Do you want learning to be easy for the end-users or for corporate-IT?
(you can only pick one!)
I recognize why large organizations seek to minimize the number of different IT systems in their L&D ecosystem and prefer large, integrated platforms that solves “almost all L&D tasks” in one platform.
SuccessFactors, Cornerstone and other major players, tries to convince customers that they are pretty close to this promise. But they are not. Such platforms are a myth.
I will argue, that for any learning related challenge there are always a range of smaller and specialized players who offer superior solutions.
I will also argue, that the Big players create an dependency to their (limited) data models and that their solutions, in areas as e.g. data analytics, are sometimes more focused on their own interests than on the interests of their customers.
But there is an alternative route. It is possible to build a learning ecosystem consisting of best-of-breed providers in every discipline – often in a combination with an existing Big Player LMS. It is possible to create services and experiences that makes life easy for the end-users, that are cost competitive compared to Big players and that are much more open to the L&D solutions that will be invented next year.
The only downside is: This approach make life a bit more complex for Corporate IT.
Before you architect your Learning Ecosystem consider a couple of principles that can help guide your decisions and priorities. Below are my favorite top 4 principles:
Principle #1: Great User Experience top any other priority
Until we get people to like, use and benefit from the solutions we offer them, all other efforts are worthless.
Principle #2: Focus on results (not learning)
It’s all about creating results: Change of attitudes, change of behaviors and improved results that support the organization’s strategy. Digital tools allow us to measure results – let’s put these tools to work!
Principle #3: Experiment. Learn. Repeat…
We want our users to be adaptive and to “take charge of their own learning”. If learning services are to keep up with empowered users, the distance from an idea to a pilot must be as short as possible. Also, adapting to user feedback should be a never-ending, fast cycle.
Principle #4: Choose ecosystem players (no-one stars forever…)
A Great Learning Ecosystem can be seen as a parallel to a “great sports team” that consistently delivers world class results. The supporting platforms are similar to “players” that must constantly fight for their spot on the team – aware that new players will always stand in line, ready to take their place.
In a world where we strive towards these principles, let’s try to investigate in somewhat more detail what a Learning Ecosystem could look like.
There are many ways to visualize and explain a Learning Ecosystem. The below is my attempt to create a meaningful overview, combining input and ideas from many smart people.
Illustration of an end-user facing Learning Ecosystem (we will talk back-end in a moment)
This illustrates how the end-user is the center of attention and it visualizes some of the resources, tools and -processes that all contribute in creating great end-user experiences.
A key point is that the complexity of the model above is completely hidden to the end-users. What they need is a one-point-access from where they seamlessly access any service.
This is a range of different internal resources, typically residing in several different existing IT systems, behind firewalls, that all play a role in delivering inspiration, resources or learning objects to the end user.
The range of available external resources is growing fast and can become an important source of delivering inspiration, resources or learning objects to the end user. Some are free and some live behