety-related procedures. Organizations are now looking at Virtual Reality as an important solution, as eLearning companies use effective Instructional Design strategies to enhance the VR experience. Using a mixture of 360-degree photographs, interactions, and many more elements, VR is becoming a useful experience. Organizations are also investing in cognitive learning products that are augmented by VR especially for children and people with special needs.

Added to AR and VR is the exciting new modality called Mixed Reality or MR. Already big players are making investments in MR which combines AR and VR to a great effect.

Organizations will continue to take advantage of this interesting trend in the year 2019 and beyond.

6. Video-Based Learning

Videos are one of the hottest modes of training right now. The popularity of video-based sites like YouTube have forced organizations to adopt more videos into their training. Be it Instructor-Led Training that is interspersed with anecdotal or contextual videos, or eLearning where videos play an integral part in disseminating information, videos are here to stay.

The focus is on decreasing the load time and the size of videos using various tools. Video-based learning will continue to grow and will be an important trend to watch out for in the year 2019 and beyond.

7. Social Learning

Social learning involves collaboration between individuals at the workplace through various modes, such as forums, informal chat sessions, sharing sessions, and learning circles. Social learning has picked up in the last few years thanks to the emphasis on building a learning organization. As more collaborative tools are developed, social learning will continue to grow and leave an impact in the year 2019 and beyond.

8. Content Curation

Content curation has found a lot of support from the learning community and professionals in 2018. What will the year 2019 hold for this wonderful method of curating information and providing the learners with just-in-time information? I feel LMSs will continue to grow and offer content curation as an important method of sharing information, and provide the right experience to the learners. I see that content curation will continue to be a strong trend in the year 2019 and beyond.

Conclusion

These are the trends I foresee as preferred modes of learning in the coming years.

I would love to hear from you with suggestions on what other trends can contribute to enhancing the eLearning space during 2019.

 

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The Methodology and Data Driving the Inc. Entrepreneurship Index

The Inc. Entrepreneurship Index takes the pulse of American entrepreneurship by sourcing traditional government data covering 60,000 households every month and big data from businesses, including real-time payroll records for more than 350,000 businesses courtesy of Paychex and capital data from Biz2Credit covering thousands of companies every quarter.

The index uses three key indicators to track the health of American small-business entrepreneurship on a quarterly basis:

Entrepreneurship rate: the percentage of U.S. adults who own their own businesses, regardless of size Access to capital: the percentage of loan applications by businesses that get approved, from sources including big banks, credit unions, and alternative lenders (Powered by Biz2Credit) Small-business job growth: the percentage growth of average employment in existing small businesses (Powered by Paychex)

In addition to the core metrics above, Inc.'s ongoing coverage will include other metrics for context, including wage growth, labor market tightness, and sources of capital.

The index will be updated and changed as more and better sources of data become available.

Founded in 2007, Biz2Credit matches entrepreneurs with credit solutions in a safe and price-transparent environment. With more than $1 billion in funding and over 150,000 small- and medium-size- business users in the U.S., it is a leading online small-business lending platform. Its patented technology works for more than 100 major banks in the U.S., credit rating agencies like Dun & Bradstreet, and major SMB service providers including Dell. Learn more about Biz2Credit by visiting biz2credit.com.

Combining innovative technology and dedicated, personal service, Paychex is a preeminent provider of human capital management solutions for payroll, HR, retirement, and insurance services. Backed by 45 years of industry expertise, Paychex serves approximately 605,000 payroll clients across more than 100 locations, paying one out of every 12 American private sector employees. Learn more about Paychex by visiting paychex.com, and stay connected on Twitter and LinkedIn.

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The irrationality of cheating at gamified learning

Game mechanics can make the learning process more sticky, but they can also encourage cheating. How do you make sure that the logic of the game doesn't overtake its intended educational purpose? 

As I came to the end to the end of my daily vocabulary exercises, I clicked on the little icon that said "Ranking" on the side of the screen. It had become a sort of habit -- you might say a guilty pleasure -- to check my progress against others learning languages on the same website. There had been a certain satisfaction when I first spotted my name amongst the top ten of users who had started at the same time as me, or the moment when my overall ranking passed from the ten thousands to a mere four figures. It was meaningless, of course. There was no prize for winning and no-one would be impressed by my progress up the charts.

It was just one of the little rituals that somehow made the process of improving my French more compelling.

On this occasion, however, upon clicking and redirecting, I was greeted by something quite different to what I had expected. No charts, no leaderboard, but a polite notice in an unassuming sans-serif. "Regrettably," it began, "we have had to temporarily disable leaderboards on Memrise after extensive cheating has been brought to our attention, some of which has been slowing down the site for the whole community."

Memrise launched in private beta three years ago and is just on the verge of launching its non-beta version 1.0. In 2010, it was named one of Techcrunch's start-ups of the year and last year garnered a whole swathe of favourable press, from Fox News' Cool Site of the Day to MIT

Technology Review. The idea, founder Ed Cooke tells Wired.co.uk, is "pretty simple: make learning as effective and enjoyable as possible".

Cooke is an Oxford University graduate who became a Grand Master of Memory at 23 (for which he had to memorise 1,000 random number and ten decks of cards in an hour) and went on to coach American freelance journalist, Joshua Froer, to become 2006 USA Memory Champion. So when Ed talks about packing Memrise "with all the science we can muster", well, that's a fair bit of science. In this case, a combination of "vivid imagery", "elaborate testing' and "spaced repetition" taking advantage of the effect first noticed by German psychologist Hermann Ebbinghaus in 1885 stating that last minute cramming is a lot less productive than a little and often over a longer period.

 

Memrise couples these techniques with a wiki library of "mems" (mnemonics) and what Cooke calls a 'Farmville-style learning game, where you plant words, grow them, water them, and see in your "memory garden" the scope and splendour of all the things you have learned.' Since its Facebook app launched in 2009, Farmville, with its addictive simplicity and viral transmission, has provided the model for a trend towards "gamification" that has taken the worlds of business and marketing by storm. It was while being mentored by one of the bosses of Zynga, Farmville's creators, that Memrise developed its garden metaphor and game-like interface.

They are not, however, the only language acquisition site on the block. Duolingo only went public in June of this year but it quickly racked up a few hundred thousand eager users. The brainchild of reCAPTCHA inventor Luis von Ahn and his graduate student, Severin Hacker, the idea came from a desire to "translate the web into every major language". The problem, von Ahn told me, is that "machine translation is just not very good yet." It soon became apparent that such a task would take millions of people - happily, "there are over 1 billion people learning foreign languages in the world and many of them translate some stuff while learning." Luis and his team put two and two together and Duolingo was born. 

If the model sounds like it takes its cue from the "artificial artificial intelligence" of Amazon Mechanical Turk, its more the case, as von Ahn delicately puts it, that "Mechanical Turk was inspired by earlier work". In 2002, von Ahn created the ESP Game which was bought by Google and became Google Image Labeler. His PhD thesis in 2005 was the first work to talk about both "human computation" and "games with a purpose". Duolingo shares with Memrise certain elements familiar from computer games -- you can gain points and lose lives -- but von Ahn is wary of the word "gamification". "Everybody," he says, "is 'game-ified' now". Ed Cooke likewise, calling it a term 'you have to hate' while allowing that incentives like leaderboards and point scoring are important for keeping people interested "minute by minute".

The suspension of Memrise's leader boards, however, seems to raise the question of what happens when the logic of the game starts to overtake itself. Margaret Robertson, game designer and managing director at Hide&Seek design studio, spoke to me of a "desire to cheat" which lurks behind the competitiveness of gaming, and in the case of Memrise this seems to have run riot. The original suspension message spoke of "bots", "dummy courses" and even a "small army of children" employed to rack up scores. Cooke didn't wish "to glorify some of the bizarre lengths people have gone to cheat on Memrise" but he did point to a "whole genre of YouTube videos" on the topic, some of which -- showing twelve windows open at once auto-completing each other -- have notched up several hundred views.

For theorist Ian Bogost, author of How to Do Things with Videogames, the problem is not with gamingper sebut comes from mistaking games for "points-machines" rather than what he calls "experience-machines". As Robertson puts it, games are "safe spaces we opt into"and a good game will circumvent the temptation to cheat by "preparing for it and embracing it" much as many of the classic console games did.

Both Cooke and von Ahn told me about plans to incorporate more competitiveness and more gameplay into their respective platforms, so perhaps the cure for gamification's excesses is simply more gamification.

August 2018

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5 Compelling Reasons Organizations Choose Multiple Learning Management Systems

Organizations go for multiple LMSs when their current LMS is unable to meet their growing needs, or when they need a fairly simple LMS to train external partners. This article uncovers 5 compelling reasons organizations opt for multiple LMSs. Why Organizations Choose Multiple Learning Management Systems

With online training being extensively adopted by organizations, the next logical step is to go for a Learning Management System or an LMS to implement, track, and measure training effectiveness.

Organizations that have adopted an LMS to manage their training may discover, a few years down the line, that their current LMS has fallen short of meeting their growing requirements. Or they may feel that they need to opt for another LMS to meet certain unique needs of their business. In such situations, they are likely to opt for an additional LMS that will meet their changing requirements.

What are the reasons for companies deciding to go for multiple LMSs? We will explore a few in this article.

1. Access And Security Requirements

Organizations feel the need to go for an additional LMS when they have to provide training to external partners such as distributors, customers, and vendors. For security reasons, they would not be willing to provide access to their regular LMS, which may contain classified content.

Of course, the primary LMS an organization uses will have restrictions on permissions and may not be accessible to everyone. However, it could be an administrator’s nightmare to provide permissions to new groups of users every single time, after taking care of all security protocols. So a second LMS with specific content and the feature to add users belonging to specific roles will solve their problem and make training management easy. A second LMS will help the organization control access rights and meet security requirements.

2. Need For A Decentralized LMS

A common pain point in LMS use for an organization spread across the globe is the inability to meet the specific needs of geographical areas, Strategic Business Units (SBUs), or manufacturing units. The training content and tracking requirements are variables they have to deal with. They find it difficult to handle these diverse requirements from a single LMS, usually managed from the head office.

To solve this problem, an additional LMS is a better option because it can be customized based on the requirements of each geographical region, SBU, or manufacturing unit.

3. Different User Groups

Apart from access restrictions to the main LMS or the need for decentralization, some organizations may need an LMS to cater to the needs of small user groups. When organizations are looking at another LMS, it does not make sense to opt for an LMS with the same features like their current one because the features will be redundant and not required for catering to small user groups.

The cost factor could make a dent in the budget, and it would not be worth the investment. A wiser decision would be to opt for a lighter version LMS with limited features that can cater to the simple needs of small user groups.

4. Avoidance Of Additional Training Investment

Organizations with an LMS that has complex features will find it difficult when a new set of users is to be added. This is because they will have to train them on the LMS and invest time and money for the purpose. This will be a repetitive process, every time a new set of users is added.

Organizations can opt for a simpler add-on LMS with intuitive, user-friendly features that new sets of users can readily adopt and use. It also saves the organization the training time and cost.

5. Curtail Costs For A User Fee

Some LMSs charge a high per-user fee once the number of permitted users is exhausted as per the pricing plan the customer has opted for. It would make sense to choose an add-on LMS that charges a lesser amount for user fees or provides a higher number of permitted users in their pricing plans.

What To Look For When Selecting An Add-On LMS?

When opting for an add-on LMS, organizations are wiser, because they know their actual requirements. That said, let us reiterate a few things you need to look for when opting for one:

Consider your budget – have realistic expectations from the LMS matching your budget. Choose add-ons to the LMS based on a 3 to a 5-year outlook of what you will need. The costs versus benefits decision should accommodate the future perspective. Look for a vendor who can implement the LMS rapidly and implement the core functionality efficiently. Opt for a vendor who can provide quicker and frequent upgrades, so that your LMS stays up-to-date with the latest technology. Choose a vendor who offers a free demo or a trial period so that you can test drive the LMS and see if it will work for you.

Organizations opting for an additional LMS do so for various reasons. Analyzing your reasons for wanting to do this and choosing an LMS that will meet your changing needs will make it worth the investment.

July 2018

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How the cloud is changing data analytics

Analytics are seeping into more functional areas of enterprises, often without IT's involvement and with mixed results.

Once upon a time, understanding and communicating business metrics was the job of the IT department or, more specifically, the IT function responsible for what we used to call “data processing.” But today, analytics is spreading out across organizations, fueled by business units and departments that want something better than what IT is providing, faster than IT can provide it. As a result, analytics are seeping into more functional areas of enterprises, often without IT’s involvement and with mixed results.

That has a downstream effect on who is managing which data, and under whose control. And it's happening primarily in the cloud. Most on-premises analytics vendors are adding software-as-a-service versions of their products, while the number of native SaaS analytics options continue to grow. Both vendor types are targeting business units and departments (in addition to or instead of IT) because the line-of-business teams are hungry for analytics and have their own IT budgets.

Why cloud-based analytics are so attractive

The scalability and elasticity of the cloud, combined with its computing and storage capabilities, enable organizations to work with larger data sets from which they can gain insights that were previously difficult or impossible to unearth. With cloud analytics, users can combine internal data in new ways, mix internal data with third-party data, and get predictive views of success levers, such as customer behavior and supply chain impacts as opposed to historical views only.

It isn’t all rosy, however. While SaaS-based analytics capabilities are attractive, there are some very real issues enterprise buyers should consider, whether they’re adding cloud analytics to an existing mix of on-premises solutions or migrating from on-premises solutions to cloud alternatives.

It’s also important to realize that different analytics options serve different roles within the organization, including data scientists, data analysts, business analysts, and business users. Sometimes, the attractiveness of one type of option is offset by limitations that hadn’t been considered.

For example, IT industry association CompTIA learned firsthand that some cloud analytics platforms do a great job of uploading data in its current format and displaying the data, but the software is not necessarily designed to do calculations. “If you have raw data and you want to show the mean, the median, and the range, you may want to do regressions analysis that not all analytics platforms are able to do,” says Tim Herbert, senior vice president, research and market intelligence, at CompTIA. “You may have to perform the calculations using whatever you’re using on-premises, Excel or database analytics, and upload it to the cloud.”

You're adding to on-prem solutions

Many organizations have on-premises analytics solutions and are adding SaaS analytics solutions to the mix. The cloud offerings likely need to be populated with data, more data than is practical to move over a network connection.

“You can’t do that over the wire. So you have to do it by another means, such as a box the vendor ships you, like AWS Snowball or AWS Snowmobile, which is a truck they drive to the customer facility,” says Mike Gualtieri, vice president and principal analyst at Forrester Research. “Once you do that, it’s not a big deal to move data back and forth because it’s drips and drabs compared to the original move.”

The city of Los Angeles uses Amazon Web Services (AWS) for cybersecurity analytics. According to CIO Ted Ross, Los Angeles is the biggest security target on the West Coast: It has the second busiest airport in the U.S., the largest port in the Western Hemisphere, and 4 million residents. With a high-profile police department—think of the number of TV shows and news stories in which it’s been featured—that makes it top of mind for hackers, who know any hacking success gains more notoriety.

“We’re ingesting 240 million records every 24 hours across 37 different departments,” Ross says. “It’s the proverbial haystack in which we have to find the needles that represent breaches. The cloud provides an effective mechanism at a reasonable cost for us to perform large amounts of data analysis, whether it’s cybersecurity or otherwise.”

Organizations with significant investments in on-premises hardware and software have to decide which analytics processes to migrate to the cloud, at what pace, and for what reason. 

“It’s a workload conversation first because it depends on what applications have been developed and when. Some of those applications may not be cloud-ready,” says David Rubal, chief technologist for data and analytics at DLT Solutions, a government-focused value-added reseller. “Technology is advancing so fast that there have been systems, applications, and databases that were developed years ago and [their creators] have gone out of business. So there’s an island in the IT environment [that requires] a separate migration path.”

When migrating from a traditional data warehouse environment to the cloud, unanticipated latency issues can arise. Latency can adversely affect application performance and therefore user experience, the timeliness of analytics, and even the accuracy of time-sensitive insights.

Also, endeavor to understand the comparative TCO and ROI for on-premises and cloud analytics. To optimize the respective workloads and investments, do your best to judge what each is best suited to. 

“If you’re putting something into the cloud, you’re not locked in. You need to be able to move workloads up or pull them down, so you can start off in the cloud and move on-prem if that makes sense, or start on-prem and move into the cloud,” says Ross. "A wise organization is always evaluating and always getting the best possible benefit.”

You're migrating to cloud solutions

Some organizations will migrate to the SaaS version of an on-premises business intelligence or analytics offering or to an entirely different solution or set of solutions. Either way, there may be more factors impacting the decision than simply product capabilities, features, and functions. Depending on the circumstances, technical issues such as data mapping may come up, particularly when moving from one vendor’s product to another vendor’s product.

“You have to plan ahead because you have to look at how data in your on-premises setup might map to whatever your setup might be in the cloud. I think anytime you do migration or export, you need to think carefully and make sure that you don’t have any problems in terms of data hygiene," says Daren Orzechowski, a partner in the Sourcing & Technology Transactions practice at international law firm White & Case. Maybe fields don’t map the same way or things aren’t coming out in the format they were in the old environment versus the new environment.”

Leaders must also consider the bi-directional portability of data because terms and conditions among vendors can vary. Uploading data to a public cloud service is usually not an issue. Getting the data out can be a challenge, however. Buyers should familiarize themselves with the terms and conditions of service, including data portability, before pressing the “I agree” button.

Cost is another issue you need to understand in detail up front. Cloud services are generally assumed to be less costly than on-prem solutions, but if you don’t understand the pricing structure, you may be in for a surprise. Some users have found out the hard way that as usage scales, so does the cost.

“I’ve heard of [companies] getting huge bills from AWS because people had an account and had free range to do what they wanted to do with data, but it can be very expensive if you have a consistent workload,” says Forrester’s Gualtieri. For example, he says, "if you're running portfolio risks every day, it may be cheaper to run them on-prem."

Don’t forget security

Some organizations are still so skeptical about cloud security that they avoid the cloud entirely. Others consider cloud solutions inherently secure. Generally speaking, enterprises have become less concerned about security given the massive investments Microsoft, Amazon, and others have made to protect their respective infrastructures. Yet as always, cloud security is only as strong as its weakest link.

“My security staff needs to understand how to perform security like we did with on-prem, and now that we’ve moved onto the Internet, we need to approach it that way,” says the city of Los Angeles' Ross. “You need to be able to know how to manage an application and data that aren’t residing within your on-premises architecture.” 

Some analytics vendors have built products on AWS, Azure, and Google Cloud Platform to take advantage of the scalability, elasticity, and security. However, even if a vendor’s security mechanisms meet your needs, your internal security practices may nevertheless open the door to breaches.

“In some cases, the situation may be exacerbated because you have more parties accessing cloud data than on-premises data, so you have to ensure you have your administrative rights set properly,” says CompTIA’s Herbert. “Usually, there will be options that allow users to get dashboard data and perform some basic manipulation, but they don’t have access to the dataset. They can’t export it or change it.”

Backups can also be an issue when the data sent to the cloud hasn’t been updated regularly. Although most businesses back up their data, many are not as disciplined as they should be when it comes to updating data assets in the cloud.

Bottom line for cloud analytics

Cloud analytics provide businesses with scalable, flexible, and often compute-intensive options that can be used to create competitive advantage. However, the ease and speed with which these products can be adopted may overshadow the fact that the implementation is more complicated than first apparent. For example, more lines of business are adopting their own cloud analytics solutions, but they may not consider who has access to the information or whether the vendor's end-user license agreement violates their company's security or privacy policies.  

Most have policies designed to govern the behavior of their employees, but those policies aren’t always enforced and the details can get lost in the complexity that has become the modern business environment. As always, a partnership between business and IT is wise when it comes to making technology decisions.

Analytics in the cloud: Lessons for leaders Don’t expect analytics nirvana. Many cloud analytics platforms have frustrating feature limitations. It’s common to use both on-premises analytics and SaaS applications. Choosing which to migrate requires answering hard questions about the appropriate analytics processes to migrate to the cloud, as well as when and why. Consider how sharing data in the cloud may add new security vulnerabilities.

 

June 2018

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Why a K-12 Operating System is the Next Step in the Evolution of Edtech

Nearly ten years ago, I started my career in education as a math teacher at a new alternative high school serving over-age, under-credited youth in New York City. My students were labeled “at-risk” of dropping out because they were 16-21 years old and previously unsuccessful in high school. Many suffered from chronic absenteeism, caused by factors such as homelessness, family responsibilities, and/or incarceration. If we, the educators, were going to serve our students well, we were going to have to get pedagogically creative.

If we, the educators, were going to serve our students well, we were going to have to get pedagogically creative.

One of the first curricular tools I built to share—on the first day of school—was a public, student-friendly gradebook on Google Sheets. (Yes, this was before Google Classroom existed!) Students could track their progress and identify which skills needed extra work at any time. Little did I know this experience would eventually propel me to help develop a school operating system that tackles technology issues plaguing educators and supports them with more opportunities to offer individualized instruction.

Creating a Toolbox—and Filling It

After creating the gradebook, my colleague and I developed a curriculum aligned to New York state math standards. We scoped and sequenced the curriculum according to a set of power standards representing scaffolded skills. If students mastered a power standard, they could move on and didn’t need to wait for others. This competency-based system made sense; if students were chronically absent, holding them accountable to a pacing calendar would prove futile. 

To supplement in-person support offered during class and lunch periods, I published a simple Google site to house my lessons, assessments, and other resources. If students missed class or needed additional help, they could go to my website and access the day’s lesson as well as videos and digital exercises from YouTube and Khan Academy.

Abbas Manjee's standards-based Algebra 1 scope and sequence. Full size image here.

As my students submitted work, I tracked everything in my gradebook. My goal was to minimize the information asymmetry that tends to exist between what teachers know about their students and what students know about their performance. At the time, I had no idea this system was called “standards-based grading.” I was so green at this point in my career that I probably assumed every classroom in the 21st century operated this way. I didn't realize what we were trying to build was innovative.

It felt like every tool I used in the classroom was inherently designed to work in isolation.

The following year, I wanted to ensure that when students did come to class, they could participate and engage—or at the very minimum—access the content via a class set of iPads. I stepped up my game by adding even more videos and assessment exercises to my class website, mining resources from IXL and CK-12. I generated logins for my students and started “blending” instruction using the free content from these publishers. This worked nicely for my students, who felt like I was carefully attending to their learning pace and providing them with targeted learning materials.

By the end of year, more than half of my students passed the Algebra 1 state exam. For context: in years prior, every one of these students had failed this exam at least once. Of those who failed again this time around, many had never come so close to passing and looked forward to retaking it in the summer. 

Enter the LMS

I was proud, but also exhausted. The time required to maintain the number of tools I was juggling was eerily close to the time I used to spend working as an investment banker. I dedicated hours every week copy-pasting student achievement data from multiple systems into one gradebook, analyzing each student’s progress and assigning work based on need. The last thing I needed was another system to maintain, but that’s exactly how my third teaching year started: my school administration decided a centralized system for grades was necessary to assess how all classrooms were doing. They bought a learning management system (LMS) and asked us to start using it. 

Procuring the LMS was purely an administrative decision, fueled by a desire to monitor school-wide trends to make resource allocation decisions. I couldn’t fault school leadership for this, but I still hated using it. I didn’t want to change the way I’d set up my class because my model working for my students. Now, in addition to importing data from IXL, Khan Academy, and an adaptive learning program called Carnegie Learning, I had to transfer the achievement data from my gradebook into another system. It felt like every tool I used in the classroom was inherently designed to work in isolation. 

By the end of that year, my patience had grown thin. I stopped updating the LMS on a regular basis and wondered how long it would take before somebody noticed. My colleagues had mixed feelings about it too. Because the LMS was designed to contain a lot of tools for teachers in a single view, it was clunky and cumbersome to use. For example, it didn’t integrate with Google Apps, which we had spent the last three years using. Nor could I customize features to align with my class set-up, or remove certain features altogether. 

Building and Brainstorming

After three more years teaching in alternative high schools, I left the classroom to join Kiddom and address this interoperability problem. In an ideal world, teachers would be able to access a set of tools driven by their classroom needs and aligned to an instructional model of their choice. Administrators would be able to measure and take action from macro-level trends, manage and review curriculum, and enable educators to incorporate the instructional models and technologies that serve their classrooms best. 

Unfortunately, teachers are constrained by tools that are ineffective or redundant. Many education technologies are not interoperable. School and district leaders continue to spend an inordinate amount of time piecing together data to understand what’s really happening. When that takes too long or doesn’t work, they resort to classroom observations—because they’re easy to do.

During my time at Kiddom, I’ve had the opportunity to apply my teaching experience and work with a team of designers and developers to tackle these problems head-on. At first, we focused on teachers and learners and the tools needed to enhance a singular classroom experience; this led to a simple, visual standards-aligned gradebook. Next, we connected this gradebook directly to digital content publishers like CK-12 and Khan Academy so that teachers could access teaching resources in order to differentiate instruction efficiently and save time.

Because every classroom experience plays a role in the larger ecosystem within a school, we designed a set of collaboration tools to help teachers work together, share, and learn from each other more effectively. We then focused on the information asymmetry that exists between classrooms and their respective administrative bodies. Working with and listening closely to public school administrators, we brainstormed various ways we could support school systems from the top-down and bottom-up.

A K-12 Operating System

The result of this work is Kiddom Academy, a K-12 school operating system supporting collaboration and individualized instruction. Using Academy, administrators can identify and act on aggregate achievement trends, manage curriculum and assessment, and efficiently integrate other tools they’ve come to rely on. They can set up frameworks for a range of pedagogies in line with their organizational goals. Classrooms gain access to a comprehensive library of standards-aligned resources and curriculum development tools. Beautiful, actionable reports help students, teachers, parents, and administrators monitor progress and take action. 

A K-12 school operating system is the next step in the evolution of education technology.

A K-12 school operating system is the next step in the evolution of education technology. Interoperability matters in schools and districts now more than it has ever before, because we’ve come expect it everywhere else. For example, I can purchase a pair of concert tickets using my EventBrite app, and then export the information directly into my iPhone calendar. So too should teachers be able to use a variety of learning apps in their classroom and expect them to work together seamlessly. As we see more content and pedagogy-specific tools in the market, we can expect increasing numbers of teachers to find and patch together the tools that work best for them; administrators will be no different. 

My teaching experience helped me understand that I didn’t need to buy a blended learning or personalized learning product. I had a process and practice in place, and needed a set of interoperable tools. I can’t imagine how much more passion and creative energy I might have offered my students and colleagues if I wasn’t staying up late every night copying and pasting data to differentiate instruction. “Personalized learning” might be trendy, but it isn’t new. Teachers have been trying to enhance and individualize learning using the tools at their disposal for a long time. 

That’s why at Kiddom, we’re hell bent on designing and implementing technology that enables all students to learn via pedagogy and pacing optimized for them. We’re betting big on the idea of building a system for other learning apps to run on—rather than in—to help schools plug and play the tools they find most effective. We can’t wait to see how schools will use Kiddom Academy to execute their vision for teaching and learning.

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Robots Are Our Friends -- How Artificial Intelligence Is Leveling-Up Marketing

How many times in the last year have you heard the question, “Is artificial intelligence going to take over our jobs?” For marketers, this question is just as relevant, but I’m here to tell you that robots are our marketing friends.

We are just at the start of tapping into artificial intelligence (AI) for marketing, but there are already a number of great ways that this  technology is improving our jobs, not killing them.

AI, in fact, has the potential to do the jobs we don’t want and the jobs we can’t do, and to ultimately help us do the jobs we already do, better. Here's more on each prediction:

AI is doing the jobs we don’t want to do.

The first obvious application of artificial intelligence is to automate the tasks that we humans don’t want to do -- those repetitive, low- skill tasks. AI can be easily programmed to do such work and do it faster, more cheaply and more reliably. A great example is the cataloguing of marketing data to be used for analysis.

Say, for example, that you wanted to write a unique blog article on the topic of “video marketing.” In order to figure out a unique angle for your article, you may want to catalogue all of the existing content on the topic of “video marketing” and even categorize each article by website, author and share metrics. This could be a very manual process for a human  and something that would invite human error into the process.

Where AI shines is that it can do such repetitive tasks -- but at scale. Imagine that, in the same time frame, a junior marketer could catalogue 100 “video marketing” articles while a machine could catalogue more than 1,000 articles on the same topic, along with 1,000 articles each for 100 more topics.

Such AI ability becomes particularly useful for marketers who are attempting to aggregate data about what’s happening outside of their company -- what’s being published by their competitors, customers or industry peers. There are tens of millions of pieces of content data created every minute, and if marketers want to leverage it, we need to employ machines to help.

AI is doing the jobs we can’t do.

Not only is AI automating jobs we don’t want to do, it’s also opening the doors to jobs we can’t do. Since AI has the ability to process an infinitely larger dataset than a human can, it can leverage that scale to identify marketing insights that would otherwise be lost.

Say you want to take the next step in that content-marketing data-collection project: You not only want to catalogue all of the “video marketing” content, but to catalogue all of the content being published in your industry more broadly. Ultimately, you'll want to use this catalogue to drive market-informed content campaigns of our own.

Identifying new topics emerging or types of articles that garner above-average shares can help direct new content creation to align with existing trends. A given article could have many different qualities that could lead to its success. It’s AI’s ability to tag and compare many data points that ultimately produce the marketing takeaway.

 

AI’s strength in turning a mass of data into insight truly shines in the noisiest, highest-volume channels that a marketer hopes to master. Social media, content marketing, news and PR are great places to start, but even competitors’ job postings and website changescan be great inputs for marketing campaigns if a business can manage to extract insight out of the noise.

Again, AI-based technologies have the ability to throw out the noise -- whether that means the same old promotional tweet or a website update to fix a typo. Those technologies can then focus on the signal -- like a tweet about an acquisition or a website change to alter a competitor’s pricing. In this way, AI can see both the forest and the trees in online data to surface takeaways for marketers they would not be able to find manually -- and in real-time, at that.

AI is improving the jobs we already do.

By incorporating AI into our marketing, we have the opportunity to free up that expensive, intelligent, creative resource that is a marketer to do higher value work. Instead of collecting data, marketers can analyze it. Instead of sifting through data, marketers can act on it.

By delegating work to AI-driven technologies, marketers can improve their work by creating content they know will stand out, by implementing conversion-optimization strategies observed from competitors’ sites and enabling sales using the latest competitor pricing. And that's just the start of what AI can potentially do.

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Going with the flow: dominKnow Platform review

We take pride at Brightwave in being authoring tool agnostic and having the in-house expertise required to design and build digital learning solutions using any tool out there. We like to understand what our clients really need and select the right tool for overcoming their specific learning challenges. Having said that, we recently found ourselves taking on a project that needed to be built in a tool that we had not previously used: The dominKnow Platform, aka dominKnow Flow. We gave the tool to our in-house Authoring Tool expert Nick Eastham to put through its paces…

Getting up to speed

dominKnow Flow is a cloud based tool that’s accessed via your web browser. At first glance the tool looks a little old fashioned and unfriendly, and consequently none of us had expected a great deal from it.

That expectation turned out to be wrong:

dominKnow Flow is in fact a very capable tool.

As with any new tool, most of the initial time was spent learning where everything was within the interface. There are so many features in dominKnow Flow that the number of tabs, ribbons, panels, buttons and menus can be a lot to take in one go.

The naming and positioning of some of these buttons and menus could be improved. For instance, there are three different ‘Copy’ buttons on the interface; each has a slightly different use. There is also a button named ‘Actions’ and tab named ‘Actions’, a fact that had me scratching my head for quite a while as the Help files didn’t distinguish between the two.

These Help files were sometimes useful but also sometimes misleading or incomplete. There were numerous times when I searched in vain for information on a particular feature, to find no mention of it at all. The community portal also seems to be more geared towards dominKnow’s other tool Claro rather than Flow.

So it took trial and error and a lot of hunting around the panels, menus and ribbons of the tool to discover its true feature set and power.

Learning Design flexibility

While there are some unusual concepts, such as pages needing to be added to Learning Objective groupings, and all of these groupings appearing to need a set of test questions, the reality is that you can structure your content in the typical chapters and pages style and can add navigation where ever needed to create the path through the learning that you require.

The real selling point of this tool is its long list of Actions that you can employ to enable you to design and build all sorts of page types and features. This is really the first authoring tool that can match Articulate Storyline’s ability in this area, and the only tool that can do this and produce fully responsive content.

You can add Actions to pretty much any page element. They can be triggered by clicks, mouse-overs, scrolls, page loads or even by other elements showing or hiding. You can show, hide, swap, toggle, play, pause, replay, or set variables or execute JavaScript. You can even send xAPI statements. And since all variables set during a session are tracked back to the LMS, they can be used on relaunch to update pages back to their previous status. We used this capability to allow the learner to create their own personal Action Plan, one they could then return to at a later time.

Art direction flexibility

On the whole we were able to style up the courses we created in the way that we wanted to. Flow allows you to select a theme from a list, then create a Variant of it, then apply a style to it.

The theme defines which functional elements appear on the page. The Variant allows you to set theme colours and apply them to text, buttons, ticks, crosses, backgrounds and tabs. You can also set background colours, button shapes and fonts. The Style editor allows you amend a set list of text styles.

I found the theme choice fairly restricting. There wasn’t quite the right combination of user interface elements available as a set theme and I couldn’t see any way to change that. In the end this didn’t matter as we opted for a fairly minimal UI.

The theme only allows you to set five colours. These are then applied to buttons, tabs, popup panels and text. It would have been nice to have the freedom to pick colours from the theme or to pick a custom colour. Five colours just weren’t enough.

Building pages

Flow allows you to insert a page, then add a layout from a pre-set list, or build your own layout, then add components into the layout areas.

The components cover such things as Click Reveals, Tab Reveals, Accordions, Carousels and Flip Cards. You can also add a Multiple Choice Question.

As well as creating your own page in this way, you can also add pre-built question pages. The options here are MCQ, Fill in the blanks, Multiple drop-downs and Drag and Drops. You can see here that there are question types available as pages that aren’t available as components. This caused us some issues. It would be great if the components also included these.

Responsive behaviour

The tool is quite flexible in how it allows you to layout your page elements. You can add rows where ever you want them and decide how many columns to partition these into. You can add empty spacers to pad out your elements and even adjust inside and outside margins on them too to fine tune positioning.

I liked the way that the page elements would collapse into the space left by any element that was hidden with an action. This allowed for the creation of pages displaying different content depending on some previous input or decision, they still looked great, with no ugly gaps present.

In use on different devices, the pages worked well. The content flowed as expected and the layout had a very controlled feel about it. There were no unwelcome surprises.

Collaboration features

The tool allows for multiple authors to be working on the same course at the same time. It does this by using locks that can be applied to pages or learning objects. The author checks out the item, makes the changes they want to make then checks it back in again to lock it. It’s very easy to use and was a huge help in enabling several authors to work simultaneously on different aspects of the same course. Our clients could also make changes if they needed to.

Publishing options

Courses can be published to the usual SCORM and AICC options. They can be set to complete on both visiting the learning and passing any tests, or just on passing the tests. You can’t however specify particular screens that the learner should visit.

But then, not many authoring tools can.

Overall,

dominKnow Flow is a very powerful authoring tool, perhaps the most feature packed and flexible of any responsive authoring tool currently available. I look forward to being able to use it again on future projects, especially now I know how to use it!

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Adopting Video-Based Learning Strategies To Boost Employee Engagement And Workforce Development

Incorporate Video-Based Learning Strategies Into Your eLearning To Meet Customized Training Objectives

Changing digital learning landscape is paving the way videos are used to impart training for the modern workforce. With the advent of the flipped classroom approach, employees prefer getting familiar with the training course first before attending the face-to-face session. It has resulted in bringing out significant changes to overall Learning and Development of the workplace. The strategy to redesign training course content in response to technological advancements has left a tremendous impact on improving content quality.

Today, videos have shifted the concept from didactic strategy to self-paced learning where employees have full control over different aspects of learning. Interactive videos are used for both conceptual and practical training purposes which include video tutorials, short clips, and scenario-based video modeling. In today’s modern scenario, there is an increasing trend of combining learner-centric and teaching-focused approaches for personalized learning experiences.

Driving Learner Engagement Through Videos

The modern workplace is filled with ample activities including working on different projects, finishing tasks, delivering customized services, and more. Industry leaders have realized the potential of employee engagement, which is more than merely completing daily tasks. Workforce engagement ensures that:

Employees are dedicated to meeting organizational goals. Have the knowledge that their participation will make a significant difference.

Today, learner engagement is the primary need for modern organizations to drive optimum workplace productivity and training outcomes. With high employee engagement, organizations seek multiple benefits including lower employee turnover, huge productivity, and less absenteeism. As per Gallup’s State of the Global Workplace report, only 15% of employees are engaged in their jobs. [1]

Today’s generation of modern workforce is the biggest consumer of online videos. Combined with the flipped classroom approach, educators are opting for innovative ways to leverage the maximum benefits of using videos. It has become more efficient to use videos that boost employee engagement and offer an experience that beats text-heavy content hands down. Let us discuss the following 5 strategies that help engaging learners using videos:

1. Embed Videos With A Training Course

Merging interactive videos into online courses is a great way to improve learner engagement. Videos boost learner interaction by bringing the course to life with an availability to access courses over multiple mobile devices such as smartphones and tablets.

2. Capture Interactive Sessions And Share

Modern learners are impatient, so they prefer instant access to the courses available via online sources. Several organizations are investing for lecture-based sessions which are instantly available to employees, allowing them to re-watch videos at their own pace.

3. Optimize Content

It is essential that video-based courses are accessible across any device, in a way that they allow learners to browse, search, access and engage in an intuitive way. In addition, content should have relevant tags and metadata to allow learners find media relevant to their need. Considering the length of videos is also crucial as content can be divided into bite-sized video nuggets that can be viewed on any mobile device.

4. Encourage Learners To Become Content Creators

The video is a highly effective tool, but it is also daunting for educators to use regularly or include it in their training methods. Also, it is important for organizations to ensure that trainers are proficient, experienced and have full access to tools which make videos easier to create, access and share.

5. Role Of Videos In Critical Thinking

Motivating employees to design and share customized videos is a powerful way to reinforce learning. Video assignments are created asking learners to submit videos rather than text-based content. This helps learners to develop new skills and improve overall workplace efficiency.

To decide whether video can be used as a tool for workforce development or critical thinking is identified through research gap. There has been less research done to analyze knowledge development and critical thinking via videos. Instead, new methodologies based on post-experimental tests are adopted to measure the effectiveness of training outcomes. Videos support this approach by providing a visually-appealing context that provides a complete understanding of the topics covered.

The prevalence of leveraging videos for workplace training has exponentially increased over the past many years and is likely to evolve in the future. New-age learners engage more through video-based courses, which empowers them to learn more efficiently. Videos offer a great level of interaction; you all watch movies and get so engrossed in the story. The same happens in case of eLearning where videos transcend your imagination into a new dimension, thereby improving the overall understanding of the content without any hassle.

May 2018

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Top 10 Hot Artificial Intelligence (AI) Technologies

The market for artificial intelligence (AI) technologies is flourishing. Beyond the hype and the heightened media attention, the numerous startups and the internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises. A Narrative Science surveyfound last year that 38% of enterprises are already using AI, growing to 62% by 2018. Forrester Research predicted a greater than 300% increase in investment in artificial intelligence in 2017 compared with 2016. IDC estimated that the AI market will grow from $8 billion in 2016 to more than $47 billion in 2020.

Coined in 1955 to describe a new computer science sub-discipline, “Artificial Intelligence” today includes a variety of technologies and tools, some time-tested, others relatively new. To help make sense of what’s hot and what’s not, Forrester just published a TechRadar report on Artificial Intelligence (for application development professionals), a detailed analysis of 13 technologies enterprises should consider adopting to support human decision-making.

Based on Forrester’s analysis, here’s my list of the 10 hottest AI technologies:

Natural Language Generation: Producing text from computer data. Currently used in customer service, report generation, and summarizing business intelligence insights. Sample vendors: Attivio, Automated Insights, Cambridge Semantics, Digital Reasoning, Lucidworks, Narrative Science, SAS, Yseop. Speech Recognition: Transcribe and transform human speech into format useful for computer applications. Currently used in interactive voice response systems and mobile applications. Sample vendors: NICE, Nuance Communications, OpenText, Verint Systems. Virtual Agents: “The current darling of the media,” says Forrester (I believe they refer to my evolving relationships with Alexa), from simple chatbots to advanced systems that can network with humans. Currently used in customer service and support and as a smart home manager. Sample vendors: Amazon, Apple, Artificial Solutions, Assist AI, Creative Virtual, Google, IBM, IPsoft, Microsoft, Satisfi. Machine Learning Platforms: Providing algorithms, APIs, development and training toolkits, data, as well as computing power to design, train, and deploy models into applications, processes, and other machines. Currently used in a wide range of enterprise applications, mostly `involving prediction or classification. Sample vendors: Amazon, Fractal Analytics, Google, H2O.ai, Microsoft, SAS, Skytree. AI-optimized Hardware: Graphics processing units (GPU) and appliances specifically designed and architected to efficiently run AI-oriented computational jobs. Currently primarily making a difference in deep learning applications. Sample vendors: Alluviate, Cray, Google, IBM, Intel, Nvidia. Decision Management: Engines that insert rules and logic into AI systems and used for initial setup/training and ongoing maintenance and tuning. A mature technology, it is used in a wide variety of enterprise applications, assisting in or performing automated decision-making. Sample vendors: Advanced Systems Concepts, Informatica, Maana, Pegasystems, UiPath. Deep Learning Platforms: A special type of machine learning consisting of artificial neural networks with multiple abstraction layers. Currently primarily used in pattern recognition and classification applications supported by very large data sets. Sample vendors: Deep Instinct, Ersatz Labs, Fluid AI, MathWorks, Peltarion, Saffron Technology, Sentient Technologies. Biometrics: Enable more natural interactions between humans and machines, including but not limited to image and touch recognition, speech, and body language. Currently used primarily in market research. Sample vendors: 3VR, Affectiva, Agnitio, FaceFirst, Sensory, Synqera, Tahzoo. Robotic Process Automation: Using scripts and other methods to automate human action to support efficient business processes. Currently used where it’s too expensive or inefficient for humans to execute a task or a process. Sample vendors: Advanced Systems Concepts, Automation Anywhere, Blue Prism, UiPath, WorkFusion. Text Analytics and NLP: Natural language processing (NLP) uses and supports text analytics by facilitating the understanding of sentence structure and meaning, sentiment, and intent through statistical and machine learning methods. Currently used in fraud detection and security, a wide range of automated assistants, and applications for mining unstructured data. Sample vendors: Basis Technology, Coveo, Expert System, Indico, Knime, Lexalytics, Linguamatics, Mindbreeze, Sinequa, Stratifyd, Synapsify.

There are certainly many business benefits gained from AI technologies today, but according to a survey Forrester conducted last year, there are also obstacles to AI adoption as expressed by companies with no plans of investing in AI:

There is no defined business case: 42%

Not clear what AI can be used for: 39%

Don’t have the required skills: 33%

Need first to invest in modernizing data mgt platform: 29%

Don’t have the budget: 23%

Not certain what is needed for implementing an AI system: 19%

AI systems are not proven: 14%

Do not have the right processes or governance: 13%

AI is a lot of hype with little substance: 11%

Don’t own or have access to the required data: 8%

Not sure what AI means: 3%

Once enterprises overcome these obstacles, Forrester concludes, they stand to gain from AI driving accelerated transformation in customer-facing applications and developing an interconnected web of enterprise intelligence.

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Can HR Become Agile?

It’s exciting to read the headline of the current issue of Harvard Business Review (HBR) for a trio of important articles: “HR Goes Agile.” Of the three articles, this review will begin with the first piece by Professors Peter Cappelli and Anna Tavis—which is presented as a status report on HR’s progress toward agility. (The other two pieces comprise an interview with IBM’s CEO and an excellent case-study of Agile implementation at the ING Bank in The Netherlands.) HBR’s editors are to be congratulated for allocating space to this cutting-edge topic—another indication that Agile is eating the world.

The Arrival Of ‘Agile Lite’

Yet before Agile advocates celebrate too extravagantly, let’s note the immediate caveat that the professors offer to the headline, “HR Goes Agile.” “HR,” they tell us, “is going ‘agile lite,’ applying the general principles without adopting all the tools and protocols from the tech world.” A miscellaneous grab-bag of practices is used to explain the concept of “HR going Agile lite:” see the Appendix below for a summary.

A further caveat, judging from the examples, is that “Agile lite” seems to mean the adoption of tools and practices without necessarily deploying them with an Agile mindset.

In effect, one has to wonder whether HR ‘going agile lite’ is like a dancer ‘going flamenco lite’ by wearing flamenco costumes and talking about flamenco, without necessarily mastering flamenco dance steps or displaying a feel or flair for flamenco music.

We should also note that the progress report is only part of the story. There are companies such as the ING Bank (as discussed in the third piece in HBR) and member firms in the SD Learning Consortium, where people management has evolved beyond “agile lite” towards genuine Agile management, with an enthusiastic embrace of the Agile mindset, goals, principles and values.

But let’s back up and remind ourselves, first, what is genuine Agile management—as opposed to ‘agile lite’— and second, what are the different roles that HR may play within an organization.

What Is Agile Management?

Agile management is now a vast global movement that is transforming the world of work. Most remarkably, the five largest organizations on the planet in terms of market capitalization—Amazon, Apple, Facebook, Google and Microsoft—are recognizably Agile. And most firms want to to be Agile: a recent Deloitte survey of more than 10,000 business and HR leaders across 140 countries revealed that nearly all surveyed respondents (94%) report that “agility and collaboration” are critical to their organization’s success,

The Agile movement took off in software development in 2001 and is now spreading rapidly to all parts, and all kinds, of organizations, as recognized in 2016 by HBR itself with its article, “Embracing Agile.” There are already hundreds of thousands of Agile practitioners all around the world. Despite scores of different labels and flavors of Agile, organizations that have successfully embraced Agile embody a mindset that includes three core characteristics or principles (as exemplified for instance in HBR’s case study of the ING ban),

1. The Primacy Of The Customer

First is the primacy of the customer. Truly Agile organizations practitioners are obsessed with delivering value to customers. That’s because globalization, deregulation, and new technology, particularly the Internet, provided the customer with choices, reliable information about those choices and the ability to connect with other customers. Suddenly the customer was in charge of the marketplace and expected value that is instant, friction-less and intimate. Now firms could no longer get away with exploiting and manipulating customers, or doing just enough to get by, within the limits and constraints of their own internal systems and processes.

In truly Agile organizations, everyone is passionately obsessed with delivering more value to customers. The firm adjusts everything—goals, values, principles, processes, systems, practices, data structures, incentives —to generate continuous new value for customers and to ruthlessly eliminate anything that doesn’t contribute. Everyone in the organization has a clear line of sight to the ultimate customer and can see how their work is adding value to that customer—or not. If their work isn’t adding value to any customer or user, then an immediate question arises as to why the work is being done at all. Some of this seemingly pointless work consists precisely of the traditional processes and systems of the traditional HR department.

2. Descaling Work For Small Teams

Agile practitioners share a mindset that work should to the extent possible be done by small autonomous cross-functional teams working in short cycles on relatively small tasks and getting continuous feedback from the ultimate customer or end user. Instead of scaling up the organization to handle big complex problems, the organization descales complex problems into small pieces that can be handled by small teams.

From the firm’s point of view, the work unit becomes the team, rather than the individual. By working in short cycles, teams can change direction easily. Big annual  plans of the kind cherished by HR departments become constraints rather than enablers. Getting the best talent that can collaborate easily and innovate rapidly becomes a top business priority. Comparing the outputs of work to a plan that is now out of date is pointless. Annual performance cycles of the kind administered by HR departments feel like relics from some bygone era.

3. The Organization As A Network

The third characteristic is that the organization functions as a network. Agile practitioners at all levels view the organization as a fluid and transparent network of players that are collaborating towards a common goal of delighting customers. Communications flow easily in all directions. Ideas can come from anywhere. When the whole organization truly embraces Agile, the organization is less like a giant warship, and more like a flotilla of tiny speedboats. Instead of a steady state machine, the organization is an organic living network of high-performance teams.

In these organizations, managers recognize that competence resides throughout the organization. The whole organization, including the top, is obsessed with delivering more value to customers. Agile teams take initiative on their own and interact with other Agile teams to solve common problems. This is a different world from traditional HR systems that, as business school professor John Kotter writes, “ask most people, usually benignly, to be quiet, take orders, and do their jobs in a repetitive way.” Such systems are get in the way of the new strategic priority: continuously generating fresh value for customers.

Those are the three core Agile principles. They are easy to understand but difficult for a traditional corporation to implement, as they involve a change in mindset and a shift in corporate culture. The principles help us understand why in large organizations, there is such a vast gap between Agile aspiration and Agile accomplishment. Thus, although in the recent Deloitte survey nearly all respondents (94%) report that “agility and collaboration” are high priorities to their organization’s success, only 6% say that they are “highly agile today.”

So, while today there are brilliant islands of excellence in Agile implementations, as at the ING bank, there is also a sea of mediocrity in terms of the business implementation of Agile, even before we get to the issue of Agile in HR. When the business itself hasn’t fully embraced Agile, it is hardly surprising that the HR department is grasping for partial solutions like “agile lite.”

What Is HR?

The HBR article provides a useful summary of HR’s troubled history.

“After World War II, when manufacturing dominated the industrial landscape, planning was at the heart of human resources: Companies recruited lifers, gave them rotational assignments to support their development, groomed them years in advance to take on bigger and bigger roles, and tied their raises directly to each incremental move up the ladder. The bureaucracy was the point: … “By the 1990s, as business became less predictable and companies needed to acquire new skills fast, that traditional approach began to bend—but it didn’t quite break… For the most part, though, the old model persisted. Like other functions, HR was still built around the long term. Workforce and succession planning carried on, even though changes in the economy and in the business often rendered those plans irrelevant. Annual appraisals continued, despite almost universal dissatisfaction with them…. “Now… rapid innovation has become a strategic imperative for most companies, not just a subset. To get it, businesses have looked to Silicon Valley and to software companies in particular, emulating their agile practices for managing projects.”

Rapid innovation may have become a strategic imperative, but some companies have moved faster than others. Some haven’t moved at all. As a result, there are today three main ways in which HR operates.

a. HR As Executioner

As firms faced more competition in the late 20th Century, many set out to maximize shareholder value as reflected in the stock price, off-shored the supply chain, regarded customers as “demand” to be manufactured, treated staff as “human resources” i.e. things to be manipulated with the goal of increasing efficiency and making money for shareholders and the executives. Downsizing was the rage, and top management needed someone to explain to staff that their lifetime employment was no longer being honored and to get them to execute the top’s orders. HR volunteered for the job. It was all about money and HR often reported to the Chief Financial Officer.

Here the conversation concerned body counts and cost reduction, ostensibly to help the organization survive. It meant HR siding with management against the staff. Little attention was given to the fear and loathing that these HR practices generated among the staff. As workers’ lives were torn apart by downsizing and offshoring, resources were shifted to shareholders and executives, and pensions were ripped off. HR’s role was to put the best possible face on a war zone.

In the process, HR won neither love from the staff nor respect from the top management. HR was no more than an executioner, following orders, but having no role in deciding what to do. It was irksome work, but someone had to do it. Today, few HR departments admit to playing this role, although it lurks in the background in many large organizations, particularly those committed to maximizing shareholder value as reflected in the stock price. It often emerges from the shadows during a crisis.

b. HR As Moderator

By contrast, in a role as moderator, HR may pursue sensible, practical ways in which it can help the organization meet the needs of all the stakeholders, moderate the more aggressive tendencies of the senior managers, and work in a low-profile way to generate a more productive organizational culture. Developing HR practices with a track record of procedural fairness can help firms do better in downsizings. Careful, firm-specific HR practices can help certain individuals perform better. Treating those employees who leave as alumni rather than deserters can win future business. Good HR policies are presented as having measurable results and helping avoid PR disasters. These are all good ideas, and good HR directors are pursuing them. Such practices can help a firm win a spot on the list of the Best Companies To Work For, but they are not necessarily enough to get the firm on a winning path in the marketplace.

c. HR As Agile Business Partner

In full-throated Agile, HR goes further and embraces the same Agile principles as the business. It becomes in effect a truly Agile partner with the business, not merely moderating support. Here HR, like the business, focuses obsessively on delivering value to external customers, setting aside anything that doesn’t contribute to that goal, descaling work for small autonomous cross-functional teams, and operating as part of a fluid network, rather than a top down bureaucracy.

The way in which these three different roles play out in an organization can be summarized in the following table. It shows that most of the “Agile lite” practices cited in the HBR article reflect “HR as a moderator,” rather than “HR as an Agile business partner:

HR Still Has Ways To Go

The HBR article is right to signal that HR’s transition from “executioner: to “moderator” constitutes relative progress. It may enable HR to escape to a certain extent from its reputation as a generator of fear and loathing. Even with this limited transition though, many HR tasks, such as traditional approaches to recruitment, on-boarding, and program coordination, become obsolete, as do traditional approaches in those areas. HR will require new skills. It will need more IT expertise and deeper knowledge about teams and hands-on supervision.

Yet in adopting the role of moderator, HR falls short of being a business partner in genuine Agile management. Acting as a moderator is not sufficient to make HR part of a winning Agile business. For that to happen, both the business itself and HR must fully embrace Agile.

Appendix: ‘Agile Lite’ Practices cited by HBR

Performance evaluation

More frequent performance assessments, often conducted project by project. Continuous feedback Distinct performance cycles for different functions. Simplifying the performance review process, Separating evaluation from development discussions, Eliminating talent calibration sessions

Coaching

Investing in sharpening managers’ coaching skills. Engaging a full-time professional coach to help all managers give better feedback to employees and, more broadly, to develop internal coaching capabilities.

Teams

Multi-directional feedback for teams. Managers solicit input from others to help them identify and address issues early on. Upward feedback from employees to team leaders and supervisors Apps allow supervisors, coworkers, and clients to give one another immediate feedback from wherever they are Front-line decision rights to operate independently

Compensation

Spot bonuses recognize contributions when they happen Eliminating annual raises for its knowledge workers in favor of adjustments for each job much more frequently, Dropping separate bonuses, rolling the money into base pay.

Recruitment

Using a cross-functional team on all hiring requisitions.

Learning

Online learning modules that employees can access on demand. Using artificial intelligence to generate learning advice

April 2018

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The 10 Most Critical LMS Requirements For Any Online Training Program

Presenting  A List Of  Top LMS Requirements For Modern Online Training

You don’t.

When shopping for an LMS, look beyond bells and whistles and sleek presentations. Instead, zero in on the most critical Learning Management System requirements your organization truly needs and can use.

And focus on those features capable of bringing definable value, either in increased ROI or improved KPIs.

1. Robust Analytics And Report Generation

Robust analytics and report generation ranks as a must-have tool in any LMS. Within the LMS, an easily-accessed dashboard should let you pull down progress reports and other learner data. Also, it should include an application program interface (API) or webhook that leverages data to trigger an automatic task in the system.

This might mean giving a badge to a learner who has passed a specific milestone. Or, for example, consider an account that has been suspended because the customer, partner, or employee requires more training: Once the user has gone through the remedial instruction you determine, the API or webhook automatically reactivates the account.

Related reading: New Tech is Sparking a Bright Future for Learning & Development

Confirm also that the reporting function can be adapted to your specific requirements. The LMS will, of course, track how many users have completed the course and the time spent on a task.

But those statistics do not indicate real user engagement or whether the LMS has had any real impact on your business goals. So, you don’t want to lose track of the question of which success metric you should measure by utilizing the LMS.

Those metrics could be more sales volume, more applicants, or fewer support calls.Whichever measurement you set, the LMS must reflect that information in its assessment data as well instructional materials. Instead of relying on a standard reporting template, create your unique model within the LMS.

2. Course Authoring Capability

In addition to delivering and tracking the eLearning program, an LMS also creates and hosts the instructional content.

Many modern LMSs, like Northpass, contain course authoring tools. This permits your organization to create content-rich text activities, audio, videos, visuals—within the LMS itself. Without that capability, you would need to originate the content via a separate creation software, like Captivate or Articulate, and then import it into your LMS. An LMS with an embedded natural course authoring tool eliminates that step.

Another factor to consider when creating courses within an LMS is whether the software is SCORM 1.2 compliant. If so, the LMS will then accept all the instructional content in whatever format without any technical glitches.

3. Scalable Content Hosting

Similarly, as your LMS hosts your content, you’ll want the ability to make updates to the courses effortlessly. As your organization grows, you'll require an LMS that can welcome more learners and undergo any necessary upgrades as learning requirements shift to match organizational needs.

Further, if you have assets, objects, or activities embedded in several courses, the LMS should allow you to alter those elements in every place they are used rather than having to upload the changes multiple times in multiple areas.

4. Certifications

If your organization trains a great many external users—such as channel partners, resellers, customers, and service agents—certifications provide assurance that those extended enterprise groups are appropriately trained in your product.

Besides the training aspect, certifications elevate an organization’s brand value and build an ecosystem of users. For example, HubSpot Academy certifies inbound marketers, which serves the dual purpose of producing more expert marketers while also reinforcing HubSpot’s market-leading expertise in that area.

5. Integrations

Your LMS should never operate on an island. The ability to integrate with other SaaS software ranks as an essential requirement.

Like most modern organizations, you probably utilize a host of software programs, whether for CRM (SalesForce); employee onboarding (fountain), virtual classrooms (GoToTraining), HR (BambooHR), as well as Google Analytics. Through the API, have the vendor or your internal staff configure the LMS so it can exchange information—such as user records—with those programs.

6. Community And Collaboration

As they progress through the LMS, learners at specific points may want to reach out to internal experts or other users. This exchange of ideas and knowledge fosters a sense of community and keeps learners engaged in the process. eLearning works well when it is delivered in conjunction with peer-to-peer and other personal interactions.

A social networking platform, discussion boards, file sharing, and virtual chats enable learners to collaborate and share ideas.

These social learning communities also offer a window into how learners are progressing through the program: Are there areas where users need more help? Do they desire training in an area you hadn’t considered previously? Use that data to develop courses your users want. Or you can gather user-generated content to create more courses and information useful to your learners.

7. White-Labeling Vs. Branding

Most LMSs allow the organization to add its logo and brand name throughout the learning program. This feature lets you shape the look of the LMS somewhat.

This feature is often called white-labeling, but it would better be referred to as branding. There is more to white-labeling than merely changing the colors or adding a logo. Double check the LMS features list to ensure you get full control of the CSS/HTML editor for advanced customizations.

8. Mobile Capability

Today’s eLearning takes place on several devices: a desktop, tablet, or smartphone, and sometimes all 3. To optimize the learning experience, the content must adapt to any device.

A course authoring tool or LMS should enable the content to fit on any screen size, thereby delivering instruction in an easy to read format. It also means the learner can advance through the LMS from whichever device he or she chooses to use.

9. Customer Support And Success

Customer support entails more than having a help desk to call when glitches or other problems occur. Optimal customer support goes beyond just an 800 line for technical questions.

In that regard, you might want to know if the LMS handles support internally, or is it outsourced to a third-party? Do they assign an account representative who oversees the partnership from the first day and through every step of the process?

And the relationship between you and your LMS vendor must be a valid partnership, not one that ends after installation or deployment. Today’s customer support revolves around ongoing customer success.

Avoid an LMS vendor that offers only a boilerplate implementation solution. Partner with an LMS vendor that takes the time to know your business challenges and how the LMS can overcome those obstacles.The LMS in-house experts should understand your instructional needs so they can make recommendations based on your unique case.

This leads to customer support that is proactive, not reactive, and an association based on ensuring your success.

10. The Key Learning Management System Requirement: Supporting Your Mission And Culture

Perhaps the most critical element of an LMS is whether it supports your organization's mission and culture. So ask yourself these questions:

Are we a fast-moving, innovative company whose training needs change quickly? If so, is the LMS agile enough to pivot with those rapid shifts? What do we want to use the LMS for?  Do we require an LMS solely for skills building or dispensing technical know-how? Or, do we envision the LMS as a platform to build the overall industry expertise of our customers, channel partners workforce?  Is the LMS more about supporting our brand values?

Lastly, since we live in an era that places a premium on User Experience (UX), find an LMS that supports a terrific UX for your users. There’s no better way to show how valued your users are to you than by providing them with a smooth UX as they progress through the LMS—especially onboarding. Plus, great UX keeps learners engaged.

As you review your LMS requirements and start comparing vendor partners, it is easy to be dazzled by a lengthy list ofoptions—they all sound so appealing. But to pick the right LMS for your needs, remember to let the purchase be guided by the features and requirements most valuable to your organization.

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The Importance Of Training Staff When Upgrading IT Systems

Upgrading your business IT systems

IT is an increasingly important element in businesses. It has completely changed the way we work, at all levels of the company, from communicating with colleagues and customers, to making informed decisions using data insights.

New business technologies are being created all the time, with exciting new developments which can assist staff members in meeting higher demands and working faster, more flexibly and more efficiently. But without the necessary experience, education or knowledge to use the latest programs and tools effectively, employees can feel frustrated, limited and stressed, which can have a negative impact on their motivation, efficiency and performance.

It is crucial for your business to maintain its IT systems on an ongoing basis and upgrade as necessary. But deciding on the upgrades and getting someone to do the work isn’t the only thing you need to plan- you should also think about your staff and how they will navigate the new systems.

Why should you train staff with new IT systems?

With new IT systems, whether you have changed the operating system, installed new software or added a new piece of hardware, staff will be faced with a change and a new way of doing things.

To minimise stress and increase the performance of staff using these tools, training is essential. This can allow your team to utilise new tools and make use of the additional capabilities, which could make their job easier and more efficient. There are a number of companies available to provide computer training, from basic level Microsoft training to a much more advanced programs and functions.

Unfortunately, many of the businesses that overlook training will later face difficulties. We’ve taken a look at some of the reasons why training is important for system upgrades and changes:

To minimise confusion and mistakes when the new system is implemented To ensure that staff are able to take full advantage of new features To ensure that the budget spent on the upgrade is not wasted To minimise unnecessary work for IT staff solving minor problems To make staff feel valued and empowered by updating their skills What else to consider

When IT systems are being planned, it is important that that your staff has some say from the start. Although everyone is likely to have different opinions, you may get some useful ideas. This is an important way to get your staff behind the IT changes, for a much higher level of adoption for the new technology. You don’t want to spend lots of money on new systems, only for your staff to revert back to their traditional methods.

Training will help to avoid this, as they will be more confident with the functionality of the programs they use. However, it shouldn’t end there. Not everyone can master something within a day, and as employees use the tool, there may be additional questions. Make sure that there is effective support for employees after the training takes place, whether this is internally or via a phone helpline.

Most importantly, look at the big picture. Don’t hold off on training because it costs money or will take time. Staff who cannot use a system to carry out their job will be less efficient and less motivated. They may even leave, which will cost time and money in recruiting efforts. It’s important to deal with problems before they arise, by ensuring that your staff is properly trained from the start with any IT systems that are being implemented. Help your team use these systems to get the most out of the job, and the business will get the most out of their investment.

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IT Systems Training with Impact: A behaviour change-based approach

You might know the best process for delivering systems training – but what can you do to design that training so that it delivers real, measurable impact?

"Knowing is not enough; we must apply. Willing is not enough; we must do."
– Johann Wolfgang von Goethe
 

Goethe seems to have measurable impact nailed. I'm not entirely sure he was thinking about systems training when he said that, but to me it sums up measurable impact pretty perfectly.

Because when we talk about measurable impact or results (which in digital learning we do… a lot), we're really talking about changes we can observe and measure. What are people doing differently as a result of the training? How have their behaviours changed?

Every piece of systems training is different and will target different learning environments and objectives, but here are a few common scenarios:

Scenario 1: You have a new system and you want your learners to get up to speed with using it as soon as possible. Scenario 2: You've upgraded a system and need your learners need to adapt the way they currently use it. Scenario 3: Or maybe your system hasn't changed at all, but you need to iron out non-standard behaviours in the way your learners currently use the system.

In any of these scenarios, the overall goal of the training is to embed new behaviours and capabilities. And that's where theories on behaviour change can help inform your design.


The COM-B model for behaviour change

There are a number of different behavioural change models, but recently at Brightwave we've been looking at the COM-B model.

The COM-B model is widely used in government and public sector organizations as a framework for exploring the factors that generate behaviour change and how they each interact.

The three factors are:

Capability: This means a person's knowledge and skills. What is the person's current knowledge and skill level. Opportunity: This refers to all the factors around a person that could make the desired behaviour possible. What prompts or changes could be put in place? Motivation: What motivates that person to make decisions or do what they do? What are their habits or routines?

Once each of these three areas has been evaluated, you can then identify what types oflearning intervention will be effective to bring about the desired behaviour change.

A good way to think about it is: what are the enablers and blockers to the behaviour change, and how do they interact?

A short analysis using Com-B

So let's think about how this would work in the context of systems training project.

Take scenario 3 as an example:

"Your system hasn't changed at all but you need to iron out non-standard behaviours in the way your learners currently use the system."

Capability
The learners already know how to use the system but may be lacking knowledge in certain areas, which is leading to errors and non-standard behaviour.

Opportunity 

What are the enablers that could make the behaviour change possible?

The overall opportunity is essentially our learning blend, but this could be made up of various different solutions:

Digital learning Face to face training

There could also be physical or environment opportunities; what can change about the learners' working environment that might make the behaviour change easier?

For example:

Performance support material Mentoring and support Technology or IT support

Motivation
On one side, this is evaluating what the learner is currently doing and why they're doing it. On the other, it's looking at ways to motivate the learner to change their behaviour.

For example, a learner might be motivated to use the system in non-standard ways because it's quicker and they don't want to spend additional time filling in extra fields etc.

"Motivation is the art of getting people to do what you want them to do because they want to do it."
– Dwight D. Eisenhower


But perhaps after questioning your learners, you find out that they'd be motivated to use the system correctly if it would save them time on admin tasks and improve data management.

What does this analysis tell us?

This is a very brief example evaluation, but you can see that by analysing the three factors of Capability, Opportunity and Motivation, you can identify the enablers – but more importantly the key gaps (or blockers) – your training needs to target to produce real behavioural change and therefore, measurable business impact.

Learners need to:

Understand how to use the system to close knowledge gaps that are barriers to behaviour change Have an environment and learning solution that makes closing these knowledge gaps as easy and pain-free as possible Relate to why they should use the system correctly so they are motivated to understand the learning and adopt the new behaviours and shed the old ones. 

What can we take from it?
I think we're all familiar with number 1: this is the heart of what our solution needs to achieve. I'm not going to ponder on the best approach to do this as that's probably a whole other article itself. But I think the key thing we can take from the Com-B model is that this part of the solution shouldn’t be considered in insolation to the other factors.

That means when designing your learning solution, think not just about what knowledge needs to drum into your learners' brains but how your solution can stimulate motivation and engagement too – because these factors are key to real change.

And alongside that, consider the opportunities you can leverage to make the learning process take place with the least friction possible. What will make new behaviours easier to stick to in the long term - it could be on-the-job aides, in-system pop-up reminders or support roles?
 

Motivation - the missing part of the puzzle?

But for me, ultimately it's the motivation factor of the Com- B model that is most useful when it comes to thinking about systems training and behaviour change.

Because motivation is often overlooked in systems training design as capability related objectives tend to take a front seat. It's easy to focus on the knowledge gaps that need to be filled rather than why our learners should be motivated to fill those gaps! The benefit of the Com-B model is that it forces you to explore motivation from all angles.

What can you do?

So how can you get your learners fired up to get to grips with your system? After all, I think we'd all admit it's not the most exciting of subjects…

But unlike other types of training, systems often has a direct impact in our learner's jobs. Small changes in behaviour here can add up to significant personal benefits over time. It's highly likely that they'll be using the system every day or week.

That gives you a direct line into what gets them fired up.

Think about it: I'm sitting here writing in a word processing program I use every single day. I could definitely tell you a thing or two about my frustrations and aspirations for this particular piece of software… and if someone offered me a chance to really get to grips with it, I’d be very grateful!

That's because I can recognise how using this program in the right way would make my job easier and more productive. It's not something that keeps me awake at night but it's definitely something I'd be motivated to do.

In the same way, we want to get our learners to understand why this our training is going to make their lives better.
That means really thinking about why your learners, not just your organisation, will benefit from the training. So of course, increased profit margins, better efficiencies etc. may be a key part of the reason why you've commissioned the training, but that might not be what resonates with your learners.

"If you talk to a man in a language he understands, that goes to his head. If you talk to him in his language, that goes to his heart."
– Nelson Mandela


For example, imagine you're introducing a new system. Of course this is going to be a big upheaval for your learners. But perhaps think about the frustrations they may have with the old system and communicate how the new improved system will make their jobs easier. Being transparent and honest, speaking in your learner's language, is how to generate the necessary enthusiasm.
 

In closing…

Hopefully this short investigation into the Com-B model has piqued your interest. Why not try it out on your next project, and see what insights it opens up for you? And most importantly don't neglect to design for motivation. After all it's what keeps us all striving, working and, well – learning.

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There’s a Data Analyst on the L&D Team?

Employees and their managers want to know if training measurably improves performance. CEOs and senior leaders are asking, “Where’s the evidence for learning and development’s impact on business results?” CFOs are asking, “What’s the return on investment for the dollars we spend on employee development?” There’s a rise in demand for L&D talent who can answer these questions with evidence and proof.

Data Analysts: A New Breed of L&D Talent

A new breed of L&D talent is using data and analytics to answer questions about learning’s impact on business results and employee performance. L&D data analysts use analytics to inform decisions about learning strategy and data for learning solutions design, deployment and investment. And while the titles may be different from company to company, the focus on learning and development analytics is the same:

“Ability to negotiate data sourcing agreements with stakeholder partners” – Learning & Development Analyst “Uses data analytics to offer Leadership/Strategy Committee insights from across the Learning and Development portfolio” – Learning & Development Measurement & Analytics Data Scientist “Leverage the workforce analytics knowledge base to promote an evidence-based approach to all things Learning” – Associate Director, Learning Analytics

“Research,” “analysis” and “measurement” describe the focus. “Data collection” and “visualization” describe the skills. Experience with SPSS, SAS, Tableau, xAPI and learning record stores (LRS) qualify the specialized expertise. These are capabilities that just a few short years ago, you would not have seen on an L&D team.

The combination of learning, development and analytics talent is unique and creates an opportunity for established L&D professionals to reinvent themselves. With the rise in demand for talent with strong L&D backgrounds and expertise in analytics techniques and technology, there’s a brand new function in learning and development. The future for L&D analysts is bright!

There's a rise in demand for talent with strong L&D backgrounds and expertise in analytics techniques and technology.

What’s Driving the Rise in Demand for L&D Analysts?

Learning analytics expert Mike Rustici with Watershed suggests the rise in demand for L&D data analysts comes from increased accountability and transfer of best practices. “Just about every group, department and function across the enterprise is held accountable for using data to demonstrate results. You’re seeing an increased desire from senior leadership for that level of accountability throughout the organization. You’re seeing people coming into L&D leadership roles from other parts of the organization. They’re bringing their expertise and best-practices with them including the infusion of data and analytics.”

Christopher Yates, head of learning and development at Microsoft, sees L&D data analysts as a critical part of the digital transformation. “It’s essential. I can’t imagine having an L&D team today that is not supported by dedicated data analysts. Without L&D analytics, you’re basing your decisions on luck or the way we’ve always done things. Without insight, all you have is a guess, a hunch or a feeling in your stomach about what’s working or not working.”

L&D Data Analysts Are Here to Stay

There’s technique, technology and, now, talent for L&D analytics. The dynamics of complex learning ecosystems require data-driven design for learning solutions and analytics for insights on L&D performance. We don’t have to cross our fingers and hope learning and development fulfills its purpose. We have the data and the L&D analysts to prove it.

L&D data analysts are changing the way learning and development leaders build their teams. As L&D is increasingly held accountable for evidence that shows impact, so will the rise in demand for talent who can use data and analytics as proof for results. Yes…there’s a data analyst on the L&D team, and they’re here to stay!

March 2018

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A Starter Kit for Instructional Designers

A 2016 report funded by the Gates Foundation found that in the U.S. alone, there are 13,000 instructional designers. Yet, when I graduated from college in 2008, I didn’t know this field existed. Surely a lot has changed!

Instructional design is experiencing a renaissance. As online course platforms proliferate, institutions of all shapes and sizes realize that they’ll need to translate content into digital forms. Designing online learning experiences is essential to training employees, mobilizing customers, serving students, building marketing channels, and sustaining business models.

The field has deep roots in distance education, human computer interaction, and visual design. But I’ve come to believe that contemporary instructional design sits at the intersection of three core disciplines: learning science, human-centered design, and digital marketing. It requires a deep respect for the pedagogical practices that teachers have honed for decades, balanced with fluency in today’s digital tools.

Most people with “instructional design” in their job title are involved in converting “traditional” written curriculum or in-person teaching into an online course. But they can also be creating learning apps, museum exhibits, or the latest educational toy. My classmates from Stanford’s Learning Design and Technology master’s program have gone on to design for big brands like Airbnb and Google as well as edtech upstarts including the African Leadership University, General Assembly, Osmo and Udacity.

Over the last few years, we’ve traded resources, articles and work samples as we try to build our own starter kit for this fast-moving field. Below are some of the lessons and resources that I wish I knew of when I first went on the job market—a combination of the academic texts you read in school along with practical tools that have been essential to practicing instructional design in the real world. This is not a complete or evergreen list, but hopefully it’s a helpful start.

Lesson 1: Start with a deep understanding of your learners.

No matter what type of learning experience you’re building, it’s always smart to start getting to know the people you’re designing for. To conduct learner research it’s helpful to combine practices from design thinking with those of participatory research or teacher action research that educators have been practicing for many years.

I typically start by developing an Empathy Guide like the one put together by the Stanford d.school or reviewing the free book by Giff Constable, “Talking to Humans” to structure productive conversations. After conducting observations and interviews with target learners, I synthesize my findings into learner archetypes.

Then, I test instructional concepts and product ideas by building rough prototypes that I put in front of learners to get their feedback quickly. The d.school has a great Prototyping Dashboard you can use to organize the hypotheses. If you’re looking for a crash course in the entire design thinking process, you can check out the free courseoffered by IDEO.org or the free resources from IDEO’s Teacher’s Guild.

Lesson 2: Ground yourself in the fundamentals of learning science.

Teachers have spent decades learning how to reliably help students master new skills, debunk misconceptions, and connect their prior knowledge to new concepts. To be a good instructional designer, you should steep yourself in the research on learning and teaching. The best and most digestible books I’ve found are “The ABCS of How We Learn,” a 2016 book by Daniel Schwartz and “How People Learn,” the 1999 foundational text edited by John Bransford, Ann Brown, and Rodney Cocking. If you’re looking for a crash course in digital education specifically, recordings from Stanford’s lecture series on Education’s Digital Future are all available for free online.

Lesson 3: Determine the “powerful ideas” you want to teach and build your curriculum using backwards design.

To get serious about education technology, you have to read Seymour Papert. His “Mindstorms: Children, Computer and Powerful Ideas” is a classic that is critical to helping you realize that all the ideas about edtech that we think are so unprecedented have actually been mulled over for decades. Pay particular attention to his chapter on “powerful ideas” where he describes how essential it is to find the enduring, transformative concepts that you want to teach and put those at the forefront of your design approach.

Once you’ve read Papert, use the Understanding By Design Framework to structure your curriculum. This approach helps you clarify your target outcomes and how you’ll collect “evidence of learning.” This curriculum design approach is used by teachers who work in traditional classrooms, but holds up just as well in the digital realm.

Lesson 4: Go study other great teachers and other great learning experiences.

Before becoming too beholden to the particular features (or limitations) of a technology platform, try to think bigger and more creatively about how you can meet the needs of your learners. One of the best ways to do this is to seek out inspiration from other learning designers. For example, look at the examples of host educationthat Airbnb puts together. Look at the altMBA program that Seth Godin runs using Slack. Watch how Angela Duckworth delivers messages to camera. Check out the beautiful animations produced by Amnesty International or the interactive lessons produced on Oppia. And look at examples of tangible rather than screen-based technologies that have been produced by groups like Paulo Blikstein’s Transformative Learning Technologies Lab.

Rather than limiting yourself to looking at educational resources produced by schools or universities, find examples of instructional materials from other sectors to get ideas. The field is so new that there are no definitive ways to do it “right” and lots of approaches are worth learning from.

Lesson 5. Get a lay of the technological landscape, but don’t let your LMS hold you hostage.

If you’re going to be an instructional designer who specializes in online courses, you should get familiar with your platform options and be prepared to speak to the pros and cons of each. Start with the “big four” that most people have heard of: Coursera, Udacity, Udemy, and EdX. Check out the list of global MOOC platforms curated by Class Central, but realize there are entirely different ecosystems of platforms that specialize in corporate training or adaptive learning. Then also read some critical perspectives from the likes of Digital Pedagogy Lab or the MIT Media Lab.

No current online education platform is perfect, but focus on being able to speak to the distinctions between them and make a recommendation based on the learning goals. You don’t need to master all of the options, but it’s helpful to keep a pulse on the major players. Perhaps more importantly, design content and learning experiences that are “platform agnostic,” meaning that you can easily transport them to another platform. Finally, check out the blogs of online learning pioneers like Connie Malmud who have been chronicling the field for many years and who has helpfully compiled a glossary of common terms.

  Lesson 6. Don’t try to migrate an in-person experience into an online format.

One of the biggest mistakes people who are new to instructional design make is trying to replicate or simply migrate an offline experience onto an online platform. Instead, the better approach is to think about what the technology can do uniquely well and then design your experience to leverage those affordances. Allan Collins and Richard Halverson’s book, “Rethinking Education in the Age of Technology,” is a useful place to start, along with the perspectives and research of Mitch Resnick and the late Edith Ackermann of the MIT Media Lab.

Lesson 7: If you build it, they won’t come. Understand the fundamentals of digital marketing.

People will not automatically show up for your online course—unless you’re working for a big-name institution like Y Combinator or Harvard University. As online courses have proliferated, the market for students has also fragmented. To be an effective instructional designer, you also arguably need to know the basics of digital marketing and how to write compelling copy to get someone to click through, enroll in, and persist in your course.

One useful post on strategies to drive enrollment and sales of an online course was produced by the founders of Groove. Udemy has also created a great toolkit to help online course instructors market their learning experience. These strategies might seem distasteful to people whose primary focus is learning outcomes, but the reality is that if you don’t attract the right population of students to your courses (even if they’re free), all of your hard work and pedagogical design is moot.

Lesson 8: Collect student feedback. Iterate. Share what you learned.

Finally, perhaps one of the most important lessons is to get out from behind your computer and actually go meet the learners who experience your courses, apps or experiences. Set up Skype calls to interview them. Pore through the feedback they submit on surveys.

Some of their input will inevitably sting—especially when you’ve spent months building a course and someone only watches two videos before leaving a scathing review. But listen for the underlying pain points. Synthesize your feedback carefully and make changes, but avoid designing by committee. Finally, share your data, your lessons, and your failures with the broader learning design community when possible.

The field is fast-moving but still has a lot to figure out. The more creative pioneers we have who are pushing the boundaries of how to design compelling, thoughtful learning experiences in new formats, the better.

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What You Need To Remember During eLearning Project Reviews

A successful eLearning project stands on multiple pillars and involves many aspects that ensure success. With a variety of stakeholders, like instructional designers, subject matter experts, project managers, end learners etc., collaboration and review are essential to ensure a successful eLearning course development process.

What are the challenges that need to be covered during eLearning project review?

Instructional designers and project manager have to ensure that pre-requisites and needs of the project have been duly met. The learning objective identified in the analysis phase of the eLearning course development process should be kept true to. The pain points of the learners have been considered. The learning environment and its constraints have been accounted for.

Reviewing a course is essential to ensure quality and that goals are being met. Here are some of the things to remember when reviewing eLearning courses:

Stakeholder satisfaction

Every eLearning project has a multitude of stakeholders. The success of the course, whether developed in-house or by an agency, is influenced by how satisfied the stakeholders are with the results and output of the project.

  source: kyanite consulting Defining scope and expectations

For each stakeholder, one thing that helps keep everything focused is defining the scope and expectations of during each phase of eLearning review.

Establishing scope makes sure that reviews are better from both a qualitative as well as quantitative perspective. Though key stakeholders share reviews during each iteration, what makes the process better is if kind of feedbackexpected is specified before each iteration.

For example, for an eLearning storyboard review, the focus of feedback should be content. At the implementation stage, the focus of eLearning feedback should be responsiveness and delivery method. Doing this can save teams from getting entangled in pointless issues that are not relevant at that particular stage.

Timely feedback management

For project managers, the task is then to create a strategy to collect and prioritize eLearning feedback. No matter what eLearning methodology is being used, stakeholders need to be kept in the loop on what feedback is being processed through.

In order to achieve a satisfactory project, one practice that teams need to adopt is exchanging feedback early and often. Teams that are using the Successive Approximation Model (SAM) as an eLearning methodology are already work with an agile process of course development that presses the importance of evaluation when developing iterations of your eLearning design. For teams using the ADDIE (Analysis-Design-Development-Implementation-Evaluation) as an eLearning methodology, contextual feedback is even more critical, as it helps log issues and provide background in the next iteration.

A good way to make sure that stakeholders are onboard from start to finish is to create prototypes or mocks initially, and then build up the project once validation has been received. This way the chances that the end project works for everyone is higher. Kineo shared a framework for stakeholder management that lays out steps for ensuring better engagement. These include:

identifying stakeholders prioritizing among them determining level of support needed from each identifying messages and actions identifying ‘owners’ for each stakeholder meeting stakeholders, and reviewing regularly Learner Driven Iterations

The success of an eLearning course development process for end learners is seeded in how much they can retain and transfer into practical application. Whether developing eLearning for students or corporate learning solutions, unless learners are able to transfer their learning from out of the learning environment, the course is not achieving its intended goal.

Thus, learner feedback is vital when reviewing eLearning projects.

  source: Shift Learning Evaluating engagement and retention

Surveys are one option. They provide a simple and consistent way to measure how learners react to the course. Have they been satisfied with the eLearning content? What could be improved? How would they rate the course? Such quantitative data can be gathered via surveys easily. This method may be easier when developing corporate learning solutions because of the one-on-one interaction learners have with the course. In case of eLearning for students in schools, blended courses may also need feedback from teachers and instructors.

But what about qualitative eLearning feedback? Typically such feedback is gathered during alpha and beta tests, by asking learners to try new modulesbefore they are added to a course. To gather qualitative feedback during alpha and beta tests, instructional designers and project managers can use zipBoard. Learners can mark up screen shots of the course, and leave their comments on those screens so that eLearning reviews have more context.

When to ask for feedback

The other question is when this feedback should be collected. Of course, as with other stakeholders, getting feedback as quickly as possible is beneficial even from learners because it helps make corrections early on rather than later at the cost of time, effort and resources. But what is certainly not a good time to solicit feedback is right at the end of a course.

Apart from the alpha and beta phases, building review cycles into the course is one way. Trying to collect feedback right at the end of an eLearning course development process can often be unproductive as it does not give the learner enough time to process all the eLearning content they have consumed, and also makes them provide feedback for the entire course in one go. Rather, check points in the course for collecting feedback work better. These checkpoints can be implemented in your eLearning templates itself so that there is a standard process in place.

Quality assurance

Quality assurance checks are vital to make sure the details are accurate and consistent. Issues such as the right image being in the right place, videos functioning as intended, spelling and grammar checks — all need to be reviewed to assess the course.

For a lot of teams, their QA and testing process still consists of Excel sheetswith columns for issue name, description, priority, person assigned to etc. This method has two problems.

source: BA Times Challenges in quality assurance It does not scale well as volume of feedback and teams grow. Excel sheets may work for a team of 2–3 people but as the number starts to grow to five or seven or into double digits, tasks get muddled and difficult to organize, feedback breaks down, tracking changes becomes tedious, and ultimately issues become overwhelming. It provides no context. There are no visuals which can lead to ambiguity. Defining the problems at their exact location and capturing them with annotations helps other collaborators see specifics and save time when implementing changes. Better eLearning tools and processes

An effective alternative is zipBoard, which provides a systematic task management workflow and also the option to annotate and communicate via comments on a live as well as mock course.

QA can be more effective not only by using better eLearning tools, but also by setting up more effective processes. One such practice is setting a dedicated number of review cycles, depending on the complexity of the course and the number of stakeholders involved. Especially when working with subject matter experts, an effective QA setup can cut down on a lot of hassle.

Andy Petroski, an eLearning project manager with nearly two decades of experience, talked of how every step of their development process is followed by SME review and feedback. While the development team can ensure functionality, SMEs can check for accuracy and consistency. This setup also highlights why collecting feedback early and often is useful because it helps with stakeholder satisfaction.

Value Matters

A better review process will enable teams to create more value in the project. Each and every aspect — curriculum, eLearning design, course content, and delivery system — can be improved to add more value for the client. The end result is quality work delivered in the allocated time.

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Measuring Learning Will Be Key to Improving It in 2018

There is a popular quote attributed to management expert Peter Drucker: “What gets measured gets improved.” In education, the mantra is equally true. However, since I began working in edtech five years ago, I have been continuously surprised by how little emphasis there is on measuring changes and progress in individual learning, especially in higher education.

This is particularly concerning given that it’s difficult to improve learning if we can’t measure it. However, I think attitudes around why it’s important to track a learner’s progress, and how to accomplish it, are starting to change. With better tooling and more emphasis, we'll see significant progress in 2018.

The most obvious sign that measuring learning is not a priority in higher-ed is that administrators and educators throw away so much data about it. Instructors grade the vast majority of high-stakes summative assessments on paper, and collapse student performance down to a single number for entry into the grade book. Instructors spend hours looking at how each student arrives at an answer, figuring out where they went right or wrong, giving them feedback—but then compress all of that information down to a single grade that omits the nuance and specific areas of improvement for a student. 

Holding on to this kind of data, however, is crucial for measuring students abilities and learning. And keeping information that would have otherwise been discarded after grading could lead to better outcomes within a course. For example, if it were easier for instructors to record student performance on specific learning outcomes, instructors could track progress across assignments. This kind of insight could give an instructor a data-informed prediction of how students might do on future assignments, and enable them to provide targeted interventions to give students extra support before the test. 

Without technology, this process may involve a professor going back and digging through old assignments to get an idea of where a student was once at, and comparing it to their latest work. Over the next year, we will see more technologies stepping in to do that digging for instructors, giving them an easy way to view a student’s performance over time and thus more bandwidth to focus on students themselves.

One trend that is picking up steam is the demands by educational technologists that institutions have access to all of the data that pass through technology solutions, often using standard formats like Caliper and xAPI. Administrators I have spoken with say they have set up data warehouses that allow learning analysts to build these types of tools using the full range of data available on campus.

Data isn’t a silver bullet, however. The more an instructor is able to provide meaning to the data, the more useful the insights derived from the data will be. Another emerging trend in higher education is the push for instructors to be more rigorous about defining learning objectives for their course. Taking it one step further, more instructors are also starting to assess their students via standards-based grading, where students are assessed against defined learning objectives. Together, these trends will make it much easier for instructors to understand the strengths and weaknesses of their students.

The more an instructor is able to provide meaning to the data, the more useful the insights derived from the data will be.

The same data would help in improving repeated offerings of the same course. If instructors could effortlessly measure student progress on every learning outcome, they would have the information they need to understand which parts of their courses need the most attention. 

Data on how students perform across a sequence of courses is plentiful. Ad-hoc analyses of this data are periodically performed, for example, when planning the curriculum for a major. These analyses often lead to information such as “students who take Math 1 before CS 2 generally score a half letter grade higher.” The ad-hoc nature of these kinds of studies, however, limit their ability to regularly capture information. Automating these kinds of trackers would thus allow for instructors to regularly use act upon student data, and improve their teaching in the process. 

Benefits of this kind of technology would start start at day one. For instance, instructors could be presented with a report about their students on the very first day of the course, eliminating the need to test students on prerequisite material.

Gathering and synthesizing information about student learning and performance won’t only be useful for faculty to see, but students could gain valuable information about their own progress as well. For example, when instructors define and assess against learning objects, student could see their progress in attaining those objectives. 

Every industry in the world is hungry for data to improve its workings. Education is unique in that data is actually plentiful—it just hasn't been captured and connected in the right way yet. I look forward to less data being discarded and seeing silos broken down in 2018.

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3 Popular EdTech Platforms You Need to Know

Education Ecosystem

Education Ecosystem(LiveEdu) is working on a Blockchain based professional development platform. They connect different participants like content creators, learners, API developers, moderators, etc. You can register on their platform and learn from industry experts. They reached their ICO hard cap recently. They have an internal ecosystem competition and are giving away a Tesla Model S. Read about it here. Their LEDU tokens are available for purchase on Gate.io(March 1st) or Bibox (March 2nd).

LEDU tokens can be used for various purposes like downloading course materials, requesting custom projects, getting replies from the content creator, etc. The more you learn, the more you earn. You earn tokens for watching project videos, submitting project suggestions, inviting friends etc. You also get rewarded for being a community moderator. You get rewarded for quality assurance activities such as reporting bugs, content moderation, etc. Education Ecosystem incentivises its content creators. They receive tokens for creating content. The more learners engage with the content the more its creator is rewarded.

ODEM

ODEM is a decentralised education marketplace. ODEM connects students and professors directly. Individual attention can be improved with one-one interaction. This is a value add MOOCs fail to provide.They use smart contracts to mediate financial relationships between its members (eg. students, tutors) and remove intermediaries. Hence drastically reducing cost. Their crowdsale is still going on.

BitDegree

Bitdegree bridges the gap between industry needs and student skills. This happens because study materials are hardly updated. Blockchain Developers are gonna be in huge demand in the coming years. In India having Blockchain Development listed in the curriculum is years away. BitDigree is already launching a solidity course on March 2nd. They even connect students with employers. This increases your chances of getting hired.

We still need a lot more ideas for Education in Blockchain. I feel this sector is yet to be disrupted. I suggest you take this free course on solidity programming in CryptoZombies (It’s fun). Hack around, write a few contracts and who knows you may be upto something. You should also checkout the free hyperledger course in EdX by Linux Foundation. The other sector which would see immediate disruption is on Private Permissioned Blockchains.

February 2018

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Smart List: 30 High-Quality Learning Platforms

Platforms can help EdLeaders, administrators and educators accomplish a variety of challenging tasks, such as powering and tracking personal learning plans, managing assignments and dynamic grouping, supporting the development of standards-aligned projects, combining formative assessment in a standards-based grade book, and connecting students, parents and teachers anywhere on any device.

Today we’re recognizing 30 platform providers who deserve a round of applause–if you’re interested in learning more, see our past Smart Bundle on how (and which) platforms can help you accomplish your goals.

Comprehensive K-12 Platforms (LMS & content)

Apex: Digital curriculum designed to actively engage students in learning, combining embedded supports and scaffolds Connections Learning: Provides K-12 online courses on the Connexus platform Edgenuity: A comprehensive set of online and blended content and management offerings Edmentum: Adaptive assessments paired with powerful learning paths for K-8 reading, language arts, and math FuelEd: Innovative digital curriculum, technology, instruction, and support enabling you to create a learning environment that is just right for your students GradPoint: Rigorous online curriculum, assessments, data, and reports in an easy-to-use LMS SevenStar: Online Christian education options for grades 6-12 Summit Learning: A free online tool that helps students and teachers personalize learning

Learning Platforms (See Getting Smart on Next-Gen Learning Platforms)

Agilix: Offers formative assessments, individualized tasks, student-choice activities, and grouping options. (See our feature) Alma: Designed to replace legacy SIS and LMS with a modern data infrastructure that can enable improved student engagement AltSchool: Helps educators engage students, communicate with parents and collaborate with one another Blackboard: Provides a range of LMSs, and is a HigherEd leader; owns Angel and Moodlerooms Desire to Learn: A system with a simple, well-designed interface Edmodo: Enables teachers to create groups, assign homework, schedule quizzes, manage progress and more Edsby: An Ontario-based, K-12 designed, mobile, social and personalized solution Touchpoint by Education Elements: Change management for district-wide programs Fishtree: A Dublin-based, adaptive learner-relationship-management tool (see podcast on Columbus MS) Gaggle: Launched as a safe email service in ‘99, it is now full LMS with safety features Google Classroom: Create classes, distribute assignments and send feedback. (part of G suite for Edu) Canvas by Instructure: A leading higherEd platform that hosts open courses on Canvas.net itslearning: A Norway-based system that started in HigherEd, designed primarily for blended learning Learning.com: Offers a range of content and tools Mileposts from Silverback: Boise-based instructional improvement system catered towards personalized learning Moodle: An open-source, integrated system that helps create personalized learning environments Microsoft Classroom: Classroom and assignment management (part of Office 365 Education) PowerSchool: Purchased Haikau LMS, and combined it with a leading SIS RealizeIt: A Dublin-based adaptive learning platform, mostly focused on HigherEd CTE Revel: HigherEd interactive learning environment that enables students to read, practice and study Sakai: An open-source, flexible alternative to commercial learning systems Schoology: An LMS with robust collaborative tools
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The Best Online Learning Platforms for Business in 2017

What Is an Enterprise Training Platform?

Enterprise training software typically falls into two distinct categories: tools designed for training companies that sell courses and services to third-parties, and tools designed for companies that conduct training with internal staff. How you plan on using your training software will ultimately determine the type of solution you'll need, how you'll be charged, what integrations will be available, and and even what eLearning authoring tool you want to use to create your course content. Our Editors' Choice tool Docebo is a wonderful tool for both sets of purchasers, as well as large and small to midsize businesses (SMBs), and that's one of the many reasons we rated it so highly. However, you'll typically find each vendor caters their training software to one specific kind of buyer.

 

The two kinds of systems are similar in how they operate, but quite different in terms of what they offer: training systems for training companies tend to offer more flexibility in terms of how much content you can store within the system, how many courses and quizzes you can create, how many separate portals (or dashboards) you can create, and how many people can access your content. That's because training companies always attempt to sell their products and services to as many people as possible. If a Fortune 500 company decides it wants to buy a course off of a Firmwater client's website, Firmwater provides the flexibility to onboard thousands of new learners. Conversely, training software for enterprises and SMBs conducting their own internal training tends to offer more restricted access. You'll be able to add a limited set of users and courses, which should be okay because dramatic expansion is unlikely for your company over a short period of time.

The Price Dilemma

The type of tool you choose will dramatically impact how you'll be charged for your software. Firmwater is designed primarily for training companies. It starts at $295 per month, with an unlimited number of users, up to 50 active courses per month, and two client portals. This is an ideal setup for training companies because it doesn't take into account how many users you load into the system. Firmwater's plans increase depending on how many courses and portals you need. There's a $695-per-month plan that includes up to 150 active courses and five portals, and a $1,495-per-month plan that gives you access to 600 active courses per month and 20 portals. But none of these plans limit the amount of learners you can activate.

Systems like LearnUpon and Mindflash offer pricing that is largely dependent on the number of people who will be consistently using the system to train. For reference, LearnUpon starts at $349 per month for 100 active users and 1 client portal, and jumps up to $1,499 per month for 2000 active users and 20 client portals. It can expand beyond the stated maximum capacity for an unspecified price depending on how many users will be using the system, but don't expect to onboard hundreds of thousands of users.

How to Use the Systems

Regardless of the kind of system you'll use, you'll be able to add most content types via upload and then develop quizzes based on the information delivered in your files. You can also use a Sharable Content Object Reference Model(SCORM) platform to create more interactive, dynamic courses combining lessons and quizzes.

Systems are easily sortable by courses, users, quizzes, administrators, and portals. Most novice technology users will be able to access, use, and master these systems with no difficulty. There are, however, some points of contention that you'll need to take into account when making your purchase decisions. For example, some vendors allow you to store unlimited data on their servers whereas other vendors limit the data you can store. This is especially important for companies using video to train staffers. Every vendor we spoke with downgrades the quality of your video file in order to minimize the file size going into their servers. If you plan on using video for your training sessions, use a SCORM platform or add your video files to YouTube, and then add the files as links for streaming within the training software.

E-Commerce, CRM, and Videoconferencing

You'll notice in your search that some training software offers an integrated e-commerce tool. This is highly beneficial for training companies trying to sell courses to users across the web. You'll also notice that training software often integrates with customer relationship management (CRM) tools in order to help companies determine who needs certification for specific roles or how employees perform before and after they use training software to master specific tasks. Live classes are becoming standard in the enterprise training market. However, because some training systems don't offer an integration with a web conferencing tool for live courses, you won't be able to take advantage of this feature.

An excellent example of live course functionality is LearnUpon's integration with WebEx, which enables trainers to mark attendance for anyone who joins or doesn't join a required lesson, and communicate directly with users throughout the course. WizIQ offers an equally impressive live course feature with its own proprietary web conferencing solution. With WizIQ, you can upload documents on the fly to schedule impromptu live sessions. You can schedule live classes in advance, enroll people in recurring live classes, or conduct classes that run 24/7. Live classes are the future of enterprise training software. I suggest buying into a system that does this well.

These integrations and add-ons shouldn't be crucial to your purchase decision-making, but they're definitely worth investigating as some tools (such as Docebo) integrate with dozens of third-party platforms, while other tools (such as Firmwater) offer very few integrations at all.

How Badly Do You Want People Using the System?

One of Docebo's main differentiators is that it offers gamification as part of its training software. Learners earn badges and they appear on company leaderboards—all of which enables you to create healthy competition among your employees. This will hopefully encourage them to enter the system to voluntarily take courses. Both Docebo and WizIQ do an excellent job building environments similar to social media platforms like Facebook and Twitter that encourage users to actually want to log in and take classes.

At the end of the day, you're spending a good deal of money to get people to take courses to become better employees and corporate citizens. Choosing the right system could help to grease the wheels to make this process more enjoyable for everyone involved. Let pricing, usability, extensibility, and enjoyment be your guiding principles when choosing the best enterprise software for you.

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Professor Alex Pentland Banks On Blockchain To Bring Predictive Analytics To The Masses

The world of business today is fast-moving and data-driven, with retailers and merchants of all sizes spending billions to acquire and analyze minute transactional details, hunting for the insights that will give them an edge. The biggest advantage of analyzing this data is the insights it delivers for anticipating consumer behavior, a strategy the financial services industry commonly employs to assess how traders might behave in financial markets.

Predictive analytics remains a complex field, and is still far removed from the average person. For new industries like the world of crypto,, the field is essentially non-existent, and some believe this is the reason why cryptocurrencies are so volatile. It’s hard to predict what the future holds, but one man, MIT Professor Alex Pentland, believes his company Endor holds the answer.

Pentland, who was listed among the 7 most powerful data scientists by Forbes, co-founded Endor together with Dr. Yaniv Altshuler - a colleague from MIT - and is a noted leader at the World Economic Forum, a founding member of Google’s advisory board and published author of books including Social Physics and Honest Signals. Using social physics, Pentland is helping Endor bring proven deep learning techniques to predictive analytics and cryptocurrency markets, with the goal of making them more foreseeable and therefore more profitable.

I've had a chance to talk with Pentland, and gain a better understanding of the capabilities social physics exhibits, and how Endor might apply these findings to accomplish in cryptocurrency what few analytic entrants have thus far attempted.

Q: What is social physics? How is Endor using it?

Pentland: Social Physics is the science of using statistics to find "laws" or "universals" in human crowd behavior. The phrase was coined in the early 1800s, and first implementation was the census that each country conducts to detect trends in population, migration, and the economy. Today we can do much more using "big data", including especially cryptocurrency trading and blockchain transactions data.

 

Q: Tell me about the evolution of predictive analytics. What are the major challenges and opportunities you’ve identified?

Pentland: The biggest challenge is dealing with change. Human society is constantly changing, which means that behavior, supply chains, or trading data you collect today may not be applicable tomorrow. The social physics insight is that there are certain statistical universals that always apply. An example is that "long tail" or "fractal" distributions are seen everywhere, which means that unusual events are inevitable.

Q: Can anyone really predict the future? Does Endor make this claim?

Pentland: All data analytics methods predict the future. This is how Walmart stocks up on snow shovels before a storm, or how Amazon gets products to you on the next day. But most methods of dealing with human behavior, and particularly human financial behavior, aren't very good because they don't have any knowledge about how trends take off and spread among humans. This is like trying to predict the movements of the planets without knowing any physics. What social physics does is add knowledge about statistical regularities in human behavior to improve detection and prediction of trends and similar crowd behaviors.

Q: Why did Endor choose to base their next phase on blockchain technology?

Pentland: Since Endor can operate on encrypted data, it is just looking for patterns, not particular values. Thus, the history of transactions recorded on blockchains are perfect for its prediction technology (and useless for almost every other method)!

Q: Can you give me a few scenarios where blockchain’s potential for predictive analytics shines through?

Pentland: The obvious one is predicting movements of cryptocurrencies. Big movements are usually due to crowd behavior—everyone gets excited (or disillusioned) when they see what other people are doing. This is Endor's core strength: tracking the building and dissipation of momentum.

Another example is supply chain logistics. Large brick-and-mortar companies have already started to adopt blockchain for these applications, simply because they are more reliable and secure. This means that the same predictions Endor already sells to enterprises (for example, regarding products' popularity, marketing strategies, etc.) will be needed as well when the transition to Blockchain is done.

Q: Tell me about how your company is implementing AI and predictive analytics to assist financial traders. How does your vision of predictive analytics and AI enhance the average trader’s investment portfolio?

Pentland: Today, the big investors spend enormous amounts of money to predict financial trends, and consequently have better yields than the average investor. Endor will allow the average investor to compete with the big investors on a more even playing field. In a sense, this would be similar to what Google did for access to information online: turning it from an expensive ordeal that requires professional teams into something anyone can do at a very low cost. Small investors would still have to be responsible for their decisions, but they would be given affordable access to technology that is currently limited exclusively to the pros.

Q: How can blockchain banking help bring social physics to the average trader?

Pentland: I think the first application will be estimating “trader momentum” in various altcoins, allowing retail traders to better play the market.

Q: What is the goal of the crowdsale? Why go the ICO route and not the VC route?

Pentland: The goal of the VC game is to get the most money out of a company in the shortest possible time, rather than building a company that is solid and will last. Moreover, VCs don’t care about building the ecology of crypto capabilities, whereas we believe that building a healthy ecosystem is in the best interest of the crowd.

Q: In your opinion, how can blockchain best be harnessed to serve the financial community?

Pentland: The key thing about blockchain is that it can allow accurate and reliable records in domains where all stakeholders have different goals and agendas. This includes having good records even when there are fraudsters in the mix.

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Your Organization Won't Survive Without People Analytics, But There's A Dark Side

People analytics is growing at an astounding pace, with organizations around the world pouring more and more resources into it every day. According to Ben Waber, founder and CEO of Humanyze, what we're seeing now is just the tip of the iceberg. I first met Ben in Madrid when we were both speaking at a conference. Ben got his PhD at MIT in the Human Dynamics group and has studied behavioral analytics for many years. His company creates badges that employees wear at work, but these badges take traditional employee ID badges to the next level. They are equipped with a variety of sensors, such as radio-frequency ID that allows the badges to act like true ID badges, Bluetooth that measures someone's location in an office, infrared that can tell who you are facing, and a microphone that measures not what you say, but how you say it and how much time you spend speaking--all metrics that truly measure human behavior.

This type of data can be used to help organizations understand things such as whether marketing is talking to engineering, whether the manager of a team actually spends time with his or her people, what top-performing employees do differently, and how the most successful salespeople speak with their customers. This type of approach is rarely done inside of organizations simply because the behavioral data doesn't exist. Eventually it will, which will allow organizations to optimize and improve everything from how teams are structured to how compensation packages are created. Ben acknowledges that survey data is still useful and important to have, but it paints only a part of the picture. However, it's still what most companies have. In the next decade or so, only a handful of companies will actually get to the next level of behavior analytics.

In many organizations, the people analytics function sits in HR. The challenge is that many HR teams don't have data science capability because it's a new skill set. HR has primarily always been about dealing with people and their interactions, hiring, and firing versus actually analyzing people from a data science perspective. However, as this area becomes more advanced, it is quite possible that it will grow into its own department that reports directly to the CEO.

There is, of course, a dark side of people analytics because data can be used to make decisions that either positively or negatively affect people. For example, people analytics can be used to calculate mass layoffs or determine ways to manipulate people. This is a delicate balance for organizations--not to mention the potential creepy factor of employees having data collected about their every move and action! People analytics models are designed by people, which means they will be inherently flawed. In her book Weapons of Math Destruction, Cathy O'Neil tells the story of a middle school teacher named Sarah Wyocki who was let go from a job with a Washington, D.C. school district because an algorithm decided that she was doing a poor job. The school district was determined to improve underperforming schools by eliminating bad teachers. Although she got rave reviews from the principal and parents, somehow she was classified as being in the bottom 2% of teachers. It turns out the elementary school where Sarah's students came from was one of several schools under investigation for cheating on standardized tests by teachers who were erasing the wrong answers and filling in the correct ones to help preserve their own jobs. This meant that when Sarah's students took standardized tests where no cheating was involved, their scores dropped considerably, thus making it look like they weren't getting the education they should have been. Naturally the blame fell on the teacher. In this situation, the algorithm would have no way of picking this up, and Sarah and over 200 other teachers were fired. This story illustrates just how important it is for us to not place all of our decision-making eggs in the people analytics basket.

Today we are still at the very early stages of what's possible with people analytics. Perhaps the biggest challenge for companies today is organizing, cleaning, aggregating, and standardizing data, a project that can easily take years depending on the size of the organization.

With technology advances and the integration of AI, you will one day be able to use voice commands to ask a smart assistant things like:

What's the employee turnover?

Who are the top three employees on my team at risk for leaving the organization?

How many contingent workers are we using, and how much are we paying them each year?

What are the top skills and weaknesses on my team?

Which teams are the highest performing inside of our organization?

What employees should I consider for a new marketing team in California?

People analytics is absolutely growing into a core business capability that every organizations must invest in heavily. It is truly the foundation of employee experience.

Learn more about the future of people analytics here.

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4 HR Analytics Trends to Follow in 2018

New technology and competition among HR software providers means there are a lot of trends in this space. Here are four to look out for this year.

Trends can be dangerous to follow, but they can also be important to latch onto so business leaders — and their organizations — don’t get left behind. These conflicting statements are exactly why my colleagues and I track trends and report on the good, the bad and the ugly. Here are four predictions we have for human resources analytics in 2018.

Continuous Listening Can’t Continue

Having your finger on the pulse of what employees think sounds great in theory. Why survey only once or twice a year if you can survey employees all the time? Measuring more often is not a strategy. Also, do you really think your employees want to take more surveys? As such, I predict that this approach won’t last, especially if limited action is taken on the results. Companies that continue with pulse surveys will quickly see the damage.

On the flip side, these companies will learn to turn their focus to the right approach — one that uses surveys to impact business objectives and measures the results. The bad news is that HR and the survey process will be collateral damage of companies abusing the survey process.

Continuous listening can’t last. A client of mine insisted on conducting monthly random pulse surveys, which went against my firm’s recommendations. Their response rates plummeted, and the value of the random pulse surveys greatly diminished. The client met the need of the organization to fill in a box on their monthly scorecard, but it greatly limited what the results told them and what they could do with the data. Now, the client is moving back to a specific survey strategy with a census survey event accompanied by a few targeted pulse surveys with a directed objective (e.g., low-performing leaders).

The Circle of Life, Employee Life

Many organizations monitor the employee at different times during the their tenure but keep the data in silos (and honestly, don’t ever really do much with said data). I predict a shift: organizations will move toward measuring the entire employee life cycle — from pre-hire to exit. The opportunity exists to build a cohesive measurement strategy to assess the different phases of the life cycle together. This requires an integration of assessment content and a strategy for how to use and harvest the intelligence from this data.

For example, organizations could measure the employee life cycle to reduce voluntary turnover, an activity that provides a real return on investment to the organization. Each phase of the life cycle can provide unique insights and value to the organization regarding voluntary turnover. Several survey firms are already moving in this direction.

Proceed with caution, though, because this approach must be done correctly. Done poorly, it will just be more data with limited value.

HR Analytics Are Here to Stay 

Most HR professionals have acquiesced that predictive analytics is not going away. The majority of midsized to large organizations are trying to invest in and build substantial HR analytics capabilities. As such, these organizations are working through several issues as they build out capabilities:

Internal or External: Organizations will continue to grapple with the “buy” or “build” approach. Many are doing both, working with external partners and building internal capabilities. A good partner with this approach will focus a significant amount of time and resources to training internal resources.

The Struggle Is Real: From data warehousing and data integration to data reporting, basic analytics and predictive analytics, there is a ton to consider when integrating HR analytics into the department’s projects. This will be difficult for HR departments to prioritize.

Technology Traps: You’ve heard about dozens of new technologies coming to the market that claim to leverage analytics, machine learning, algorithms, etc. I predict that several organizations will fall into the shiny-new-object trap and purchase a technology that doesn’t provide any value to the company. Said companies will be hesitant to invest in other (potentially valuable) HR technologies in the future.

Track Attack: Many organizations will continue to set out to “do” HR analytics at their organization, but end up solely creating tracking dashboards. This is simply not analytics. The CEO will be less than impressed by a dashboard when they ask for the results of HR analytics investments.

The organizations that journey down the long, complicated path of leveraging the power of HR analytics will have the potential to benefit greatly. Those without a strategy will not be so lucky.

Machine Learning and Artificial Intelligence in HR: The Time Is Not Now

HR is probably years — and maybe even decades — from real machine learning and AI drastically impacting day-to-day operations, so I predict that it will be just hype for a long time due to huge barriers. The first hurdle is that predicting human behavior and/or performance is difficult and complex. Letting a computer make these HR decisions, such as which candidate to hire, has danger written all over it. Just trying to put employees into specific buckets (e.g., race, age, gender) might have absolutely nothing to do with their performance, intent to turn over, etc.

The other huge hurdle is that AI doesn’t apply context well. Don’t underestimate the power of human judgment, and consider how hard it is to replicate that with AI (at least so far). For example, AI was used to judge a beauty contest. A robot panel judged faces based on algorithms that evaluated the “criteria linked to perception of human beauty and health.” The results were considered racist, as all the winners were white. Imagine making an employment decision using a similar approach. Insert lawsuit and damaged company reputation. Adverse impact and discrimination can happen when algorithms point to conclusions based on data alone, without critical context.

December 2017

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3 Big Advantages Of Offline Learning With xAPI Analytics

3 Big Advantages Of Offline Learning With xAPI Analytics

The fast pace of business and elimination of time and distance barriers have also contributed to the success of digital learning solutions – easy reach and easy accessibility, anytime and anywhere. But the rapid growth of this creative disruptor has exposed some of its potential pitfalls too – for instance, the need for good internet connectivity, the need for content security, and the ability to easily update content in real time.

Get the free eBook

Learn, Track, And Update: How To Meet The Challenges Of Offline Learning

In this free gomo eBook, we look at how an authoring tool can solve the problem of offline learning.

In the US, only 55% of people living in rural areas have access to speeds that qualify as broadband, compared to 94% of the urban population [1]. The UK fares better, and is one of the world’s top-ranked markets for internet penetration [2]. More than 80% of the UK population is online regularly. Yet globally, more than half of the world’s population lacks access to the internet, and the growth of usage in developed nations is slowing, according to a UN report [3].

So with their existing technology for offline learning, organizations are experiencing challenges in these key areas:

The ability to provide training materials to learners on mobile devices that are online as well as offline, with data being tracked in both cases. A way to control content access to specific sets of learners and the ability to track completion of assigned courses. A way to add new content as it becomes available. The Need For Employee Accessibility

Global time zones offer 24-hour collaboration with worldwide teams. These workers expect to access information whenever they need it, on whatever device is at hand. With teams operating across the world, across different countries and with varying levels of connectivity, how can our new disruptors change the game and provide for these needs?

Whether learners are working on a construction site or at a customer’s office, the organization must make sure they have the support and training they need. Let’s explore the challenges and solutions of offline learning in this world of creative disruption.

What Do We Mean By Offline Learning?

What exactly is the difference between online and offline learning? The term “online learning” has specific meaning in regard to computer technology and means learning programs that are connected to the internet.

The term “offline learning” indicates a disconnected state, where learners use portable devices such as smartphones, laptops, and tablets for learning purposes but without being connected to the internet.

This is typically done using an app, which tracks learner activity. On-premise classrooms and other forms of face-to-face training have also been considered offline training.

How Offline Learning With xAPI Analytics Benefits Trainers And Remote Learners

The lack of network connectivity in many areas makes it difficult for remote learners to gain access to course content. Offline eLearning—allowing content to be set up ahead of time when access to internet connection is available— then becomes the solution for those who don’t have an internet connection at home or while traveling, who work in far-off rural areas, or in parts of the globe where connections are few and far-between.

Offline learning with xAPI analytics brings 3 big advantages to any organization’s trainers and remote learners:

1. Access To Content For Disconnected Learners

Being disconnected doesn’t mean learning stops. In fact, for many workers offline learning is their ‘new normal’. While many people who live and work in urban, technology-enabled areas are almost always connected to the internet, not all learners experience the same scenario.

Sales reps, for example, are often on the road, sometimes in locations without stable wi-fi or internet connections. Likewise, remote workers such as oil rig technicians whose professions see them working in far-flung corners of the globe, rely on offline learning content to continue their training. Even urban workers who commute extensively on trains and planes may have prolonged periods of no internet, periods which are actually perfect for learning as there are usually less distractions.

Any provider that can give learners access to training programs while offline (as well as online, of course) could potentially be invaluable.

2. Dynamic Content Updates On Reconnection

With ‘push’ notifications, users can always have access to the latest training and sales information. An icon on the app lets users know when there’s new content available and to update their courses.

3. Good Offline Learning Provides Full Tracking

With a good offline learning tool, like the gomo central native app, organizations can track user activity and assessment scores, even when learners are disconnected. When the learner comes back online, the activity is then uploaded and the organization can see the user’s engagement with the learning content.

References:

Technology Is Improving, So Why Is Rural Broadband Access Still a Problem? US New & World Report, June 9, 2016 UK Digital Users: The eMarketer Forecast for 2017, eMarketer, February 22, 2017 More Than Half the World Still Without Internet Access, Newsweek, Sep 21, 2015
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What Is A Learning Management System? LMS Basic Functions And Features You Must Know

What Is A Learning Management System? LMS Basic Functions And Features You Must Know

The term "Learning Management System" (LMS) makes an appearance quite frequently in eLearning articles, tip sheets, and beginner’s guides. As such, it’s important to get a good grasp on what a Learning Management System entails and the benefits it brings. Is a Learning Management System really worth the resources? Or will a more manual approach suffice? What are the advantages of investing in a LMS, and which features should you look for? Are there different hosting and pricing plans you need to keep in mind? This article will address all these questions and give you the insider scoop on Learning Management Systems so that you can decide whether a new LMS is right for your online training program or not.

What Is The Primary Function Of An LMS?

The role of a Learning Management System varies depending on the organization’s objectives, online training strategy, and desired outcomes. However, the most common use for LMS software is to deploy and track online training initiatives. Typically, assets are uploaded to the Learning Management System, which makes them easily accessible for remote learners. In some cases, the LMS may even have built-in eLearning authoring tools that allow you to develop online training materials without additional third-party software.

Think of a Learning Management System as a vast repository where you can store and track information. Anyone with a login and password can access these online training  resources whenever and wherever. For self-hosted Learning Management Systems, users must also have the LMS software installed on their hard drive or access to the company’s server. Whatever the installation option, the thing to bear in mind is that LMS users fall into two categories: First, online learners who use the Learning Management System to participate in online training courses; second, your eLearning team who relies on the LMS platform to disburse information and update the online training content.

Who Can Benefit From An LMS?

Learning Management Systems are beneficial for educational institutions and corporations alike. Extended enterprise online training is yet another application for Learning Management Systems. For example, companies are able to deploy online training resources to external sales channels, franchisees, and even customers. It’s vital to identify your organizational and training objectives before you start the LMS selection process, as LMS vendors typically cater to different consumer groups. Some specialize in eCommerce, while others are known for their sales online training features. For instance, the power to integrate CRM software.

LMS Deployment Options a. Cloud-Based (SaaS)

These LMS platforms are hosted on the cloud. The LMS vendor maintains the system and carries out any tech upgrades or updates. Online learners and collaborators login to the Learning Management System with a user name and password. There’s no need to install any software, which makes it a great option for organizations who want to get started as soon as possible. The downside is that some cloud-based Learning Management Systems cannot be customized. For example, there are fewer opportunities to incorporate branding or personalize the dashboard.

b. Self-Hosted

Learning Management Systems that require software downloads. The LMS vendor may offer direct download from their site, or you must request physical software discs. However, the former is more common these days. Self-hosted LMS platforms allow for greater creative control and customization. The disadvantage is that you usually have to pay for updates, and the system may require IT know-how.

c. Desktop Application

The LMS app is installed on the desktop. Some desktop apps are even accessible on multiple devices, making it easy for your entire eLearning team to collaborate.

d. Mobile Application

Learning Management Systems that are accessible whenever, wherever via mobile devices. You can upload online training content so that online learners can track online training initiatives on the go.

LMS Customer Types a. Large Enterprises

Larger organizations can use these Learning Management Systems to track hundreds or thousands of employees. Not to mention, deploy global online training initiatives. In some cases, they may even feature extended enterprise features so that you can keep franchisees and sales channels in the loop.

b. Small & Medium Businesses (SMBs)

Small and Medium-sized Businesses (SMBs) benefit from this type of Learning Management Systems as they can utilize fewer human resources. These tools also scale along with your business to adapt to your ever-changing training needs.

c. Freelancers

LMS platforms designed for eLearning freelancers who work with multiple clients and need to deliver a diverse range of deliverables. These Learning Management Systems may feature built-in collaboration tools, which allow you to fly solo or work with a remote eLearning team.

LMS Licensing Types a. Open Source

Open Source Learning Management Systems are generally free and based online. You’re able to modify the source code in order to suit your needs. In addition, many open source options have active online communities, which means that you can get tips and troubleshooting assistance if you do encounter a problem. The drawback is that you typically need some degree of programming experience.

b. Free License

There are a number of free LMS options, usually open source systems. However, the money that you save on licensing or monthly fees may be spent on IT staff, especially if you don’t have any programming experience. In addition, you may have to deal with a steep learning curve to get the most from the Learning Management System.

c. Paid License

Paid Learning Management Systems require a monthly or yearly fee. Some even allow you to purchase the software outright. They typically offer more advanced support options and user-friendly features.

6. LMS Pricing Models a. Licensing

Instead of paying per user, this LMS pricing plan involves a licensing fee. Typically, an annual fee that you must renew on a yearly basis, or an outright upfront fee that grants unlimited lifetime access. However, as technology advances you’ll probably still have to purchase replacement software in the near future.

b. Subscription

A subscription fee usually grants you access to all LMS features, or relies on a pay-per-user model. This pricing model involves a fee for each user, or active user. In some cases, the LMS vendor offers different price brackets. For example, the fee covers up to 25 active learners. This is a great solution for smaller organizations who want to minimize online training costs, but still want to be able to scale the Learning Management System as their company expands.

c. Freemium

These LMS platforms are free for basic features but a fee is charged for more advanced functionalities, such as add-ons or upgrades. For instance, a more comprehensive eLearning assessment engine or advanced reports.

LMS Specification Support Types a. SCORM 2004

This set of standards helps eLearning authoring tools and eLearning content communicate with the Learning Management System. SCORM 2004 enables tools to format eLearning content in such a way that’s shareable across the board.

b. Tin Can API

Also known as Experience API, Tin Can spec support is often viewed as the follow-up to SCORM. It allows for external learning activities and tracking, and gives eLearning pros the ability to develop and deploy native mobile apps.

c. AICC

Aviation Industry CBT Committee support allows the LMS and eLearning content to communicate via HAC protocols. In essence, the system relies on an HTML form to transmit the information, then the LMS relays the information back via text.

d. IMS LTI

Learning Tools Interoperability (LTI) was introduced by the IMS Global Learning Consortium. It specializes in apps that are hosted remotely, as well as web-based eLearning content.

Learning Management System Benefits 1. Organizes And Safely Stores Big Data

Learning Management Systems allow you to gather all Big Data in one location. This also makes it easier to maintain and update your learning materials. In addition, most LMSs feature advanced encryption so that you don’t have to worry about data falling into the wrong hands.

2. Monitors Learner Progress And Performance

Virtually all LMS platforms feature built-in reporting and analytics. Thus, you’re able to track various aspects of your online training program. If the Learning Management System lacks sufficient reporting capabilities, you can typically purchase add-ons or plug-ins to boost its functionality. You can track everything from learner engagement to eLearning assessment results. This means that you can identify patterns and trends, especially since many LMSs provide data visualizations, such as graphs and charts.

3. Improves Resource Allocation

There are a number of ways that LMS platforms can help you allocate online training resources more effectively. First and foremost, you can identify aspects of your online training program that aren’t meeting expectations. Low learner engagement is usually an indicator that you need to reevaluate an online training module or activity. Secondly, Learning Management Systems help your eLearning team update online training assets more rapidly. Then there’s the matter of deploying online training resources on a global scale. Thus, you have the power to keep corporate learners up to date using a single tool.

4. Personalizes The Online Training Experience

You can assign different learning paths or online training resources for individual corporate learners with the help of an LMS. Therefore, everyone gets the individualized online training they need based on their learning goals, job duties, and various other criteria. There’s even the option to unlock the navigation so that corporate learners can choose their own online training activities and coursework. All this translates into more effective online training experiences and increased learner satisfaction. Not to mention, improved memory retention and engagement.

5. Improves eLearning Accessibility

Modern learners expect online training resources on demand. After all, we live in the digital age, where information is always at our fingertips, thanks to smartphones and wearable tech. Learning Management Systems allow you to deploy and track online training courses without geographical limitations. So long as they can login to the system, corporate learners have the opportunity to expand their knowledge and hone skills.

Top Features To Look For In Your New LMS 1. Reports And Analytics

You must be able to monitor your online training initiatives to determine if they are on target or require minor adjustments. The same rule also applies to individual learner performance. Are corporate learners engaging with the online training content? Is it giving them all the information they need to achieve their learning objectives? These are questions that can be answered with a robust reporting system built into your new LMS. Learning Management Systems also feature analytics that allow you to monitor online training on individual and group level. For example, determine whether a certain percentage of your audience has completed the online training course requirements or not, or how long they take to complete each online training activity on average. Most will even deliver the analytics right to your inbox via automated email reports.

2. Responsive Design

Multiplatform-friendly online training resources give everyone the chance to benefit from your online training course. Even those who prefer to use their smartphones or tablets to access the learning materials. Thus, your LMS should be responsive, enabling you to create a master layout that features distinct breakpoints. The Learning Management System automatically displays the most suitable version of the online training course based on the user’s device. For example, shrinks images down to size so that they don’t occupy the entire smartphone screen. Ideally, you should be able to preview each version and make necessary modifications before launch. It’s also wise to look for a tool that allows corporate learners to download the learning materials and view them offline. Especially when Internet accessibility isn’t an option.

3. Intuitive User Interface

Feature-rich systems aren’t of much use if your eLearning team is unable to use the user interface and navigate the LMS platform. The same goes for your corporate learners. Does the tool make it easy for them to access the coursework, or does it present its own set of challenges? The LMS you choose should have an intuitive user interface that aligns with your eLearning team’s skill sets and abilities. For this reason, it’s essential to get their input before deciding on a platform. In addition, take advantage of free trials and demos to ensure it’s user-friendly.

4. Support Services

LMS vendors offer different support services. As such, you need to determine the level of assistance you need based on your eLearning team’s experience level and the complexity of the tool. For example, novice eLearning teams might need more extensive support in order to utilize the system effectively. Many LMS vendors also host online discussions that allow you to connect with other users, in addition to online training tutorials, guides, and tip sheets. You may be able to pay for additional support services if you require more advanced options, such as a toll-free number that gives you direct access to a trained tech.

5. eLearning Assessment Tools

You need to assess your corporate learners periodically to identify gaps and intervene when necessary. Therefore, the LMS must be able to support a broad range of eLearning assessment methods. Many even offer built-in eLearning assessment tools, such as eLearning templates. Lastly, there must be LMS reports dedicated to eLearning assessment tracking.

6. Gamification Features

Some emplooyees require extra incentive to actively engage in your online training course. Game mechanics give them the motivation they need in the form of badges, points, and leaderboards. The key is finding an LMS that has built-in gamification features so that you can easily incorporate these rewards.

7. Compliance And Certification Support

This is an essential feature for organizations who provide company policy and compliance online training, as well as those who require more advanced certification features, such as the ability to track individual skill and performance gaps. You can also refer to the LMS records in the event of an audit, which helps prevent violations and fines.

8. Social Learning Support

Social learning gives corporate learners the chance to interact with peers and share their experiences. Many Learning Management Systems now feature integrated social media tools. For example, the ability to track online discussion participation, or incorporate a news feed into your eLearning course design.

9. Localization

Multilingual support is crucial for organizations who plan to deliver worldwide online training resources. Every member of your team should have the same opportunity to develop their professional skills. Some LMSs even feature geolocation features that automatically display the appropriate version of the online training course.

These are just the basic LMS components and considerations. Keep in mind that there is no one-size-fits-all LMS. Every organization has unique training needs and budgetary constraints. Thus, you need to do your homework to find the LMS that meets your requirements and benefits both your corporate learners and bottom line.

Are you interested in learning more about LMS pricing plans? Read the article The Insider's Guide To Learning Management Systems' Pricing Models to explore the most common Learning Management System pricing models to consider, from perpetual licensing to pay-per-use. This way you can determine which option is best for your budget and training needs.

Also, don’t forget to check out our free LMS directory, which allows you to filter your search results based on deployment, customer type, licensing, and pricing models.

November 2017

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4 Secrets Of Successful Informal Learning Initiative

Gartner has estimated that a massive 90% of social collaboration initiatives fail. Find out what you need to make sure yours isn't one of them!

What Are The Secrets Of Successful Informal Learning Initiative?

In the pursuit of more efficient and effective training methods, many learning managers are turning to social learning technologies to get a better return on their investment. In a survey [1] by global management consulting firm, McKinsey & Company, 82% of respondents said that their organization had implemented an internal social network of some kind. With informal learning making up around 90% of all work-based learning, this is only logical.

Creating a more collaborative learning environment is a good first step towards better training results, but it’s not a simple switch that you can flick on. Tapping into that huge vein of informal learning takes a lot of work and sadly, many learning managers underestimate the effort involved.

Gartner has estimated [2] that a massive 90% of social collaboration initiatives fail due to the so-called 'provide-and-pray' approach – the false idea that a new initiative doesn’t need extensive internal promotion and marketing. According to Jacques Bughin of McKinsey, if a social network is to be a success, 30-40% of staff should be using it on a daily basis. If you don’t secure that buy-in, your social learning initiative will gradually wither and you won’t get the results you’d hoped for. As with so much in learning and development, learner engagement is the fuel that keeps your informal learning initiative running.

1. An Engagement Strategy

Informal learning can lead to a huge repository of organizational knowledge, and an exciting and varied learning program that helps learners go further in their careers. To get there, you need to have a clear engagement strategy to ensure that learners participate in the first instance.

Use reward and recognition to give them an incentive to share their knowledge. A gamified platformgives you a world of new ways to make the learning experience more fun and more addictive. If your LMShas plenty of customization options, use them to build a relevant and meaningful online space that makes sense to your learners and reinforces the common values in the organization. It’s also important to make the platform as easy to engage with as possible. That means ensuring it can be accessed on all devices, including mobile.

2. An Open Community

Informal learning works so well because it aligns with the modern learner’s need for autonomy. Your learners want an open platform that they can explore and use to discover new things. You want them to contribute and share their knowledge and ideas.

It can be tricky to balance your learners’ need for autonomy, and the needs of your organization. To achieve the right mix, you need to give the learners a sense of ownership. Instead of prescribing a rigid company-sanctioned curriculum, create open-access discussion groups and make sure your learners can find them easily.

You can support this further with game mechanics, awarding points, and badges to the top contributors. Not only will this give you a fun and relevant knowledge resource, it will also let you identify who the real experts are in any given topic.

3. A Dedicated Admin Team

Because of its nature, an informal learning initiative has a lot of moving parts. You need to make sure that every member of your Learning and Development team is on board with the initiative’s aims, and understands their role in achieving them.

If you can get the managers excited about the possibilities of informal learning, they can become extensions of your admin team, engaging their own teams, and highlighting any valuable user-generated content.

When any new initiative is introduced, the organizational culture needs to adapt to accommodate it. This necessitates changes in behavior that cascade from the highest levels, downward. With all the managers playing their own small role, this sets a positive example for everyone else.

4. Recognition From The CEO

Engaging all your managers works in a similar way. The only difference is that you need to go a little further up the chain. Getting the CEO on board has a huge effect on engagement. I’ve seen the impact first hand with Growth Engineering’s own clients. One CEO shares a short video on the platform every month, and this regular feature has become a huge driver for traffic.

Reinforcing the message of the learning campaign doesn’t need to be complicated either. The above CEO doesn’t spend time sharing figures and stipulating targets. He merely says 'thank you' for all the hard work everyone in the company does on a daily basis.

The important thing is that these regular updates from the top legitimize the platform in everyone’s eyes, and improve the chances of learner buy-in.

Conclusion

A social learning platform won’t save your organization all by itself. Real success relies on the people behind the initiative. If you want to a return on investment, social features let you get the most out of your intellectual capital. With passion, dedication and an open learning culture, you can finally harness and capture all the power of informal learning and make use of your learners’ hidden knowledge.

The benefits of leveraging informal learning are enormous, but to reap them, you need to make sure that your campaign is engaging for the learners. Once they are convinced of the platform’s worth and begin using it regularly, you might just achieve stunning results in places you hadn’t even expected.

References:

Transforming the business through social tools. Gartner Says the Vast Majority of Social Collaboration Initiatives Fail Due to Lack of Purpose.

October 2017

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People analytics reveals three things HR may be getting wrong

More sophisticated analyses of big data are helping companies identify, recruit, and reward the best personnel. The results can run counter to common wisdom.

Bill James, the factory watchman turned baseball historian and statistician, once observed, “There will always be people who are ahead of the curve, and people who are behind the curve. But knowledge moves the curve.”1Some companies are discovering that if they employ the latest in data analytics, they can find, deploy, and advance more people on the right side of the curve—even if the results at first appear counterintuitive.

Over the past decade, big data analytics has been revolutionizing the way many companies do business. Chief marketing officers track detailed shopping patterns and preferences to predict and inform consumer behavior. Chief financial officers use real-time, forward-looking, integrated analytics to better understand different business lines. And now, chief human-resources officers are starting to deploy predictive talent models that can more effectively—and more rapidly—identify, recruit, develop, and retain the right people. Mapping HR data helps organizations identify current pain points and prioritize future analytics investments. Surprisingly, however, the data do not always point in the direction that more seasoned HR officers might expect. Here are three examples.

1. Choosing where to cast the recruiting net

A bank in Asia had a well-worn plan for hiring: recruit the best and the brightest from the highest-regarded universities. The process was one of many put to the test when the company, which employed more than 8,000 people across 30 branches, began a major organizational restructuring. As part of the effort, the bank turned to data analytics to identify high-potential employees, map new roles, and gain greater insight into key indicators of performance.

Thirty data points aligned with five categories—demographics, branch information, performance, professional history, and tenure—were collected for each employee, using existing sources. Analytics were then applied to identify commonalities among high (and low) performers. This information, in turn, helped create profiles for employees with a higher likelihood of succeeding in particular roles.

Further machine learning–based analysis revealed that branch and team structures were highly predictive of financial outcomes. It also highlighted how a few key roles had a particularly strong impact on the bank’s overall success. As a result, executives built new organizational structures around key teams and talent groups. In many instances, previous assumptions about how to find the right internal people for new roles were upended.

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Whereas the bank had always thought top talent came from top academic programs, for example, hard analysis revealed that the most effective employees came from a wider variety of institutions, including five specific universities and an additional three certification programs. An observable correlation was evident between certain employees who were regarded as “top performers” and those who had worked in previous roles, indicating that specific positions could serve as feeders for future highfliers. Both of these findings have since been applied in how the bank recruits, measures performance, and matches people to roles. The results: a 26 percent increase in branch productivity (as measured by the number of full-time employees needed to support revenue) and a rate of conversion of new recruits 80 percent higher than before the changes were put in place. During the same period, net income also rose by 14 percent.

2. Cutting through the hiring noise and bias

The democracy of numbers can also help organizations eliminate unconscious preferences and biases, which can surface even when those responsible have the best of intentions. For instance, a professional-services company had been nearly overwhelmed by the 250,000 job applications it received every year. By introducing more advanced automation, it sought to reduce the costs associated with the initial résumé-screening process, and to improve screening effectiveness. One complication was the aggressive goals the company had simultaneously set for hiring more women, prompting concern that a machine programmed to mine for education and work experience might undermine that effort.

The worries proved unwarranted. The algorithm adapted by HR took into account historical recruiting data, including past applicant résumés and, for those who were extended offers previously, their decisions on whether to accept. When linked to the company’s hiring goals, the model successfully identified those candidates most likely to be hired and automatically passed them on to the next stage of the recruiting process. Those least likely to be hired were automatically rejected. With a clearer field, expert recruiters were freer to focus on the remaining candidates to find the right fit. The savings associated with the automation of this step, which encompassed more than 55 percent of the résumés, delivered a 500 percent return on investment. What’s more, the number of women who passed through automated screening—each one on merit—represented a 15 percent increase over the number who had passed through manual screening. The foundational assumption—that screening conducted by humans would increase gender diversity more effectively—was proved incorrect.

3. Addressing attrition by improving management Too often, companies seek to win the talent war by throwing ever more money into the mix. One example was a major US insurer that had been facing high attrition rates; it first sought, with minimal success, to offer bonuses to managers and employees who opted to remain. Then the company got smarter. It gathered data to help create profiles of at-risk workers; the intelligence included a range of information such as demographic profile, professional and educational background, performance ratings, and, yes, levels of compensation. By applying sophisticated data analytics, a key finding rose to the fore: employees in smaller teams, with longer periods between promotions and with lower-performing managers, were more likely to leave.

Once these high-risk employees had been identified, more informed efforts were made to convince them to stay. Chiefly, these involved greater opportunities for learning development and more support from a stronger manager. Bonuses, on the other hand, proved to have little if any effect. As a result, funds that might have been allocated to ineffectual compensation increases were instead invested in learning development for employees and improved training for managers. Performance and retention both improved, with significant savings left over—showing yet again the value of digging into the data at hand. When well applied, people analytics is fairer, has greater impact, and is ultimately more time and cost-effective. It can move everyone up the knowledge curve—often times in counterintuitive ways.

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Building the Next-Gen Organization

Building a change-resilient and future-friendly organization is all about the right skills, right leadership and a culture thats conducive to change.

Change is the only constant, and this has never been truer than today, where businesses need to constantly reinvent the wheel to stay relevant for the present and future. Accordingly, the very “Future of Work” is taking a 360 degrees turn, and HR practitioners and business managers are forced to imbibe this new work paradigm. This significant shift is inviting a lot of talk about about the evolution of work and what it means for masses. Some experts have gone so far as to condemning automation and artificial intelligence as socio-economic destructors. Here is an objective look at the Future of Work, as it plays out for both employees and employers. 

The Construct of the Future Organization

On a broad level, a new order of work will emerge based on the following five courses of change: 

A truly connected world: The rise of connected devices and emerging technologies like the Internet of Things, Artificial Intelligence (AI) and Data & Analytics has enabled seamless connectivity at the workplace, breaking barriers like never before. Truly connected is giving rise to new work expectations and norms. 
  Social organization and reintegration: Emerging technologies are disrupting work norms, about 38-40 million skilled workers and 90-95 million low-skilled workers may be affected by automation. There is a notion that this will lead to the revision of key organizational roles, leading to imbalance. 
  Collaboration: Communication and collaboration will be two sides of the coin in taking organizations to greater heights in this complex environment. 
  More inclusive global talent: As a result of technology-infiltration, the nature of talent itself is changing. Consider the case of Topcoder.com, a talent platform revolving around the gig economy, today there are thousands of technologists, 5 years ago there were less than three thousand. The gig economy is here to stay, and future organizations must learn how to leverage this unique talent pool. 
  Employer-employee relationships: Relationships are no longer binary, they are highly dynamic. Going forward we will see a mix of various work-models- traditional, outsourcing, free agents, alliances and partnerships, talent platforms, volunteers etc.  A Changing Talent Landscape

In line with the above changes, the definition of work itself is undergoing a transformation. Work of tomorrow is moving away from ”leading the workforce” to “leading the work” itself. As a result, the talent landscape is moving from jobs to tasks, from collective to dispersed,  from relationship-based to virtual, from self-contained to associative, from rigid structures to malleable fluid structures, from permanent to impermanent, and from collective to very individualized. All of this can be summarized in a holistic shift- from traditional to imaginative. And to fit talent into this imaginative work concept, HR too must imagine the unimaginable. This starts with gearing up for the transformation- building a change-resilient organization. 

Making the right skills available at the right places will be extremely crucial going ahead, so as to control machine-outcomes on-time and accurately.  

An opportunity in the making: How to build resilience

As technology is evolving there also lie immense opportunities for organizations, only if they are ready to embrace change. Yet, most organizations struggle. The following elements need to be relooked at and revamped to make this possible. 

Build the right skills: The right skill-sets or competencies are what will help bridge the gap between today and tomorrow. This starts with understanding the challenge at hand, and by leveraging available technologies and tools like data and analytics. The right futuristic skills will ensure that we are more connected than ever before, and know our problems better. We have many more resources than before- data, access to people, etc. we must only harness these to create multiple avenues of driving business. For this, HR must work with business and develop a data-oriented objective approach to building talent capability. The key question should be, “How to harness digital skills?”
  Cultivate a conducive organizational culture: Building a change-conducive organizational culture involves thinking about talent differently. Analyse where the issues are and where talent is rare, rather than just hiring adhoc. Building resilience is all about giving talent the freedom, the leeway to experiment and to outperform without hiccups. Many organizations taste success with failures because it welcomes more learning, more opportunities to do something different. Building such an open and transparent culture is not easy, HR leaders must proactively enable talent to flow in line with their aspirations. A great culture often helps fulfill a business need, while establishing a connect with the right talent. 
  Lead by example: The CEO of CISCO once famously said, “The organizations of the future have only two leaders- CEO and CIO/CTO, everything else will be contingent”. Organizations must build leadership capability to deal with demanding business. Leadership roles are changing, they are not so much about the job description, but the problem at hand. Leadership roles are no longer “here and now”, they are highly future-oriented i.e. roles 3-5-10 years from now. Vision for the future and long-term planning are being looked upon in new light. It is important to assess people on their ability to deliver excellent results in the long run. This may require HR to create a “training JD” rather than a “role JD”, which outlines how to get “there”. From the org-perspective this should be an ongoing investment.


The future of work thus lies in creative intelligence, social intelligence, and ability to leverage digital. 

Worries about machines overtaking man in the workplace abound, but the fact remains that the future of work will comprise a shared model, where man and machine work together.

Ultimately, people are at the core of organizational success. After civilization, this is the fourth Industrial Revolution, and in every revolution, new jobs have been created. Worries abound that robots will take away our jobs, but the reality is that we still need someone to guide those robots. This calls for a new outlook, employees are used to thinking in terms of process and workflow, i.e. how things will be designed. The future need is to think of “flow of work to the right places”. What will make a real difference is not just letting work happen, but directing it correctly. And that is where the right human intelligence remain irreplaceable. 

(This article has been curated from the session conducted at the Singapore Human Capital Summit 2017)

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Psychometrics: Using multiple assessments for more predictive analysis

Psychometric assessments have already proven their objectivity and reliability in various HR decision-making processes. But their current way of use proves lacking against the evolving organization HR challenges, like the emergence of new skills and occupations, perennial dearth of talent, and more than ever diverse working environments.

Recruitment mistakes remain a reality and despite the proliferation of selection methods its success rate stands at only 54%. That means a recruiter makes one bad decision for every two recruitments.  

According to a study by the Society for Human Resources Management (SHRM), the cost of selecting the wrong person can run up to five times of a bad hire’s annual salary. And higher the position and longer the person remains in that position, the more it will cost to replace them. It is also known that in 89% of the cases, the failures are explained by behavioral factors and not by a lack of technical know-how.1 

Psychometric assessments have already proven their objectivity and reliability in various HR decision-making processes. But their current way of use proves lacking against the evolving organization HR challenges, like the emergence of new skills and occupations, perennial dearth of talent, and more than ever diverse working environments.

Better target potentials through multi-criteria assessment approach

Human behavior is incredibly complex with each person having a unique set of characteristics. So, trying to predict how a person is going to behave and perform at work is not an easy task. That is why making a good recruitment decision is not anymore based on “gut feeling” or “liking the candidate”; it is about combining multiple data for a more accurate and predictive analysis of a candidate’s potential.

Due to their construction and scientific validity, psychometric assessment matches well the "big data" approach and provide accurate and unbiased insight into people’s behavior and potential.

However, it is well known that psychometrics is not a crystal ball. Psychometric tests have surely shown to have a predictive value in relation to job competencies and overall performance, but their success rate depends significantly on the how well the assessments are used.

Recruitment decision cannot be based solely on cognitive skills evaluation or just a personality test alone. As research has shown that the predictive ability to use a single assessment tool is often moderate. However, when multiple assessments are combined, their predictive analysis enhanced significantly.

This is precisely what Harvard Business School study shows2, the combined use of personality and intelligence tests increases recruitment efficiency by 15% compared to a non-test recruitment process.

These significant findings corroborate the Schmidt & Hunter study, which highlighted the predictive values of several selection methods including intelligence tests and integrity assessment. Thus the use of intelligence tests in addition to the structured interview allows to increase the success rate by 12% compared to maintenance alone. More generally, this study shows that the combination of selection tools, when they are relevant, is always more predictive.

“In terms of recruitment algorithms do better than intuition.”

Since the results from different psychometric tests complement each other, they can ensure a more accurate assessment. For example, one can combine a personality test, a sales aptitude test with an emotional intelligence test for a more precise and comprehensive evaluation, when it comes to hiring for a sales position.

The only limitation with this approach is that the assessors need to juggle report results of different assessments to obtain one complete analysis of the candidate’s profile.

A psychometric test creator Central Test, understood the challenge and developed a tool called TALENT MAP that uses the multi-criteria approach to psychometric assessments. 

It relies on a powerful algorithm to analyze the results of multiple assessments in a single competency framework and job referential.

TALENT MAP offers decision-makers the power to match a candidate profile with 36 competencies and 138 occupations, with just one click. Fully customizable, the tool can adjust to your own criteria and you can define the competency estimated according to your expectations.

The multi-criteria approach redefines the use of psychometric assessments and will significantly increase the success of your recruitments.

In summary, psychometric tests are excellent tools for decision making in recruitment, even though there is no quick fix. This predictive accuracy could be further enhanced by an optimized use of psychometrics, notably through the promising multi-criteria approach.

References: 

 1 "Hiring for attitude”, Mark Murphy, 2012

  2 "Discretion in hiring", Harvard Business School, 2015

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Can machine learning help overcome human failures?

A lot of HR technological tools today are incorporating machine learning to help, support and empower humans at their workplaces. Here is a glimpse of a few ideas shared at the People Matters and Microsoft India roundtable on the same subject.

There has been a lot of hullabaloo over artificial intelligence and how it would change the world in the course of the next few years. People Matters and Microsoft India organized a roundtable which discussed key ideas on artificial intelligence and how it is impacting workplaces today. This article attempts to capture some of those key ideas and present to you in a simplified format.

Artificial intelligence is actually at a very nascent stage

Despite all the discussions that have been undertaken in many of the public spheres, there is still a lot of confusion about what exactly can artificial intelligence do for you. First, for any system to become intelligent, it will capture data, analyze it, learn from the frequent interactions with the user, and then intelligently respond to the situation. The end of the goal is for the machine or the software to take decisions without human intervention. This leads to automation in processes. 

An example, which was discussed during the roundtable, revolved around automating the process of reading hundreds of resume and shortlisting candidates dependent on an algorithm which ensured that only the best fit for the job was selected.

Is Machine Learning only restricted to the domain of HR

Machine Learning is constantly evolving and very differently across industries. To understand why something like this is possible, one needs to understand that the evolution of any technology, and especially something like artificial intelligence, the evolution is completely dependent on the use cases. The use cases determine the data that is captured, the algorithm which is developed to organize the data, and finally, the purpose for which the analysis of the data is put to use.

In one of the instances, Sanjoe Jose, co-founder, and CEO of Talview, during the roundtable gave an example of how an algorithm which determines the survival of the patient, referred as ‘survival analysis’ was adapted to create a similar algorithm which determines the time it would require for a position to get filled in the organization.

AI and L&D

Similarly, artificial intelligence is being used in the domain of learning and development, and which is not just restricted to skilling talent, but also managing and guiding talent within the organization. Consider, that most of these technologies are cloud-based, what is they further enable the employee to chart his own career path in the organization. The software would let him know of all the training and resources available to him to develop the requisite skill, which will help him fill his desired role in the future.

During the roundtables, it was extremely well demonstrated in the case of a recently onboarded employee who is looking for resources which would enable him to carry out a task. Organizations today understand that employees do not just learn on the job by default, but they also look forward to ‘learning’ on the job. 

In larger setups, individual attention and mentorship not always available and which is why for many large organizations it makes sense that a 24/7 chat bot communicates with the new joinee and enable him to perform on his job. 

The process is actually quite simple: once the data at the organizational level is collected and organized, it can simply be grouped dependent on the algorithm deployed. Further, when the chatbot receives a query, it is translated into the language that the computer understands, the query is processed and the solution is made available, this solution is then presented to the person who asked the query, in the language that the person understands.

For example: A person who wishes to organize an office offsite but does not know how to go about it, would simply type in the chat and ask for help. The chatbot would then give it a list of videos or articles which his colleagues or peers would have accessed in the past, and also the ratings and comments they had for that particular resource. Similarly, it could also connect that person with somebody who has conducted successful offsites and they could connect with one another over chat or on call, enabling the transfer of knowledge within the organization.

We need more data scientists

Sandeep Jayaprasad Alur, the Director Partner Technology Engagements, Microsoft India gave the answer to this question, when he revealed to the audience during the roundtable, that tech giants like Microsoft have been working on developing cloud-based artificial intelligence based platforms since the last decade, and have only recently unveiled the technological platform, because it is only very recently that organizations have had access to humongous data that they have today.

The infrastructure which consists of the cloud computing, algorithms and the abundance of data is today readily available to organizations, but what is lacking today are the people who would take these technologies to the next level, and by people, it specifically meant the data scientists. He defined them as people who knew much more about statistics than a programmer, and much more programming than a statistician.

Using Machine Learning for engagement with candidates

A major challenge that the recruiters face today is responding to the hundreds of applications which organizations receive. The recruiter finds it difficult to effectively engage with all of them. The challenges start with analyzing the data in the resume, to engaging with candidates on an individual level, arranging for assessments tests and interviews, lacking data inputs which would enable the organization to make the best decision.

Today, all of the above is being taken care of technology which are an integration of data capturing, analysis of the same within the domain of the algorithm deployed, mapping the skills to the job roles, and uses a user-friendly interface (chatbots are most popular) to respond to candidates, and hence leading to effectively managing hiring.

From baby steps to shaping the future of tomorrow

During the roundtable, a question was posed to one of the speakers, that what most of what they show that technologies exhibit is actually extremely advanced. To which the speaker answered that they have the algorithms but what technology would lack on initial installation is the organizational data. But because the algorithms learn from interactions with the user, it would acquire the required data both at an individual and organizational in no time, and hence would then accomplish all the complex tasks (the example of a person wanting help with organizing an office off-site), very easily.

Hence, to summarize it is too soon for us is to completely imagine the altered employee experience of tomorrow. But what we do know for certain is that our employee experience at workplace will never be the same again.

Finally, can machine learning help overcome human failures

In most cases, the algorithms actually predict the probability of the desired outcome happening. Which means if the software tells the recruiter that of the hundreds of resumes received by the organization, only five are the best fit for the job, then that means that is the most likely outcome that it has arrived at. Most algorithms are predictive models which boast of a certain level of accuracy, but because machines do not err, in the sense that it won’t skip any of the resumes because it felt tired; machine learning to large extent would enable humans to perform to the best of their abilities.

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Future of performance management system

Organizations such as Adobe, Accenture, Microsoft and Delloite have adopted new ways of assessing to enhance individual and organizational performance.

Performance Management System has undergone a lot of changes in the recent past to effectively translate effort to performance. The old ways of assessing performance have proven to be costly and ineffective. Bell curve alias relative comparison has been observed to be time consuming and often detrimental to performance. Organizations such as Adobe, Accenture, Microsoft and Delloite have adopted new ways of assessing to enhance individual and organizational performance. 

Recent Changes 

Key modifications in the performance management system include 

Rating team members on managers’ own future actions with respect to the team members is also practiced by few organizations. This solves the problem of idiosyncratic rater affect with managers rating employees on their own feelings / intentions rather than rating employees’ skills inconsistently.
  Goal setting no longer being an annual exercise but goals being reviewed quarterly/periodically.
  More frequent meetings between managers and employees for setting expectations clearly, sharing feedback and coaching on developmental goals. At least end of the project or quarterly feedback is recommended though the meetings could be more frequent than this. 
  Rating employees on absolute performance rather than using bell curve.
  Results so far 

Though the results are awaited largely, few organizations have already started reporting the benefits they are experiencing. Adobe has reported a drop in voluntary attrition rate by 30% and an increase in involuntary attrition rate by 50%. Inorder to facilitate more frequent feedback and development conversations, Adobe has introduced a system namely “Check-in” as per which managers should have atleast quarterly discussions with their team members. More frequent communication has honed the leadership and communication skills of managers. Infact, 78% of employees perceived their managers to be open to feedback from them. Adobe has also witnessed promotion of a culture of ownership where employees want to participate in the success story of the organization. GE has discovered that the new performance management system has promoted trust between managers and employees – a key characteristic of high performing teams. The new system involves a mobile app called as PD@GE to define near term goals. Summaries of frequent conversations, named “touchpoints” can be captured in the app. GE has also witnessed better results by the use of the new system in the pilot project they have run. Encouraged by organizations such as Adobe and GE, Deloitte has also revamped its performance management system to clearly see, recognize and fuel performance. One of the most important actions taken by Deloitte is to request its managers to evaluate their future intentions with team members rather than rating them on their skills. The new feedback structureincludes questions such as “Given what I know of this person’s performance, I would always want him or her on my team”. This enables managers to take judgment solely on their available knowledge of the team member. While results are still awaited, Deloitte is working towards creating not just a simple but also a rich view of employees’ performance to increase the transparency of the system.  

As per a survey conducted by CEB 43% of organizations are either planning to introduce or open to consideration of new performance management system (n = 296) across the globe while the vast majority of 51% organizations have no plans to do so. Organizations which are planning to introduce are awaiting results from their pilot study while other organizations are awaiting results from organizations which have already implemented the changes. 

Way Forward

With greater focus on continuous feedback & development and absolute performance, we are moving towards a more progressive way of assessing performance. In this changing scenario few practices have become more important and need to be relooked / redesigned for successful implementation of the new approach. These include:

Honing feedback giving skills of managers - This has become more important than ever since this is the cornerstone of a culture of continuous feedback.  The feedback needs to be constructive and future oriented else employees will feel burdened with overdose of feedback. Organizations not only need to provide periodic behavioral training to their managers but also assess them on how they are faring on this skill. Organizations need to provide individual guidance to managers in case they are struggling to be positive in their approach. Leaders need to take initiative and set right examples for others to follow. 

Facilitating real time feedback – The more data points there are on the performance of employees the lesser the subjectivity in assessing the performance. Organizations should use mobile friendly tools which facilitate providing continuous multi-rater real time feedback to employees. 360 degree feedback helps employees understand how they are perceived in the organization. Organizations should empower employees to initiate feedback. This will build a culture of ownership amongst employees. 

The tool should not just provide data but also insights on development areas and track progress on them. Use of Big Data could narrow the gap between an organization’s top and bottom performers by analyzing their daily activities, finding patterns and highlighting the difference in their approach. This will help managers to have more effective development conversation with employees. This will also enable HR to track the quality and frequency of conversations between manager and employees. 

Continuous recognition – Continuous feedback also calls for continuous recognition. It has been researched that employees are best motivated when they receive immediate rewards / recognition for their achievements. Coupling continuous feedback with year-end rewards / recognition is not a very effective way of motivating employees. Thus organizations need to redesign their recognition program to support the new performance management system. 

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Email and Calendar Data Are Helping Firms Understand How Employees Work

Using data science to predict how people in companies are changing may sound futuristic. As we wrote recently, change management remains one of the few areas largely untouched by the data-driven revolution. But while we may never convert change management into a “hard science,” some firms are already benefiting from the potential that these data-driven techniques offer.

One of the key enablers is the analysis of email traffic and calendar metadata. This tells us a lot about who is talking to whom, in what departments, what meetings are happening, about what, and for how long. These sorts of analyses are helping EY, where some of us work, by working with Microsoft Workplace Analytics to help clients to predict the likelihood of retaining key talent following an acquisition and to develop strategies to maximize retention. Using email and calendar data, we can identify patterns around who is engaging with whom, which parts of the organization are under stress, and which individuals are most active in reaching across company boundaries.

Understandably, there may be privacy concerns about examining an individual’s email or calendar, even in a work context. However, you can also get powerful insights using anonymous metadata, where the individual names and specific content are removed. It’s possible to analyze the metadata for content themes and frequency of contact between departments, and to correlate this data with more traditional indicators of process effectiveness, cycle time, right-first-time, and so on. What this gives us is hard data on how processes fail in the organization. We no longer need to rely on anecdotes or employee surveys — instead, we can pinpoint precisely where the breakdowns are occurring just by examining data on day-to-day workflows. We can say precisely what behavior change is needed to make a new process work, and then monitor improvement in real time.

An early example comes from an organization restructure we have been working on. These sorts of projects are usually motivated by a desire to improve strategy execution and reduce costs. Traditionally, only the financial element was measurable, which could easily drive decision-making. For one EY client, we are using data science to make organizational design decisions that accelerate strategy goals. The client wanted to increase collaboration across units, for example, between sales and product development. We used an analysis of anonymized email and calendar data to predict what impact the number of direct reports a manager had on the ability of specific teams to collaborate. That helped us to optimize work design to achieve the result the client wanted.

The potential of these techniques is to change the way managers interact with employees. Today, most managers are doing their best to engage and motivate employees. However, we have to wait for “formal triggers” before we can respond, such as an employee survey or a one-on-one with a manager. Analyzing activity in email traffic might allow us to intervene much faster and find out whether what we are doing actually works. This can become a sort of “real-time employee sentiment analysis” that would transform the quality of insight managers have at their disposal.

Let’s take the example of the recent executive order in the United States that imposed a travel ban on seven mostly Muslim countries. This was a major concern for many technology companies that have a large number of employees on H1-B visas, both from the countries involved and from their neighbors in Asia and the Middle East. If companies were using an artificial intelligence solution that provided real-time insight, they would be able to monitor the level of concern in the organization, perhaps even anticipate the sorts of concerns that employees were having. Many employers set up dialogue sessions with employees to answer questions and attend to their concerns. The only evidence we have on the impact of these sessions was anecdotal. With a “real-time employee sentiment” system, we’d be able to say precisely and respond accordingly, and measure the impact of those responses.

We will always need professional change managers to interpret this data and to design the right sorts of ways to work with employees during transformation or external emergencies, such as the travel ban. What these data science tools can do is make our responses faster and more targeted and tell us what worked in a faster, more reliable, and less invasive way than was previously achievable. In the organization restructuring referenced above, it took only three weeks to analyze a year’s worth of behavioral data to be included in the design of the future processes and structure. In the past, we would have relied on invasive techniques, such as interviews and employee surveys, that not only take up time but also introduce all kinds of bias. Our advice for the change manager of the future is to make data your friend; never reorganize without it.

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How To Successfully Build a Business Operating System for Your Company

Want to increase your business' chance of survival? Franchises are much more likely to survive than any other type of business, so here is what you can learn from them.

American business franchises account for well over $1 trillion in revenue.

The following table illustrates that American franchises have an enviable rate of success compared to other American businesses. Franchisers provide their franchisees with three advantages that most entrepreneurs do not have: an established business system, a profitable plan and financing. Of these three advantages, the critical differentiator is the established business system, what I call a Business Operating System.

The news and our neighborhoods are filled with stories of companies going out of business or reducing their workforces significantly. However, you might be hard pressed to find a McDonalds, Starbucks, Subway or any other franchise who has closed one of its locations in your neighborhood. So, what can we learn from the successes of the American franchise business?

Business Operating System

A Business Operating System (BOS) is your company's unique way of doing things--how it operates, goes to market, produces and deals with its customers. An effective BOS transcends the people who are doing and managing the work, and is more valuable as a result. A business that effectively operates without you is always more attractive to public and private sources of capital.

In order to create an effective BOS it is key to view your product as the business itselfrather than the commodity/service you produce. This paradigm enables the leader to think of the business as a model for 100 others just like it. For example, McDonald's commodity - hamburgers and fries--are not claimed to be the best. However, McDonald's product--its business operating system--is undoubtedly one of the best.

Although many companies spend the time and resources needed to create their BOS, they are disappointed with the results. This is because the components of a BOS are held together by The X Factor.  The X Factor is the same thing that sets great companies apart from their competition. I am frequently asked, "How do Southwest Airlines and The Container Store achieve outstanding results and create such a great place to work?" A closer inspection reveals that their success is less about incredibly innovative management practices and all about The X Factor--discipline.

Great companies create and reinforce a rigorous discipline about the little things that affect their customers, employees and shareholders. They have instilled a discipline in their business (via a BOS) and reinforced discipline at a personal level (via their cultures). Personal and organizational discipline help breathe life into your BOS and enable you to sustain it over time, making it the way you do business rather than just a set of hollow procedures.

Components of Your Business Operating System

It is important to create each BOS component to be scalable, up or down, for future growth or contraction. The components are interrelated as with any living system. Therefore, the successful leaders address all components and understand how they affect each other.

A description of the five components is presented in priority order for effectively creating your BOS.

Processes Systems Roles Skills Structure.

1. Processes

Underdeveloped work processes are the most common risk factor for growing companies, and are the first thing that will crater a company in tough economic conditions. In addition to traditional work processes, we include other processes like communication, decision-making and conflict resolution. It is easy to say, "We need a new system". However, effective leaders have the discipline to resist the illusion that a new system will solve their problems. Streamline your manual processes before changing technical systems. Companies who jump into a new system typically automate their own inefficiencies. This is why Processes should be the first BOS component you create.

Effective processes are:

Clear Replicable Documented Supported by tools Easily accessible.

2. Systems

This component addresses hard and soft systems including: technology, financial, marketing, operations and people. A hard people system is your payroll and human resources information system, whereas soft people systems include performance management, selection, compensation and development systems. Well-designed and applied systems create predictable customer and employee experiences and also enhance your operational efficiency.

Looking at the 80/20 Rule, the 20% of the most effective employees (who produce 80% of the results) inevitably use some kind of a system to enhance their effectiveness. A client recently had to let go of 70% of its sales force and found that the remaining 30% actually accounted for 90% of the company's revenue. Sure enough, the remaining sales people were disciplined in using a system of prospecting, qualifying, proposing, presenting and closing business.

3. Roles

Defining clear roles is a big challenge that requires significant personal discipline. You should write a job description (even if a brief one) for all roles within your desired BOS. Remember to focus on the role itself, not the person. At the early stages of your BOS, one person may play multiple roles. By creating the roles first, you acknowledge this. As your company changes, predefined roles will enable you to make more effective decisions about which roles an employee should continue or discontinue doing and who you should add/delete from the payroll to effectively implement this change.

Resist jumping to the structure component when defining roles--again this requires personal discipline. This step is about defining the required roles to accomplish your company's mission, not how those roles relate to each other.

4. Skills

Now that you have clear roles that your business requires, you can more precisely match the necessary skills to each role. Effective processes and systems will ensure the highest and best use of your talent. Your systems and processes should be created for the lowest common denominator so they are not people-dependent. This will free up your employees' minds and time so they can focus on more creative, proactive ways to improve your business. It is common to see talented employees who are underemployed because they are using excess time trying to figure out how to get their work done.

When you fill your roles, it is important to match the role requirements with the employee's skills and natural style. Ensuring a skills match has obvious benefits. Matching the role with the employee's natural style is subtler but is often even more critical. This can be achieved via a simple style assessment and helps the employee be successful. We all can remember a time when we were in a role for which we were not ideally suited, resulting in greater stress and lower productivity than we (and the company) would prefer.

5. Structure

The key to an effective organizational structure is to design it before you need it--then grow into it. It takes great discipline for leaders to design the other four BOS components before they design their organizational structure. In fact, tinkering with structure is one of the great executive past-times. Unfortunately, this tinkering typically ignores the other, more substantial components.

Structure dictates process. That's why I have outlined the sequence of BOS components in this order. If you create a structure first, your business process will be constrained by your structure and may not reflect the needs of your business and customers. Defining your processes and systems first, as we suggest, results in an organizational structure that supports the way you do business rather than constraining it.

Winston Churchill said, "For the first 25 years of my life I wanted freedom. For the next 25 years I wanted order. For the next 25 years I realized that order is freedom". Your BOS will provide you and your business the order and freedom to work on your business rather than in it.

Although I suggest a particular sequence for creating your BOS, most companies have naturally created one or more of the five components. Since each component may be developed at different levels, it is helpful to prioritize the readiness of each component.

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Challenges And Benefits Of Learning Management Systems

Learn about the benefits of Learning Management Systems and how to define whether your business needs one. Find the roles existing in the learning course development process as well as the comparison of 3 popular and efficient Learning Management Systems. Challenges And Benefits Of Learning Management Systems: Does Your Business Need An LMS?

Try to imagine today’s world without eLearning. Without multiple online courses, mobile apps (Udemy, Duolingo), business training programs, university educational software solutions. Possible, but rather difficult. Corporations, having to keep up with the times, have started to actively use Learning Management Systems taking into account all specific business needs and peculiarities. There are a plenty of LMSs out there that allow to build your own courses by using pre-built content templates, extensions, features, and inserting media. In this article we will be speaking about the challenges and benefits of Learning Management Systems (LMSs); we will also examine whether your company needs one.

4 Top Benefits Of Learning Management Systems 1. Reduce Expenses On Training.

Organizations can reduce cost on hiring and paying wages to instructors, training facilities, and educational courses payment. For example, many companies want their employees to acquire necessary skills and knowledge, as well as direct them through the course or career ladder. They have to pay for language courses in the first case, and provide trainers with fees in the second. Thus, with a single Learning Management System it is possible to reduce these expenses.

2. Make Course Access Location-Independent.

Anytime, anywhere. Learning Management Systems allow employees to complete courses / programs using their PCs, tablets, or smartphones (if there is mobile learning made) from any place, even while being in another country. Simple access with no limits on location and device use is always a great thing.

3. Customize Courses / Training Programs.

Learning Management Systems generally ensure customization of your courses / programs to the needs of your company. You can build in-house courses using tools and features of the chosen LMS. For example, a corporate program that includes material (video, texts, tasks, short quizzes, etc.), a test after each stage, and a final exam. You can set up time for each quiz, see how many times it was passed by each user, and the results of each completion, track progress, and define whether required skills or/and knowledge were acquired. Creating a tailored solution is a good opportunity to enhance educational process and overall performance as well.

4. Build Efficient Educational Environments.

Why not to integrate a single Learning Management System for all situations? A separate course aimed for gaining required knowledge for new employees, a training program to check job progress, acquire new skills, and define the best workers, a course for learning Chinese, a course teaching to “deal with” complicated equipment and computer programs and systems, and so on. It may seem a bit difficult at first glance, but modern Learning Management Systems provide pre-built templates for content, many extensions, simple solutions for inserting audio, video, images, tests and exams, and other efficient opportunities to create and customize courses. Most Learning Management Systems offer convenient tools that allow to create custom courses and thus implement educational, teaching, and management processes in the organization.

3 Roles To Perform In Course Development 1. Administrator.

They customize the eLearning solution to the needs and requirements of a certain organization, and manage the educational process by adding users, user groups, etc. Also an administrator creates a library of courses, making connections between a certain course and user group (for example, courses for sales managers will be shown for them only within a company).

2. Trainee.

They pass the course program including studying required materials, completing tasks, taking tests and exams.

3. Trainer.

They create training courses: Content that can include lectures, text, audio, and video materials, and develop evaluation systems involving tests, quizzes, exams, their order and evaluation surveys as well. Thus, the teacher tracks user progress, analyzes results, and fills the course with content.

Does Your Company Really Need To Implement An eLearning Solution? 

You may want to answer the following questions to find out:

Do you already have courses prepared? Do you have someone in charge (instructors, teachers, etc.) of training at your company? Do you need to track employee results and progress? Do you need to have a training program to quickly and efficiently onboard employees? Do you often hire new employees? Do you have specific skills your employees have to acquire? Do you have employees in multiple locations? Do you charge a fee for courses? Do you offer external training to customers? Do you offer and report certification training to motivate learners? Do you handle hundreds of registrations per some learning event? Do you have a learning strategy and program to educate employees?

If you have at least 5 answers “Yes”, you are ready to integrate learning courses or another eLearning software solution.

So, now you can proceed to the choice of a Learning Management System to build a tailored course or program. There are a lot of options, and to choose the right one isn’t so simple. Here we will compare 3 of the most popular Learning Management Systems; iSpring, Moodle, and Totara. They suit for training and educating, and they all provide large opportunities to customize a solution to your organization’s necessities.

What’s important, all of these Learning Management Systems are SCORM compliant. You can learn more about benefits and principles of the standard here: Building eLearning Software: Why Choose The SCORM Standard?

Learning Management Systems provide not only basic features like blended learning, SCORM compliance, asynchronous learning, and skills tracking, but also a lot of advanced features such as mobile learning, certification management, and gamification (used primarily for motivation), as well as social learning (except iSpring).

Also, when building an eLearning solution, ensure it will have high level of scalability, user-friendly interface, and simple reporting, as lack of these features is one of the most common reasons Learning Management System users want to switch off their own.

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Top 10 LMS Requirements For Corporate Training

Ready to move your corporate training online but aren’t quite sure what your LMS needs are to get the job done? In this article, I´ll share the top LMS requirements for corporate training that you need to know about when choosing a learning management system for your organization.

LMS Requirements For Corporate Training

In many ways and in the simplest of terms, an LMS is a lot like a puzzle. It must have all the key pieces in place, all of the functions and features your organization needs, if you truly want to get the most return from your investment. In this article, you’ll discover the top 10 LMS puzzle pieces that you’ll need to create a whole and effective corporate training experience for your employees.

1. Site and Online Course Customization

Are you going to be able to integrate your branding into the LMS? Is the LMS vendor providing you with your own online training website that employees can log in to access their online training modules? One of the most important LMS requirements for corporate training, particularly for organizations who want cohesive branding, is a product that allows you to customize virtually every aspect of your online course and of your online training site. This can add value to the online training course by increasing its credibility, as well as its aesthetic appeal, which enriches the online training experience as a whole.

2. eLearning Course Building

When considering LMS requirements for corporate training, effective eLearning course building tools are a must-have. Not only should the LMS provide a wide range of tools you can use to create the online training course that you have in mind, but it should also allow for both usability and design freedom. In other words, it should be easy enough for your design team to use, while still providing the features they need to take full advantage of their skills and talents.

3. Multimedia Integration

Videos,interactive scenarios, and multimedia presentations are all key ingredients to an immersive online training course. This means that one of the major LMS requirements for corporate training is that it has to offer you the ability to integrate multimedia into your eLearning design quickly and conveniently. Can you upload your own videos into the eLearning course, or integrate links that your online users can click on to access online presentations hosted elsewhere? Determine which multimedia elements you will be using regularly and then ensure that the LMS supports these media.

4. Updating Capabilities

Chances are that you may need to update your eLearning course contents on a regular basis. This is especially true for compliance online training courses or those that focus on product knowledge. Online assessments will also need to be updated on a regular basis, as well as certifications and links to other online resources. As a result, your LMS should give you the power to modify and add elements to your eLearning course design with relative ease.

5. Multilanguage Support

Even if you aren’t planning on delivering training to international audiences at the moment, you may need to do so in the future, particularly if your organization is considering going global. Does the LMS offer you the opportunity to add subtitles or captions to your eLearning course, or to create eLearning templates that can easily be modified to accommodate for other languages?

6. Online Assessments

Online assessments are on the most effective ways to gauge the effectiveness of your online training program. They give you the power to determine if your corporate learners are actually absorbing information and skills or if your eLearning strategy may need to be fine-tuned. As such, having a learning management system that allows for easy test, quiz, or exam integration is fundamental. Do they have a database of questions that you can use? Are there any online templates that will help to make the development process simple and straightforward? Does the LMS enable you to create interactive assessments?

7. Tracking Reports

Learner performance, progress, as well as strengths and weaknesses are just some of the items included in online tracking reports. Having a LMS that features online tracking capabilities offers insight into how your employees are faring and whether your training strategy is achieving its goals and objectives. Some LMS providers offer dashboard reports, while others may deliver them directly to your email inbox.

8. Compliance

Failing to meet compliance requirements can lead to a variety of negative consequences. Therefore, one of the LMS requirements for corporate training should be that your LMS should be able to track compliance training results and help you to ensure that every member of your staff is meeting the standards. Some may even be able to issue compliance certifications that your employees can earn by completing specific online modules.

9. Feedback tools

One of the powerful tools you have at your disposal is learners' feedback. Having a LMS that has built-in poll, survey and questionnaire online tools can make the data collection process more efficient and streamlined. You can find out which aspects of your online training course you may need to improve and which are offering your corporate audience the most value, without having to use third party poll sites.

10. eCommerce

If you are planning on selling your online training courses, in addition to offering them to your employees, it’s wise to have a built-in eCommerce platform. There are certain LMS vendors who offer you the opportunity to set up a virtual storefront, while others allow for shopping cart integration directly on your corporate site. If you are going the eCommerce route, then you may also want to look for a learning management system that also has marketing and social media features integrated, so that you can promote your product online.

Keep these LMS requirements for corporate training in mind when selecting your next LMS to ensure that you get the most value for money and that you provide your employees with the skill set development they need to achieve professional success.

 

September 2017

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Beat the Machines with these 10 Employability Skills for the Future!

Experts are predicting that automation will make its way to the general workforce as early as 2020. With robotics and AI progressing by leaps and bounds within the last decade, we really can’t deny that this might be the future that’s awaiting all of us. In the coming decades, machines will be doing most specialized and manual work; while we humans will need to adapt and move on to new careers.

We came up with this list so that we can start working on them today. You really won’t be that surprised that some of the skills to be mentioned have already been part of our repertoire for quite some time. Nonetheless, you might also be astonished at how much the development of these skills was taken for granted for so long, even though these competencies will eventually define how we will work in the future.

There will also be new skills that hinge on the advances in technology. These competencies weren’t even around a decade ago; but will be ever-defining skills to be competitive in the future workforce. With these in mind, there is now a definite need to polish these competencies and deepen our understanding of how our careers depend on them.

Without further ado, here’s the list of what we believe will be the top ten employability skills for the future workforce:

Top 10 Employability Skills for the Future Workforce

1. Creativity

One of the biggest predictions is that the future global economy will be made up mostly of creative output. Industries that have a ‘human touch’ such as advertising, arts, design, music, and publishing will be left mostly untouched by automation. Come to think of it, even we humans have a hard time comprehending what makes things ‘beautiful’ and ‘compelling’, machines are a very long way from it.

Humanity’s use of innovation and imagination in developing creative solutions just cannot be replicated. Creativity is one of the keys to human survival and dominance – and for a good reason. It has allowed us to improve our quality of life and push the envelope in going beyond what was always assumed as ‘humanly impossible.’

Creative thinking is one of the professional skills that will be most sought-after by future employers. As one of the integral skills for employment, it would be a good idea for us to start honing our creativity even more as early as now.

2. Complex Problem Solving

Another skill in our list of employability skills of the future involves finding creative solutions through problem-solving. Solving problems can actually be done by automation; and in some cases, machines might even prove to be better than us humans. Machines are most effective in problem-solving scenarios that involve choosing preset actions dictated by standard procedures.

However (and that is a big however), most problems don’t fall under any pre-set configurations or procedures. Most problems involve complex scenarios that bring about more elaborate consequences – all of which cannot be defined by parameters of 1s and 0s or any mathematical algorithms. Oftentimes, problems have no rational answers at all!

Now, this is where humans have a big advantage over the automatons. We have the ability to perceive different unstated factors and considerations when solving problems. Things like empathy, interpersonal sensitivity, ethics, and morality are some examples of implied elements of decision-making that only we humans can discern.

Being keen and sensitive to these factors will make complex problem solving one of the most sought-after employability skills for the future workforce.

3. Critical Thinking

Critical thinking is the ability to identify problems, gather information, and make sense of data to find viable solutions. The most important factor though is the ability to recognize implicit assumptions and identify significance of certain details on the issue. The human advantage is the ability to perceive how “everything” is connected with each other. To add, critical thinking also demands awareness that details shouldn’t be taken at face value.

Gauging priorities, gathering information, and interpreting data can be easily done through automation. Nevertheless, critical thinking is still part of this list for human employability skills of the future. This is due to the fact that making sense of all the complex relationships, interrelated propositions, and implicit assumptions when facing issues allow us to better prioritize and interpret information and use them to come up with the best solution to a presented problem.

4. Virtual Collaboration

Advances in technology have allowed people across the globe to work together through remote virtual teams. This has then opened the workplace to more diversity – being able to work with different people from divergent cultures, across different time zones and geographical areas.

Of course, face-to-face interaction will still be the top choice in workplace communication. Nevertheless, we really can’t blame organizations wanting to employ the best workers on the planet – while looking for the most efficient and cost-effective way to make the remote workforce system work.

Virtual collaboration is one of the employee skills that we need to adopt as early as now. Aside from the usual tools and processes, soft skills in the workplace are also needed for this. Skills for employees of virtual teams include, but are not limited to, collaboration, cross-cultural sensitivity, and adaptability to a multi-cultural environment.

5. Social Intelligence

Here’s another one of these future skills employers want – social intelligence. Also generally known as ‘People Skills,’ social intelligence pertains to the way we are able to go about complex social relationships. Simply put, it is our aptness to associate with other people.

People skills are also closely linked to emotional intelligence – which is the recognition of our own and other people’s emotions and handling them appropriately. Social intelligence is definitely one of the skills you need for a job in the future because it will absolutely be needed for interaction with clients, customers, and peers; especially when most interactions will already happen online.

6. New Media Literacy

Today’s definition of computer-literacy is obsolete. Gone are the days when the ability to operate the computer and use office-related applications are the only skills needed for a successful career. Literacy to new media is definitely one of the more important employability skills for the future.

The use of different digital media is slowly becoming the standard of ‘computer literacy.’ These new media include, but are not limited to, blogging, social media, online publications, digital games, and virtual reality, just to name a few.

Skills for the future workforce would somehow merit leveraging these so that employees can conveniently transact with customers or each other on the aforementioned platforms.

7. Lifelong Learning

Employment skills for the future require one to be a lifelong learner. This kind of an educational mindset means that a person becomes a self-directed learner, able to operate without set agendas or curriculums – just an attitude to learn what is or will be needed.

Personal and professional development and anticipation of skills for the future will be one of the defining skills of the future workforce. Commitment to lifelong learning also brings about other competencies and attitudes like having a growth mindset, iterative thinking, and viewing mistakes as learning opportunities – and these are some employability skills for the future.

8. User Experience (UX) Mindset

It is said that most of the customer-service related jobs will be automated within the next few years. Just imagine there wouldn’t be anyone to talk to over the phone, or even personally, about concerns and issues. Every transaction would go through pre-recorded, automated responses.

What would be missed is the total customer / user experience. And this is why there would be a high demand for people with user experience mindsets, especially designers. The future will require products or processes to be specifically designed so that the end user would be more satisfied with quality and usability at the onset rather than having to go through the entire customer service process.

9. Design Thinking

Another one of the cutting-edge employability skills of the future is design. Design thinking takes a different approach when analyzing situations and solving problems. Aside from the usual, structured, problem solving and analytical approaches, design thinking draws more on ‘business soft skills’ rather than the technical ones.

For example, aside from using approaches in engineering or software programming, design thinking also utilizes creativity, systemic reasoning, and intuition in developing creative solutions.

10. Responsible Digital Citizenship

In a world where the boundaries between the virtual and the physical world are blurred, responsible digital citizenship is another one of those must-have employability skills for the future. Responsible digital citizenship means using online resources responsibly.

For example, a responsible digital citizen can distinguish between fake and real information found on the web. In addition, a responsible netizen has genuine concern for other users and would know how to handle malicious websites, fake news, malevolent beings and trolls in the online sphere.

With laws changing due to the ever-increasing influence of the internet, there will come a time when a person’s digital footprint will also be a substantial component of hiring and employability.

Why is this future employment skills list so important today?

The next few years will be the most crucial in ensuring that we still get to retain our livelihood come the next few decades. This is why as early as now, we need to equip ourselves with the top employability skills for the future – future skills that will keep us competitive in a very high-tech workforce.

We hope that this employability skills list was able to help you figure out what new skills you need to learn and what other competencies you need to work on. With automation threatening human jobs – the ones that we currently have – we always need to upgrade ourselves and develop the skills that are desperately needed for the future workforce.

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How to measure the impact of your L&D program?

Learning effectiveness is a two-fold assessment that evaluates the quality of the intervention itself, and its impact on business outcomes.

Today, employee capability development is under the spotlight, primarily because organizational success factors are rapidly evolving. Organizations are demanding new skill sets to cut through the intense competition.  Organizations are pouring billions into learning and development initiatives, in a bid to empower employees to be their productive best. However, HR leaders often shy away from justifying these L&D expenses. They measure the quality of the intervention itself but miss out on how it adds value to the top line or to business growth. In a situation where the HR landscape is wrought with constraints of time, budget and intent, a failure to justify the value-add of L&D to business can dissuade organizations from investing in employee development programs. It, therefore, becomes necessary to measure and showcase the impact of L&D programs. 

A number of traditional models for evaluating training effectiveness have made the rounds of HR textbooks, a renowned one being the four-level Kirk Patrick Model. Companies find themselves at various stages of evaluation i.e. reaction, learning, behavior, and results, with very few actually measuring results in line with the business strategy. Moreover, today we see a highly evolved L&D landscape, with diverse learning channels like online, mobile, classrooms, gamified learning, social learning and so on. Each of these demands a different training-evaluation approach i.e. a blend of quantitative and qualitative metrics to measure training impact. However, most companies continue to carry out standard evaluations such as happy sheets, testimonials, line manager feedback, psychometrics assessments for mapping behavioral changes and so on. None of these really assesses learning effectiveness in alignment with strategic functional and business goals. It is time HR professionals move beyond the obviously seen and delve deeper into the business impact of L&D initiatives. This is a must to win over the confidence of business leaders and contributes at a strategic level. 

Learning elements you must measure

We are no longer in the age when measuring feedback ratings and completion rates is enough. A data-backed training analytics mindset is a pressing need in L&D today. As a learning and development professional, the first step is to look at the core L&D outcomes in itself i.e. the key metrics that capture how your learners have changed as a result of a learning intervention. Here are some of the key aspects to think through: 

Skill attainment: This is a typical training evaluation approach that relies on measuring knowledge levels, both pre-learning and post-learning. Think of knowledge-gain in conjunction with the role and the deliverables the learner is expected to perform well in.
  Skill application: Skills without real-world application do not serve the purpose. It is, therefore, important to measure, to what extent the learner is practically applying the newfound knowledge/skill in his or her role. 
  Behavioural changes: Primarily this applies to culture and soft skills training. It is important to know how well the learner has imbued the organizational values or soft skills which are required to succeed at the job. Ideally, the personal values of the learner should be completely aligned with the organizational values. Behavioral changes must be assessed at both the individual and team levels for the learner. 
  Goal attainment: L&D outcome evaluation must be closely tied to goal attainment i.e. the role-based performance goals laid out for the learner. L&D effectiveness must, therefore, be intricately tied in with the performance management process. How to quantify outcomes in business terms

The above four-step assessment will help you arrive at an overview of your learning and development outcomes- whether they are giving you the desired performance results in the learner’s role or function? The next stage is to drill deeper into the fourth element i.e. goal attainment at an overall business level. For this HR professionals must evaluate the return on investment of L&D initiatives in quantitative business terms. Measure effectiveness both quantitatively and qualitatively is a necessary step to generate the necessary buy-in with the CXO suite. Here is what you should look out for. 

Sales growth: Training (especially sales-specific training) should result in sales revenue growth. Conduct a pre-training and post-training analysis of employees’ productivity and workloads to understand whether the training has improved delivery numbers.
  Cost reductions: An objective of training is to increase efficiency, thereby enabling cost savings. For example, employees may come up with cost-reduction projects when trained for opportunity-seeking. Monitor the relationship between skill enhancements / behavioral changes by the learner and reduced costs in the immediate function/team.
  Employee retention: The role of training is not just to improve business metrics, but also to indirectly aid business by providing the right talent. Training is an effective engagement tool that creates employee stickiness within an organization. It thus helps reduce recruitment efforts and costs. Track your learners for their retention levels and get to know whether learning initiatives are actually valued by your people, or do you need to change course in your L&D strategy? Embrace L&D analytics

Measuring the outcome of L&D initiatives and ensuring their effectiveness is a talent analytics effort. HR leaders must rope in the latest technologies and learning / HR evaluation systems and processes to make training evaluation an ongoing commitment. HR must move away from the mindset of one-off measurements and adopt a continuous process to improvise on learning methodologies. Evaluations must be real-time, data-driven and actionable to achieve the desired learning outcomes. Only then can organizations extract maximum value from learning and development interventions. 

The goal is to build organizational capability

The goal of learning and development is to build individual and organizational capability and help navigate the business conundrums of today and tomorrow. At the employee end, learning and development also serve as an engagement and retention tool, by offering career advancement opportunities. These dual-fold objectives can be achieved only when the L&D strategy is effective and optimized to the core. Every stage right from training needs identification to implementation to measuring effectiveness must be revisited and revised as per need. Only then, can HR professionals expect to create a sustainable change in the knowledge, skills, and attitudes and align talent with the organizational needs.

 

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Learning Analytics and the Value of Understanding L&D Metrics

When learning & development organizations successfully prove that they aren’t merely cost centers—that they reliably and verifiably deliver positive results to the bottom line of the enterprise—they inevitably gain stature and influence with business leaders. By establishing a solid metrics and measurement program, underpinned by a learning analytics process, learning leaders gain access to the evidence that illustrate their team's everyday impact.

Analytics turns learning metrics and measurement into insights that enable informed decisions and actions. Learning insights may include process efficiency, alignment of employee skills to business needs, and the impact of learning on key organizational metrics like staff turnover and leadership development capabilities. When analytics are leveraged effectively, they can influence not just how courses are designed or how the L&D function is staffed, but also larger decisions such as hiring and competency development.

The benefits of structured and consistent development and communication of learning analytics may extend to all levels of the organization.

 

When learning experiences are constantly being reevaluated for effectiveness via analytics, a few things tend to happen. Learners are more likely to be engaged when they receive the right level of training, which in turn spikes knowledge transfer and application. Learners are also more likely to enjoy a supportive and motivating work environment, as learning analytics can help diagnose non-learning issues that impact performance.

L&D organizations have much to gain from investing in L&D analytics, including identifying and addressing obstacles to learning effectiveness. Basing recommendations and budget requests on learning analytics adds a degree of professionalism and credibility to a business unit that is often at a loss for hard numbers. It also enables learning leaders to prioritize effort and make changes to better align with business goals and optimize the organization’s function.

Business stakeholders benefit from analyzing L&D metrics by being able to see where their investment of time and budget goes. They can see how the learning organization is addressing and impacting operational efficiency, learning effectiveness, employee performance, and ultimately business results.

Choosing the Metrics to Analyze

When we talk about metrics and measurement, we’re typically referring to gathering data on three areas: efficiency, effectiveness, and outcome.

Efficiency is generally thought of as learning-centric metrics—number of learners, hours of training, cost to produce content, etc. Efficiency measures can be useful as supplemental data and are of interest to internal L&D staff. Their value to business stakeholders is limited, though.

Effectiveness metrics are evaluations-focused—Levels 1–3 on the Kirkpatrick scale—and include things like learner satisfaction, quality of deliverables, knowledge acquisition, and performance impact. Some of these things are more valuable than others when it comes to proving business impact, but effectiveness measurement is the area where both L&D and business stakeholders share common ground. Unfortunately, too many metrics and measurement initiatives don’t go beyond effectiveness to the third category…

Outcome metrics are ultimately what really matter. Outcome looks at bottom-line results, such as revenue and cost reductions generated by the learning initiative. To the extent that efficiency and effectiveness metrics matter, they provide validation and explanation for the outcome.

Potential Pushback to Analytics

Some learning professionals are hesitant to initiate a learning analytics practice for two reasons: the perception that they must address everything at once, and concern that leadership will use the insights in a penalizing way.

Systems thinking and optimizing ongoing operations are two keys to success. Systems thinking helps escape the L&D-only mindset and into the perspective of the business. Systems thinking informs the questions to ask, your stakeholders, data to gather, accountability to provide and use data, the technology platform, standards, definitions, and reporting that drives use.

One of the first steps should be to review the current state. What metrics are you gathering, if any, and are you using them to inform decisions? If a metric is not informing a decision, there’s no need to keep gathering it. If it is, optimize the specific data and learn how to turn it into insights that inform decisions that matter to L&D and the larger organization. Over time, add more metrics, always keeping in mind the decisions they inform.

There will be metrics that you actively manage and metrics that you monitor. What’s the difference? You manage metrics that need optimization and other adjustments. There are other metrics that may already be optimized, so they just need monitoring. Further, determine target thresholds for the monitored metrics that will trigger an “alarm” for active management.

For learning professionals who lack experience with L&D analytics, there are many resources available, starting with the Center for Talent Reporting. Critical thinking, the ability to think like a stakeholder, and the ability to ask good questions are key when proving the business value of learning.

Content was really clear 464 Content hit the target 378 Thanks for the learning boost! 355

There’s a Data Analyst on the L&D Team?

Employees and their managers want to know if training measurably improves performance. CEOs and senior leaders are asking, “Where’s the evidence for learning and development’s impact on business results?” CFOs are asking, “What’s the return on investment for the dollars we spend on employee development?” There’s a rise in demand for L&D talent who can answer these questions with evidence and proof.

Data Analysts: A New Breed of L&D Talent

A new breed of L&D talent is using data and analytics to answer questions about learning’s impact on business results and employee performance. L&D data analysts use analytics to inform decisions about learning strategy and data for learning solutions design, deployment and investment. And while the titles may be different from company to company, the focus on learning and development analytics is the same:

“Ability to negotiate data sourcing agreements with stakeholder partners” – Learning & Development Analyst “Uses data analytics to offer Leadership/Strategy Committee insights from across the Learning and Development portfolio” – Learning & Development Measurement & Analytics Data Scientist “Leverage the workforce analytics knowledge base to promote an evidence-based approach to all things Learning” – Associate Director, Learning Analytics

“Research,” “analysis” and “measurement” describe the focus. “Data collection” and “visualization” describe the skills. Experience with SPSS, SAS, Tableau, xAPI and learning record stores (LRS) qualify the specialized expertise. These are capabilities that just a few short years ago, you would not have seen on an L&D team.

The combination of learning, development and analytics talent is unique and creates an opportunity for established L&D professionals to reinvent themselves. With the rise in demand for talent with strong L&D backgrounds and expertise in analytics techniques and technology, there’s a brand new function in learning and development. The future for L&D analysts is bright!

What’s Driving the Rise in Demand for L&D Analysts?

Learning analytics expert Mike Rustici with Watershed suggests the rise in demand for L&D data analysts comes from increased accountability and transfer of best practices. “Just about every group, department and function across the enterprise is held accountable for using data to demonstrate results. You’re seeing an increased desire from senior leadership for that level of accountability throughout the organization. You’re seeing people coming into L&D leadership roles from other parts of the organization. They’re bringing their expertise and best-practices with them including the infusion of data and analytics.”

Christopher Yates, head of learning and development at Microsoft, sees L&D data analysts as a critical part of the digital transformation. “It’s essential. I can’t imagine having an L&D team today that is not supported by dedicated data analysts. Without L&D analytics, you’re basing your decisions on luck or the way we’ve always done things. Without insight, all you have is a guess, a hunch or a feeling in your stomach about what’s working or not working.”

L&D Data Analysts Are Here to Stay

There’s technique, technology and, now, talent for L&D analytics. The dynamics of complex learning ecosystems require data-driven design for learning solutions and analytics for insights on L&D performance. We don’t have to cross our fingers and hope learning and development fulfills its purpose. We have the data and the L&D analysts to prove it.

L&D data analysts are changing the way learning and development leaders build their teams. As L&D is increasingly held accountable for evidence that shows impact, so will the rise in demand for talent who can use data and analytics as proof for results. Yes…there’s a data analyst on the L&D team, and they’re here to stay!

Kevin M. Yates is creator of The COURAGE Model© and advisor for measurement, evaluation and analytics for learning and development. Connect with Kevin on his website, Twitter, Facebook, LinkedIn and YouTube.

 

Content was really clear 407 Content hit the target 319 Thanks for the learning boost! 339

Global Trends in L&D Analytics

All functions in today’s organizations face tremendous challenges to show value. As a result, the Learning & Development community is responding with changes in its approach to measurement, evaluation, metrics, and analytics.

Much has changed since the global recession. Budgets are tight, accountability is everywhere, and business results are expected routinely. All functions in an organization, including Learning & Development, face tremendous challenges to show value. The good news is that the Learning & Development community is responding with changes in their approach to evaluation. Here are seven metrics trends that are occurring globally and particularly in the U.S.

1. There is increased focus on the impact and return on investment (ROI) of major programs.

Although this trend has been evolving for years, the movement has been significant in the last five years—it is being driven by the recession itself. In 2008, many companies found themselves to be bloated, bureaucratic, and inefficient, and they began to trim their organizations during the recession, even if they were still financially strong. Senior executives and the chief financial officer are vowing to make sure their organizations are efficient, responsive, lean, and mean. This is causing major projects to be pushed to the impact and ROI analysis, showing a connection to the business and the financial ROI, the ultimate measure of success. In some cases, an ROI forecast is required before the program is designed, developed, or implemented.

Top executives crave impact and ROI data. A major study, supported by ASTD, showed that the No. 1 measure desired by CEOs from Learning & Development is business impact (“Measuring for Success: What CEOs Really Think About Learning Investments” by Jack J. Phillips and Patricia Pulliam Phillips; ASTD, 2010). With input from 96 Fortune 500 CEOs, this study revealed that the No. 2 measure is ROI. At the same time, these executives indicated that the current level of measurement is far from where they want it. Only 8 percent said that they see the business impact now, while 96 percent wanted to see it. For ROI, 4 percent see it now, and 74 percent want to see it in the future.

An important target for this level of analysis and accountability is soft skills, where it is more difficult for an executive to see the value. When the programs are important and expensive, executives especially want to see the value. In a study of 232 Global Leadership Development directors, 88 percent said there was an emphasis on ROI, and the No. 1 reason was the pressure for cost and efficiency (“Measuring Leadership Development: Quantify Your Program’s Impact and ROI on Organizational Performance” by Jack J. Phillips, Patricia Pulliam Phillips, and Rebecca L. Ray; McGraw Hill, 2012). This same study revealed that for leadership development, 34 percent of programs are measured at Level 3, Application; 21 percent measured at Level 4, Business Impact; and 11 percent at Level 5, ROI. These are the most ambitious numbers we’ve seen from leadership development.

2. The budget for measurement, evaluation, metrics, and analytics (MEMA) is increasing.

The Learning community has underinvested in measurement, evaluation, and metrics. Consequently, during the recession, many Learning leaders were not able to show the value of major programs and projects. Routine accountability at the level of evaluation sought by executives did not exist. Most organizations without a comprehensive approach to MEMA were spending approximately 1 percent of the budget on tools. Proactive Learning leaders are justifying additional expenditures by showing the value of current projects. Learning leaders are using the results to move to a best practice of 5 percent of the Learning budget to be spent on metrics and evaluation.

3. Responsibility for MEMA rests with all the team.

This trend has been shifting for some time, but it accelerated during the recession. Two decades ago, there was a move to centralize evaluation and have a core group of people with that responsibility. Although this appeared to be efficient, it often was ineffective. Every other member of the team— the designers, developers, facilitators, participants, and even managers of participants—would indicate that measurement and evaluation was not their responsibility, claiming the evaluation team should be doing this. Proactive Learning leaders have recognized that evaluation is everyone’s responsibility, and sharing the responsibility makes it much more effective. It reduces the resistance and keeps everyone accountable. Often, it is more efficient in terms of resources, because they all have their full-time job with part-time evaluation. Still, in large organizations, a small core group is available for very technical issues.

4. Finance, Accounting, and the CFO are more involved in L&D.

This trend has both good news and bad news, but is probably obvious to most Learning & Development functions. You don’t have to look far to see increased involvement of the Finance and Accounting departments, not only for Learning & Development but for other functions, as well. The CEO is pressuring the CFO to use the concept of ROI, which originally was developed to show the return on investing in capital expenditures (buildings, tools, and equipment). The concept now has moved to non-capital areas such as Human Resources, Marketing, Technology, and Quality. This has brought the CFO into the process as he or she implements ROI into these areas. According to Gartner research, many chief human resource officers (CHROs) are reporting to the CFO. Since most Learning & Development functions report to the CHRO, this brings the CFO into the reporting chain of command for some Learning functions. Proactive CLOs are stepping up to this challenge, making sure they have CEO- and CFO-friendly data, bringing Finance and Accounting into the process, and pursuing them as a colleague, not as an enemy.

5. Learning leaders are more proactive with impact/ ROI analysis.

Before the recession, many learning leaders would wait for the request to pursue a more rigorous analysis, particularly ROI. Unfortunately, the recession showed that approach to be disastrous. When the Learning & Development function is asked for this ultimate level of accountability and nothing has been put in place, it’s often too late. This places the Learning team on the defensive, with a short time line, and on the top executive agenda—not a good place to be. Proactive leaders learned their lesson and they are not waiting for the request. They are building capacity and experimenting with impact and ROI. They want to be driving the process, not reacting to it. They want to set the agenda, time line, and pace.

6. There are still barriers to impact/ROI use.

Although the concept of connecting learning to impact is all traceable to the early 1950s, and the use of ROI traces to the 1970s, the concept still does not enjoy the widespread use executives prefer. Some significant barriers must be overcome. Proactive Learning leaders are minimizing, diffusing, demystifying, removing, or going around those barriers. Here are the top five:

            Fear of results. As you can imagine, any program owner is nervous when someone is conducting an ROI study on his or her program and it’s negative. How will it affect me or my program, or my performance? Will it be discontinued, diminished, or not respected? While these thoughts are common, proactive leaders are managing the process. They use ROI as a tool for process improvement, not performance evaluation for the team.

            The perceived complexity of ROI use. Some proponents of ROI have created this fear by trying to develop complicated formulas. In reality, ROI is a ratio first encountered in fourth-grade mathematics.

            Perceived cost of an ROI study. Some think ROI costs too much, and they don’t have a budget or the time. In reality, costs are small. For a major program, the total cost of an ROI study is usually less than 1 percent of the program cost. It rarely goes over 5 percent, and that’s when a particular program is inexpensive. Proactive Learning leaders learn to manage this cost by building internal capability.

            They don’t know how to do it. This was a good defense 20 years ago, but not any more. Impact/ROI evaluation is now a part of the preparation for Learning & Development and Human Resource Development degree programs. ROI certification is offered globally, with more than 7,000 individuals having participated in the ROI certification offered by the ROI Institute.

            The client hasn’t asked for it. As mentioned in trend #5, this is a disaster. Proactive Learning leaders are reminding the team that we want to be in control of this issue.

7. Impact/ROI evaluations have many uses. Proactive Learning leaders are pursuing a more comprehensive measurement and evaluation system, linking Learning & Development to the business in credible ways and occasionally developing ROI studies for major programs. This proactive evaluation generates many great uses:

            Increase funding. Since the recession, this is the No. 1 reason for pursuing this issue.

            Satisfy executives in a request for accountability. Before the recession, the No. 1 reason for exploring impact and ROI was to meet a particular request from an executive group.

            Improve programs. This is the preferred reason for using impact and ROI and is the No. 1 reason advocated by the ROI Institute.

            Increase support. A key target for communicating results is participants’ managers. Showing the results at the impact level essentially ties the learning to the key performance indicators (KPIs) of these managers. That’s what’s needed for them to provide the level of support needed to make learning a useful process.

            Build business partnerships. To be effective, partnerships drive programs, funding, and new initiatives and make the process work smoothly. When executives see that L&D is making a contribution, they are more willing to be a viable business partner. Proactive Learning leaders are translating the business contribution of L&D to a successful business partnership.

            Improve client relationships. The ultimate client—the person who funds the program—has a much better image of learning and involvement when he or she sees learning as a valuable business contributor.

            Earn a seat at the table. For more than a decade, we have heard the comment that the Learning & Development leader (i.e., the CLO) should be involved in decision-making at appropriate high-level meetings. When a business contribution is clearly there, it’s much easier to earn and keep a seat at the table.

An expert on accountability, measurement, and evaluation, Dr. Jack J. Phillips provides consulting services for Fortune 500 companies and major global organizations. Dr. Phillips is chairman of the ROI Institute, Inc.; the author or editor of more than 50 books; and creator of the ROI Methodology, a process that provides bottom-line figures and accountability for all types of learning, performance improvement, Human Resources, technology, and public policy programs. For more information, call 205.678.8101 or e-mail jack@roiinstitute.net.

Patti P. Phillips, Ph.D., is president and CEO of the ROI Institute, Inc. She earned her doctoral degree in International Development and her Master’s Degree in Public and Private Management. While working for a large electric utility, she played an integral part in establishing Marketing University, a learning environment that supported the needs of new sales and marketing representatives. An accountability, measurement, and evaluation expert, Dr. Phillips is also the author and co-author of several books, including “The Bottom Line on ROI” (CEP Press, 2002), which won the 2003 ISPI Award of Excellence.

June 2017

Content was really clear 444 Content hit the target 361 Thanks for the learning boost! 362

Who is going to disrupt education?

We, the Learning Gypsies, were recently part of a really cool event called The Creative Summit, in Skelleftea, Sweden. Yes, we didn’t know where it was on a map either, but we will never forget it now.

The event, brilliantly organized by Peter Mandalh (@PeterMandalh ) and his team, was focused on the theme “the Future of Work” and we had the privilege of sharing the stage with some of the leading thinkers about this fundamental topic: @congbo , @mikearauz, @Joeli_Brearley, @LydNicholas , @alisoncoward ,@disruptandlearn @jeremycdalton and @alexanderneuman , who did an incredible job intervening our three kids during a panel that helped redefined what it means to be successful.

It was really strange to have just 3 hours between sundown and sunrise, (something to experience in a lifetime) but the 2 days we spent in lapland was one of the best parts of this trip.

We learned a lot about the future from all the sessions we saw during the day: about Robots and A.I, new Organizational Models, the Skills of the Future, a fairer future with no discrimination against pregnant women, the wonders and possibilities of VR and AR, and about how improving collaboration might give us a chance at a better future at work.

Our approach to the question of the future was framed from our experience during our research about the future of education.

There is no video of the talk, and you might find some bits on twitter, but considering all the people who have requested the transcript, we decided to post it on medium.

(We would like to hear your reactions and get some feedback, so please let us know by writing a comment when you are done)

I’m Iñaki and I’m Hazel. We have a hypothesis about the future of work we are dying to share with you, but before we do that, we would like to tell you a little story.

Almost a year ago we left our life, our friends and the hype of Brooklyn, New York to research the future of Education around the world.

Our 3 kids, my mom and the two of us have been traveling from country to country for over 11 months looking for the answer to one question: how should kids learn in a world where everything will change?

CHANGE

A world where they might not need to learn to drive, where a lot of the current work will be automated… a world where cryptocracy might be the new black, food will be harmless and immortality might be a thing we need to pre-order.

STORY

And as we all know, with changes come surprises.

What we thought was going to be easy, was more difficult. And some of the challenges we anticipated, turned out to be easier.

We thought it was going to be harder for the kids to move around, city to city, from one continent to another. After visiting 42 cities in 11 months they keep on surprising us with their incredible flexibility and adaptability.

We thought it was going to be easier to take the kids to world class Museums, but they wouldn’t have it. After two museums in Sao Paulo they told us: if you want me to walk all day looking at old things I can’t touch, at least tell me what we are doing ahead of time.

To tell you the truth it’s been us the adults that have struggled the most.

Taking on the responsibility of homeschooling the kids has been more challenging than expected, keeping our full time jobs with the unexpected and chaotic nomadic life has been a test. Finding good wifi, the impossibility of a having a routine or finding moments of intimacy with Hazel have been some of the hardest things for us.

But in a project focus on understanding the future of education, the hardest aspect by far is how difficult it is to predict the future.

FUTURE

For us humans at least it is. We pretty much suck at it.

Look at the last 10 years alone. Experts predicting election results, the emergence of the sharing economy and the impact of Facebook, the iPhone or Netflix.

And we think that it is because we walk into the future backwards, with our sight on the past. Which forces us to see a future just like today but slightly different.

I think a great example are flying cars! we imagined flying highways with traffic lights.

When we keep our eyes on the past, we can’t imagine a completely new future. And that’s the challenge we face when we talk about the future of education, or the future of work!

HYPOTHESIS BASED ON SETTING IKER

Our son Iker, now 6, will be 9 in 2020, 14 in 2025, and 24 in 2035 , ready to go into the workforce. Which I hope will prove to be wrong too.

Yes, we think that the world of 2035 is unpredictable, and that the skills Iker will need to be successful are impossible to imagine with any reliable degree of certainty.

If we want to talk about a certain future we should then talk about behaviors. Because humans have been really consistent with our behaviors for the last 4,000 years.

We need love and appreciation. We crave respect and power, but we are also capable of showing incredible compassion and empathy. We learn these concepts from the media, our friends, at schools and churches, but mostly from the environment closest to us; our parents.

Remember at the beginning we said we had a hypothesis about the work in the future? Well, it is our believe that the future of work will be impacted, not by new technology or a new type of organization, but rather, by a much stronger force, the behavior kids see in their parents, and the relationship those parents have with their work.

OUR RELATIONSHIP WITH WORK

I grew up watching my father work 70 hours per week for 45 years. And he worked for only two companies in his entire life.

By the time I started my first professional job at 24 years of age, my values and expectations had already been defined: Loyalty, and hard work from my father. And care and sacrifice from my mother.

Through our research we have found that much like Iñaki everyone’s biggest influence is their parents. Funny thing is we are the least equipped to deal with such powerful responsibility. Their relationship with work will be determined by the way they see we relate to work. That is the strongest model they have.

To our 11 year old, whom you will meet in the next panel, a great part of her relationship with work was determined by our crazy workaholic lives during the first 6 years of her life. While she saw creativity (we both were creative directors in advertising) she also saw her parents working many nights and weekends, pitching campaigns and complaining constantly about clients.

OUR RENEWED PURPOSE

After having lost our path and even worse our purpose, we both shifted careers to education, where, with its imperfections, at least we have a clear purpose of helping people find their unlimited potential by inspiring them to fall in love with learning again. Hopefully now our kids are developing a new relationship with work. One about purpose, commitment and appreciation.

EXERCISE

There is a piece of paper on your chair. Please take 3 minutes to write the answer to this question:

What is the one thing in my relationship with work I need to get rid of?

Keep the piece of paper

NOT SKILLS BUT RELATIONSHIPS

We talked this morning about skills and organizations. But we think that we should also talk about relationships; not only with people but with ideas and institutions, such as work.

We, parents, guardians or anybody who has a young person in their life, construct the building blocks of those relationships for our kids. What is to love. To be happy, to be a citizen, to make a living, and to be a professional.

The idea of work will be disrupted or reinforced by the behaviors our kids, see at home every day and night. And that will define the future.

WE HAVE A DREAM

We have a dream, a big dream, we dream to help improve the future of society by empowering parents and children to develop a good relationship with themselves, their community, and ultimately with their jobs. A relationship that asks questions instead of giving answers, one that continuously learns and is never done, one that questions assumptions. One that can make any company in the world the best place to work!

To achieve that dream, we need your help

We need you to reflect on what model we are building for our kids and take the first step in changing the future by doing a little experiment we have created.

Exercise:

Explore the one damaging thing you have in relationship to work you learned from watching your parents work. It can be working in the home or at a job.

Write only one thing per paper. For example, wait I can’t give you an example, my mother is sitting right here, so Iñaki it is all you to give a few examples ;)

I grew up watching my father putting work before family. So also put work before family for many years.

You will have 5 minutes to write it, just one, and then turn your paper into an airplane. Once you are done, put it up.

We, the Learning Gypsies, were recently part of a really cool event called The Creative Summit, in Skelleftea, Sweden. Yes, we didn’t know where it was on a map either, but we will never forget it now.

The event, brilliantly organized by Peter Mandalh (@PeterMandalh ) and his team, was focused on the theme “the Future of Work” and we had the privilege of sharing the stage with some of the leading thinkers about this fundamental topic: @congbo , @mikearauz, @Joeli_Brearley, @LydNicholas , @alisoncoward ,@disruptandlearn @jeremycdalton and @alexanderneuman , who did an incredible job intervening our three kids during a panel that helped redefined what it means to be successful.

It was really strange to have just 3 hours between sundown and sunrise, (something to experience in a lifetime) but the 2 days we spent in lapland was one of the best parts of this trip.

The kids during their panel about the future of work.

We learned a lot about the future from all the sessions we saw during the day: about Robots and A.I, new Organizational Models, the Skills of the Future, a fairer future with no discrimination against pregnant women, the wonders and possibilities of VR and AR, and about how improving collaboration might give us a chance at a better future at work.

Our approach to the question of the future was framed from our experience during our research about the future of education.

There is no video of the talk, and you might find some bits on twitter, but considering all the people who have requested the transcript, we decided to post it on medium.

(We would like to hear your reactions and get some feedback, so please let us know by writing a comment when you are done)

I’m Iñaki and I’m Hazel. We have a hypothesis about the future of work we are dying to share with you, but before we do that, we would like to tell you a little story.

Almost a year ago we left our life, our friends and the hype of Brooklyn, New York to research the future of Education around the world.

Our 3 kids, my mom and the two of us have been traveling from country to country for over 11 months looking for the answer to one question: how should kids learn in a world where everything will change?

CHANGE

A world where they might not need to learn to drive, where a lot of the current work will be automated… a world where cryptocracy might be the new black, food will be harmless and immortality might be a thing we need to pre-order.

STORY

And as we all know, with changes come surprises.

What we thought was going to be easy, was more difficult. And some of the challenges we anticipated, turned out to be easier.

We thought it was going to be harder for the kids to move around, city to city, from one continent to another. After visiting 42 cities in 11 months they keep on surprising us with their incredible flexibility and adaptability.

We thought it was going to be easier to take the kids to world class Museums, but they wouldn’t have it. After two museums in Sao Paulo they told us: if you want me to walk all day looking at old things I can’t touch, at least tell me what we are doing ahead of time.

To tell you the truth it’s been us the adults that have struggled the most.

Taking on the responsibility of homeschooling the kids has been more challenging than expected, keeping our full time jobs with the unexpected and chaotic nomadic life has been a test. Finding good wifi, the impossibility of a having a routine or finding moments of intimacy with Hazel have been some of the hardest things for us.

But in a project focus on understanding the future of education, the hardest aspect by far is how difficult it is to predict the future.

FUTURE

For us humans at least it is. We pretty much suck at it.

Look at the last 10 years alone. Experts predicting election results, the emergence of the sharing economy and the impact of Facebook, the iPhone or Netflix.

And we think that it is because we walk into the future backwards, with our sight on the past. Which forces us to see a future just like today but slightly different.

I think a great example are flying cars! we imagined flying highways with traffic lights.

When we keep our eyes on the past, we can’t imagine a completely new future. And that’s the challenge we face when we talk about the future of education, or the future of work!

HYPOTHESIS BASED ON SETTING IKER

Our son Iker, now 6, will be 9 in 2020, 14 in 2025, and 24 in 2035 , ready to go into the workforce. Which I hope will prove to be wrong too.

Yes, we think that the world of 2035 is unpredictable, and that the skills Iker will need to be successful are impossible to imagine with any reliable degree of certainty.

If we want to talk about a certain future we should then talk about behaviors. Because humans have been really consistent with our behaviors for the last 4,000 years.

We need love and appreciation. We crave respect and power, but we are also capable of showing incredible compassion and empathy. We learn these concepts from the media, our friends, at schools and churches, but mostly from the environment closest to us; our parents.

Remember at the beginning we said we had a hypothesis about the work in the future? Well, it is our believe that the future of work will be impacted, not by new technology or a new type of organization, but rather, by a much stronger force, the behavior kids see in their parents, and the relationship those parents have with their work.

OUR RELATIONSHIP WITH WORK

I grew up watching my father work 70 hours per week for 45 years. And he worked for only two companies in his entire life.

By the time I started my first professional job at 24 years of age, my values and expectations had already been defined: Loyalty, and hard work from my father. And care and sacrifice from my mother.

Through our research we have found that much like Iñaki everyone’s biggest influence is their parents. Funny thing is we are the least equipped to deal with such powerful responsibility. Their relationship with work will be determined by the way they see we relate to work. That is the strongest model they have.

To our 11 year old, whom you will meet in the next panel, a great part of her relationship with work was determined by our crazy workaholic lives during the first 6 years of her life. While she saw creativity (we both were creative directors in advertising) she also saw her parents working many nights and weekends, pitching campaigns and complaining constantly about clients.

OUR RENEWED PURPOSE

After having lost our path and even worse our purpose, we both shifted careers to education, where, with its imperfections, at least we have a clear purpose of helping people find their unlimited potential by inspiring them to fall in love with learning again. Hopefully now our kids are developing a new relationship with work. One about purpose, commitment and appreciation.

EXERCISE

There is a piece of paper on your chair. Please take 3 minutes to write the answer to this question:

What is the one thing in my relationship with work I need to get rid of?

Keep the piece of paper

NOT SKILLS BUT RELATIONSHIPS

We talked this morning about skills and organizations. But we think that we should also talk about relationships; not only with people but with ideas and institutions, such as work.

We, parents, guardians or anybody who has a young person in their life, construct the building blocks of those relationships for our kids. What is to love. To be happy, to be a citizen, to make a living, and to be a professional.

The idea of work will be disrupted or reinforced by the behaviors our kids, see at home every day and night. And that will define the future.

WE HAVE A DREAM

We have a dream, a big dream, we dream to help improve the future of society by empowering parents and children to develop a good relationship with themselves, their community, and ultimately with their jobs. A relationship that asks questions instead of giving answers, one that continuously learns and is never done, one that questions assumptions. One that can make any company in the world the best place to work!

To achieve that dream, we need your help

We need you to reflect on what model we are building for our kids and take the first step in changing the future by doing a little experiment we have created.

Exercise:

Explore the one damaging thing you have in relationship to work you learned from watching your parents work. It can be working in the home or at a job.

Write only one thing per paper. For example, wait I can’t give you an example, my mother is sitting right here, so Iñaki it is all you to give a few examples ;)

I grew up watching my father putting work before family. So also put work before family for many years.

You will have 5 minutes to write it, just one, and then turn your paper into an airplane. Once you are done, put it up.

Content was really clear 426 Content hit the target 356 Thanks for the learning boost! 361

How to Effectively Harness Behavioral Economics to Drive Employee Performance and Engagement

How to Effectively Harness Behavioral Economics to Drive Employee Performance and Engagement

 

The Incentive Research Foundation’s (IRF) Using Behavioral Economics Insights in Incentives, Rewards, and Recognition presents new insights—and challenges long held assumptions—on what makes employees work their hardest.

Offering practical takeaways to apply immediately in incentives, rewards, and recognition (IRR) programs, the IRF’s report highlights proven behavioral economics approaches that make sense of—and capitalize upon—the powerful role of emotions in employee performance.

Emerging in recent years as a discipline in its own right, behavioral economics has long been overshadowed by the more readily accepted traditional economics which suggests, among other things, that:

            People tend to act rationally and in their own best interests when making decisions

            Money is the most effective motivator of employees

However, because behavioral economics recognizes that 70% of human decision-making is emotional—as opposed to rational—it proves to be a more useful tool than traditional economics in helping employers understand what actually motivates employees, why some incentives are more effective than others, and how they can strategically apply these principles to their own businesses.

Studies indicate that typically only about one-third of employees care about their work. But companies that incorporate proven techniques from behavioral economics into employee motivation programs and other aspects of their business models have a competitive edge and enjoy higher levels of productivity, engagement, and retention among employees than those relying solely on traditional monetary incentives. In most cases, an understanding of the person being incentivized and an appropriate experiential or merchandise reward will result in a far more memorable and impactful reward than cash.

How do IRR professionals decide which rewards to use and how exactly to use them? It’s hardly a surprise that factors like an employee’s age, income, and family status all play into how strong an impact a particular reward has on that particular employee. For a truly effective incentive campaign, IRR professionals should also give careful consideration to these subtle, though perhaps seemingly inconsequential variables:

            Ease of selection:  Is the incentive system user-friendly for the employees being rewarded? Do employees need to make multiple decisions or fill out multiple forms? Are there too many rewards to choose from? Are there enough?

            Reward type: e.g., experience, merchandise, or monetary

            Motivation type: e.g., internal vs. external; cooperative vs. competitive

              How can the reward be made most meaningful for and therefore most effective at motivating this particular employee? Who does the recognizing? Does the recognition seem to come from an HR representative, an executive level manager, direct supervisor, or the rest of the team?             How frequently should rewards be given? What time of year is best to recognize employees? Does it depend on the type of reward? Should the employee know about the reward in advance or should it be a surprise?

            Desired impact: What are the long-term goals of the IRR program? How will these be tracked? How can employers and IRR professionals work together to achieve these goals?

The IRR community might be astounded by some of the IRF’s findings, many of which are downright counterintuitive. However, the study also sheds light on how to best use these findings and proposes numerous ways to successfully apply these insights in the constantly evolving workplace.

Top Recommendations

Here are the top recommendations, and the rationale behind them, from Using Behavioral Economics Insights in Incentives, Rewards, and Recognition:

Ease of Selection

            Incentive programs should focus on using nudges (subtle incentive tools/practices) to make the reward system user-friendly and to maximize the program’s emotional impact. Emotionally compelling rewards hit the mind harder, are remembered longer, produce quantifiably better results from employees, and influence the internal brand the most.

Reward Type

            Employers need to move beyond programs that rely solely on monetary rewards. For large rewards in particular, experience-type programs involving travel tend to generate warm memories and appeal to more than two-thirds of an IRF survey’s respondents over the cash equivalents.

            IRR programs should offer material items and formal recognition more frequently while using intense experiential rewards more sparingly. Experiential rewards (e.g., a tropical getaway or box seats at a premiere sporting event) and material rewards such as plaques each have their own unique value as reward types and should be used in strategic combination to complement each other. One type tends to deliver more intense happiness, while the other serves as a more permanent reminder of appreciation.

Motivation Type

            Reward a top performing team as opposed to using a system in which members of a team all compete against each other for a single reward. In today’s workplace, cooperative incentives are more effective and valuable than competitive incentives. Emotional pressures cause people to do things they don’t really want to do; but it doesn’t cause them to do those things well.

            Don’t underestimate the value of rewards that reinforce internal motivation. Intrinsic rewards increase the recipient’s self-esteem by establishing or affirming a sense of purpose, fueling a desire to live up to expectations of peers and social norms, or helping the recipient master new skills. Intrinsic rewards create a long-lasting desire to perform well. For instance, simply celebrating reward-earners publicly by listing their names has measurable, favorable effects on productivity.

 

Personalization

            Employers need to depart from a generic, one-size-fits-all model and incorporate creativity and personalization (based upon what matters to the individual and his or her peer group) into rewards. For instance, a “working vacation”—toiling, for a fee, at a family farm, bakery, vineyard, brewery, or in another romanticized trade—is an increasingly popular example of a reward that incorporates both intrinsic and extrinsic elements. These “vacations” which include mentoring by experts and impart a new specialized skill upon participants are often a far more appealing choice to individuals who might get restless and bored on a beach vacation.

            Who does the recognizing and how personalized or public that recognition is can have an impact on the employee’s emotional response and ultimately the employee’s productivity. One employee may value and appreciate public recognition while another might respond more favorably to private acknowledgement from an esteemed colleague.

Timing

            Surprise the employee with the reward after the goal has been achieved to avoid the entitlement effect and make it more meaningful. A reward that is explicitly promised in advance to an employee if he or she achieves a particular goal loses its impact much more quickly than a reward received unexpectedly by the same employee in recognition of reaching said goal.

            Use hyperbolic discounting to determine the optimal distribution of bonuses. Hyperbolic discounting refers to humans’ tendency to prefer smaller payoffs now over larger payoffs later. In other words, individuals tend to disregard the future when it requires sacrifice in the present. IRR professionals can make the most of this nearly universal phenomenon, by offering initiatives with titles such as “fast start" which accelerate payouts of incentives in the first few months of the program, making the incentives more tangible and generating more early excitement about the incentive opportunity.

Desired Impact

            Implementing emotionally meaningful incentives in IRR programs has benefits that extend beyond just improving employee productivity. The more valued a company’s employees feel, the better the internal brand impression. Internal brand impression will be talked-up on social media and thereby attract the most talented employees. Eventually, high-performing employees turn into brand ambassadors who extoll the company’s virtues to non-employees—including current and potential customers, vendors, and media.

            Ideally, every incentive and reward program will align to purpose and meaning in some way. If employees believe in the company and its purpose, freely invest in the company, trust their leaders, and develop caring relationships with the people they work with, then the employer becomes an asset in the employees’ ledgers that they will instinctively protect. In this situation the employee feels like an owner as opposed to a renter and will act accordingly.

            Rewards programs that prove you truly care about your employees are the most effective ones. This last insight from the paper ironically draws upon a principle of traditional economics—nothing ventured, nothing gained. Many of these recommended practices for designing a rewards system based on behavioral economics require employers to actually care about their people—something that can’t be faked. Pulling off emotionally meaningful rewards, in other words, may require a cultural change and a mind-set change on the part of the board, executives, managers, and superiors.

 

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Data and Analytics 101: Tips for Success in Corporate Training

Analytics, predictive analytics, diagnostics, data, big data and data mining are all terms used frequently in corporate training. But what do they mean, and what do training professionals need to know? Here are some definitions and tips for success.

Data, Analytics and their Uses

In training, analytics is the process of measuring an individual, system or organization’s performance. Training diagnostics is the process of examining and evaluating training and organizational performance through assessments, analysis and data collection. Big data refers to large, complex data sets that are difficult to analyze using traditional methods but that can reveal important patterns and relationships that inform decision-making.

Data mining and predictive analytics “are a collection of mathematical and computing techniques that can reveal new insights in data,” according to an email from Jeff Deal and Gerhard Pilcher, authors of “Mining Your Own Business: A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics.”

Data mining organizes data into patterns and relationships, and predictive analytics uses the data to make predictions about the future. Thanks to technology, artificial intelligence (AI) is increasingly used in this process through machine learning, which automates the process of analyzing data and making predictions. The people working with the computer, then, ensure the right questions are asked and, according to Peter Clark, co-founder of Qlearsite, use their experience to interpret what the AI tells them: “The combination of a human’s ability to ask good, relevant questions and an intelligent machine capable of searching within big data for a statistical answer is extremely powerful.”

Deal and Pilcher say that analytics can recommend new training and measure its effectiveness, suggest changes to existing training to improve outcomes, and measure the relationships “between training and employee retention” and “between training and employee satisfaction.” Data science, Clark summarizes, “will prove the ‘return on investment’ of learning … in short, [ensuring] the learning and development function delivers more value to the organization.”

James Densmore, director of data science at Degreed, elaborates, writing in an email that “Data Science is key to making the learning experience more personalized and more social.” Using “search and recommendation algorithms,” employees can learn the skills they need using the modality or modalities they prefer. Data can also help connect learners to their peers to learn from and collaborate with each other.

To reap the benefits of data and analytics in training, here are some tips.

1. Use relevant data.

“Just because it’s interesting doesn’t mean it’s valuable,” Densmore says of the data available to training professionals. Understand your business needs, and then define actionable metrics that will enable you to develop training to meet those needs. “Usually,” say Deal and Pilcher, “an effective baseline measure naturally emerges that becomes an effective tool for measuring ROI.”

Qlearsite uses natural language processing to convert written text into “analyzable scores on themes and sentiment.” Up to 80 percent of a business’ “people data” consists of communications, survey responses, performance reviews, assessments and other written text, according to Clark. It’s important to capture that information in a usable way.

2. Leverage technology wisely.

Algorithms “learn” from the data that you provide them with, and “algorithms are only as good as the data you train them with,” Densmore says. When using machine learning or other technology-enabled analytic techniques, evaluate your data and “tailor it to specific domains and use cases.”

3. Curate content thoughtfully.

There’s a large amount of content on the internet that learners can use effectively to improve their performance. Training professionals can help ensure that they access the right content at the right time using content curation. Densmore cautions that L&D organizations should classify content into interrelated topics rather than using a hierarchy, which doesn’t take the interconnectedness of topics into account.

Ask learners what they want to learn, determine what skills they need to learn based on their role, “look at the content they’ve been consuming” and then use all that data in your machine learning system to recommend relevant content.

4. Don’t oversimplify.

Clark says that “simple correlation of two metrics can create false signals.” For example, participants in one training program may have higher scores than participants in another, but does that mean the first program is better? It might be; on the other hand, the people taking that program may be more skilled than participants in the other program. Statistical factoring can alleviate this problem, and automation can help L&D professionals without a mathematics background complete that factoring more easily.

5. Communicate results.

Make sure the conclusions drawn from data are communicated to L&D managers. They need to know “what content is making the biggest difference, gaps in learning vs. industry trends and emerging technologies,” according to Densmore. That way, they can plan programs and resources strategically.

Data and analytics are powerful tools in corporate training, but only if they’re used strategically. Use these tips, and make your data work for you and your employees.

 

 

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The Doughnut Dilemma: What The Office Pastry Teaches About Behavioral Economics

If you want to understand human nature at work, start with a doughnut.

Place it on your desk. Then read the following warning.

Eating doughnuts or any other foods high in fat and sugar increases your risk of heart disease, obesity, diabetes, and other serious health issues.

Should you eat it?

Take your time. Think about all the bad things that could happen to your health if you made a habit of eating doughnuts. You do want to live to 90, right? You really shouldn’t eat it, and you know you shouldn’t.

Now see how long you can leave the doughnut without eating it.

If you feel your will failing, perhaps insults will help. Here’s what one one blogger wrote some years ago about the pastry.

I do not like doughnuts. Never have, never will, and with good reason. Among the myriad offensive foodstuffs enjoyed in this nation of atherosclerotic manatees stuffed prematurely and unnecessarily into grossly over-expanded stretch-pants, whirring around strip malls in motorized scooters, the doughnut has always been, and will always remain, particularly loathsome.

The doughnut is a delicacy of the dim — a favoured indulgence of those with a pedestrian palate and absolutely no understanding of how to run a cost-benefit analysis.

So run the cost-benefit analysis. Then look again at the doughnut, the yummy doughnut sitting right there, helpless.

Chances are, you failed fairly quickly. The warning did not dissuade you. The insult only insulted you. If your fate is to be a dim atherosclerotic manatee, at least you will be a dim atherosclerotic manatee happy from just having eaten that doughnut. The emotional part of your brain wanted the doughnut more than the logical part of your brain could persuade you not to eat it. So you ate it.

Welcome to behavioural economics.

To a classically trained economist, all the doughnut consumption makes little sense. For many decades, the prevailing theory of economics held that people were largely rational, that if they had enough information to make an informed decision about what was in their best interest, they would, in fact, make that kind of decision. Rational Man, he was called, or Homo Economicus. Behavioural economist Richard Thaler calls them “Econs” for short, “mythical creatures that populate economics textbooks.” What makes them mythical? “They solve any problem as well as an economist would.”

In this respect, he says, they are a lot like the Star Trek character Mr. Spock.

“I prefer the concrete, the graspable, the provable,” says Mr. Spock in one episode.

“You’d make a splendid computer, Mr. Spock,” responds Captain Kirk.

“That is very kind of you, Captain,” says Spock.

“We’ve evolved that the agents of the economy, as assumed by economists, have been getting smarter and smarter for the last 60 years,” Thaler said in a 2010 interview. “But human being are just as dumb as we always were, just as human.”

Real humans, he argues, are less like Mr. Spock than they are like Homer Simpson.

A behavioural economist knows that in any real-life environment, people will eat the doughnuts. Why? Forget about today’s office worker and think instead about his deepest ancestors. For them, the food supply was unreliable. Starvation was a constant risk, and sometimes the only meal available might be less like the giant doughnut taken on by Adam Richman in the TV show Man v. Food and more like the bugs eaten by Bear Grylls on Man vs. Wild. They might go weeks between a large, fatty kill, or finding ripe, sweet fruit. When they had these foods, survival might depend not just on eating, but on overeating calorie-rich foods.

So in many ways, we eat doughnuts today because somewhere deep in our brains we’re trying to store up calories for the coming famine, a famine that never comes because, unlike our ancestors, we have grocery stores, and fast food, and every week someone brings doughnuts rather than carrots and celery to the office. Try as leaders might to explain, warn, or incentivize toward what makes sense, people act as people have acted for tens of thousands of years.

“One of the unstated assumptions of economics is that people have perfect self-control because they choose just what they should choose. So, an ‘Econ’ never has a hangover, never needs to go on a diet because he eats just the right amount,” said Thaler. “It’s not that people are choosing to be fat. There’s a conflict there. One part of them wants to be thinner; another part of them reaches for the bag of potato chips. If we’re going to have a good model of that conflict, we have to face it head-on.”

The doughnut dilemma is one of hundreds of mismatches between the rational way people “should” react and way they actually do react in the workplace. Leaders who design choices in wellness programs, compensation plans, company mergers, performance ratings or dozens of other systems assuming too much rationality are destined to be disappointed. Such programs often fail as human nature kicks in and unintended consequences spring to life. For example:

• From a rational standpoint, employees should not need much recognition. The bi-weekly paycheck should be reinforcement enough. In practice, employees are strongly motivated by recognition, and recognition has proven to be a pivotal aspect of productivity-boosting engagement.

• Strictly rational employees would collaborate whenever the benefits outweigh the costs. In the real world, people have a strong friend-or-foe response, jumping in with people they trust while shunning or even extracting revenge on the people they dislike, even if both kinds of decisions are costly.

• In a logical world, everyone’s pay could be public knowledge. In reality, most people consider their pay a private matter, and, if the books were opened, the emotions of everyone making comparisons among themselves could bring a company to a virtual standstill and cause mass resignations.

But while human nature creates many managerial complications, it also brings many incredible upsides. A strictly rational person would not be motivated to design a wildly creative advertising campaign unless he was fairly certain it would get him more money or a shot at a promotion. A rational employee would not grind away week after week formulating a new medicine chiefly for the fulfilment of making the breakthrough. A rational employee would not form an inordinate attachment to a company because it’s a cool place to work, and could be lured away for a decent pay raise. In fact, real people work not just for pay, but for the emotional rewards, which leads to great customer service, inspiring design, incredible innovations and thousands of other accomplishments enriched by human nature rather than pure rationality.

The lesson for leaders and front-line managers is to build their employee value propositions around, not against, human nature — to create a company that appeals as much to employees’ emotions as it does to their rationality, to inspire and recognize and mentor and challenge and celebrate and pay attention to all the reasons why people will find an inspiring place to work as irresistible as they find a doughnut.

Rodd Wagner's – Forbes contributor -  latest book is Widgets: The 12 New Rules for Managing Your Employees As If They're Real People. His website is workhappier.com.

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Translating the Neuroscience of Behavioral Economics into Employee Engagement

It typically takes ten years for science breakthroughs to influence real world applications.  The Incentive Research Foundation’s paper Using Behavioral Economics Insights in Incentives, Rewards, and Recognition: The Neuroscience aims to expedite this process. Offering practical C-suite takeaways, the IRF’s report describes some of the unifying behavioral economic principles connecting the powerful role of emotions in employee performance. 

As productive employees are more readily recognized as playing a vital role in maintaining a profitable business in today’s competitive marketplace, effective businesses now require a systematic, strategic use of motivation and recognition in practice. Incentive, Rewards, and Recognition (IRR) professionals help all business types design and implement motivation programs to improve productivity, performance, morale, and retention with their employees and channel partners.

Behavioral Economics
Behavioral economics proves to be a more useful tool than traditional economics in helping employers understand what actually motivates employees, because it recognizes the majority of human decision-making is emotional as opposed to rational. It integrates social, cognitive, and emotional factors to more fully explain human decision-making biases and challenges long-held traditional economics assumptions such as:

People tend to act rationally and in their own best interests when making decisions and Money is the most effective motivator of all employees

Behavioral economics helps explain why some incentives are more effective than others and how they can strategically apply these principles to their own businesses. 

Neuroeconomics
Neuroeconomics provides an additional powerful layer of proof by exploring the biologic underpinning of decision-making. In many ways behavioral economics and neuroeconomics are like a tag team trying to wrestle neoclassical economics out of the ring for its failure to accurately capture how real human beings think and make decisions. 

Technological advances allowing researchers to probe the brain in unprecedented detail are powering an explosion in neuroeconomics research. For instance, brain-imaging technologies now allow us to see which brain areas are active during economic decision-making and which are not.

The most powerful neuroeconomics finding is that all forms of reward – monetary or otherwise – are processed in the brain’s master reward center, the striatum, and are experienced as rewarding feelings. For example, when research subjects are offered various forms of reward – ranging from their favorite food to a compliment to a monetary gift – neurons in this structure fire. This means rewarding employees intrinsically by treating them better or rewarding them extrinsically with money are treated equally in the brain, with both causing rewarding feelings emanating from the striatum and the dopamine reward system. This important finding is at the base of helping organizations craft more effective, rewarding environments. 

Using Emotional Reward Units to Craft a Rewarding Environment
Consider two employees, A and B. Both make the same monetary salary and benefits—let’s say $50,000. We will assume that this amount of pay creates positive feelings in the striatum equivalent to 10 emotional reward units, or ERUs. Employee A unfortunately works for a toxic manager who makes his life a nightmare. Employee A receives constant criticism, is threatened and disrespected, and never gets a kind word. The pain experienced by employee A creates a reward deduction of let’s say 5 ERUs. The emotional take home “pay” for employee A is therefore only 5 ERUs (10 ERUs–5 ERUs). 

Employee B is luckier. She works for an emotionally intelligent manager who understands human nature, takes a personal mentoring approach, believes in coaching employees and recognizing their achievements, and tries to encourage their development and success. Employee B loves coming to work and therefore gets a 5 ERU bonus on top of her monetary pay, which results in an emotional take home “pay” of 15 ERUs. 

Who do you think will want to work harder to meet the organization’s goals: the employee earning 5 ERUs or the one making 15 ERUs? The answer is obvious – the more rewarded employee will be more engaged and more productive. This is why considering engagement as a system, versus an individual intervention, is crucial to organizations. 

Applying Brain Principles for Better Business
As Nobel-prize winning economist Daniel Kahneman discussed in his book Thinking, Fast and Slow, our brains form thoughts in two ways:

System 1: A fast, automatic, involuntary, subconscious system (sometimes called the old brain) which harnesses all of our life experiences to date and where decisions are initially made (and feelings emitted) within milliseconds of encountering a situation. For example, driving to work on “autopilot” without giving it much thought or getting a “gut feeling” about a situation.  System 2: The “conscious” system where we think about, deliberate, imagine, and analyze the world around us.  

It is most important to know that System 2 is more energy-intensive on the brain, so the brain therefore offloads as much work as possible to System 1. This is why after much deliberation we will select the easy, automatic solution because it ‘feels right.’ In sum, finding ways to work in tandem with System 1 can help us create more effective engagement solutions. Five examples are below:

The Associative Machine and Halo Effect: The associative machine takes all of the information we know about something (such as “bird”) and stores it under a filing for fast recall. If we come across something in an unfamiliar situation, the associative machine pulls up whatever facts it has in memory (wings, nest, egg) to instantly provide an explanation of the situation at hand and provide a feeling of confidence. For ease of processing, the brain will also combine and connect what it deems as relevant connected experiences – called the halo effect. This is how fuzzy, pink bunnies or dancing fruit can cause things as mundane as batteries and underwear to emit positive emotions within us. This holds true for the workplace as well. 

Implications: The more highly positive, emotional experiences, throughout the lifecycle of employment an organization offers from hiring to retirement, the more positive emotion one associates  with the company.

Emotional Stamps: Given the amount of information we must process each day, the fast part of our brain does much of our thinking. All of our memories are marked with an emotional stamp that controls their storage and retrieval. The stronger the emotional stamp, the easier the memory recall. 

Implications: Simply put, if we want people to remember things, we must tap emotions in some manner.

Frequency Bias: Our brains employ a frequency bias, which means ideas, thoughts, images, and awards that we see more frequently “feel” more familiar and therefore “feel” more positive. Hence, more frequently mentioned awards or destinations will have an automatic, emotional edge over the less-known alternatives. 

Implications: The more reward and recognition happens within an organization, the more often it will continue to happen and “feel” like a normal part of business. 

Temporal Bias: We remember short, peak emotional experiences more than average ones. This finding means at most, that short, highly impactful reward experiences may be more memorable and at least, that all reward experiences should conclude with the most emotional part of the event (or the big reveal) as the final portion. If it happens at the beginning of the day, quarter, year, or event, that time frame will be less likely to be perpetually stamped with the positive emotion. 

Implications: Meetings and incentive travel programs should always end on a high, emotional note. 

Harnessing Human Drives for Better Business

In Driven: How Human Nature Shapes Our Choices, Harvard researchers Paul Lawrence and Nitin Nohria propose four social drives that complement our biologic drives and regulate virtually everything happening in the workplace. If we learn how to work in tandem with these productive drives, our companies will enjoy maximum productivity and our employees will experience maximum engagement in their work.

The social drives create pleasant and painful feelings that push and pull on us during the course of a typical workday, subtly encouraging us to inquire, invent, achieve, and cooperate as a corporate team. Based in neuroscience, psychology, anthropology, and biology, Nohria and Lawrence found they serve as motivational “hot buttons.” When pressed individually, motivation rises marginally, but when pressed all together motivation grows exponentially within an organization – causing even larger impacts to engagement, retention, and commitment. Reward and recognition provide organizations a powerful tool because, in a single intervention, they help activate all of these four drives: acquire, bond, innovate, and defend.

Drive to Acquire: Employees are driven to acquire tangible goods (money, property, cars) as well as intangible skills (expertise, new abilities) and status. Dopamine is released into the brain anytime we anticipate achieving a goal or we achieve it. Likewise, companies provide compensation to employees and want them to be competent, confident experts. Ideas on activating include:

Make goals clear with defined implications for achieving Train managers and each employee to recognize and reward positive, productive, aligned behaviors Set high, yet achievable, targets that are broken in to sub-goals, then reward their realization Make recognition public and provide status to recipients Provide rewards (tangible or intangible) as close as possible to the desired behavior Make recognition spontaneous, personal, and heartfelt (not on auto-pilot or auto-schedule) Provide down time after long periods of extensive effort to achieve a goal Provide tangible rewards to supplement intangible recognition from managers and peers Provide group goals and celebrations

Drive to Bond: Employees are driven to have authentic caring relationships not just with family and friends but with their workmates and supervisors (their tribe) and to experience the warm, friendly feelings that come with them. Humans are also the only creatures which bond to abstract concepts such as ‘team’ or ‘nation.’ Bonding is supported by the release of the neuropeptide oxytocin in the brain. Likewise, companies want employees to collaborate and cooperate as a team in order to solve difficult problems. Companies that provide rewards for group achievements are working harmoniously with the drive to bond. Ideas on activating include:

Have employees create online profiles that are socially available for all to see Create randomized dyads of employees and encourage mutual-mentoring where they work together to solve problems  Ensure each instance of reward and recognition has a face-to-face element

Drive to Innovate: Employees are naturally driven to learn about the world around them and create new thoughts, systems, process, relationships, and goods based on these discoveries. Studies show how opioid receptors in the brain help create a “Eureka Pleasure,” meaning it feels good to satiate curiosity, think up a new an idea, solve a difficult problem, or comprehend a difficult concept. Likewise, companies also want their employees to learn and innovate. Ideas on activating include: 

Give all employees at least a small amount of time to innovate within their sphere of knowledge Ensure each instance of reward or recognition helps the employee learn the exact behaviors that are valued and important to the organization Encourage managers to have an “open door” to hear new ideas Continue to encourage employees when an idea does not pan out Organize dedicated “skunkworks” teams to promote radical innovation

Drive to Defend: Employees are driven to feel safe and secure and to defend the objects, people, and ideas they hold dear. The brain’s prefrontal cortex is an active participant in activating our defensive mechanisms, causing us to feel irritated, frustrated, angry or scared when we believe a closely held relationship or our status is at risk. Likewise, organizations want to minimize the activation of this drive and the inherent stress and negativity that arises when employees are in active-defense mode. Ideas for mitigating this drive: 

Maintain openness and transparency in all communications regarding determination  of all organizational incentive and rewards Gather employee input on incentive, reward, and recognition efforts to ensure they are perceived as fair Remind employees often of their importance to the organization’s mission

If when collectively activated, these drives have a compounding effect, then well-executed organizational incentive, rewards, and recognition programs hold a crucial opportunity for organizations, since they present, in a single instance, the opportunity to hit on all four drives at onceIn a single instance of giving an employee a reward or recognition, the organization allows an employee to acquire status (and potentially good or services), to bond with their team or the person giving the recognition, to more deeply comprehend what is important to the organization, and to defend the very deeply held belief that he or she is good at what they do and has chosen the right organization for employment.

From studies on oxytocin to dopamine to the pre-frontal cortex, there is no shortage of emerging neuroeconomics research on what makes humans, and employees, tick.  By working in tandem with the brain, however – and considering concepts such as the associative machine, the halo effect, emotional reward units, and the four drives –businesses will craft organizations that are not only highly productive and competitive, but better for employees overall.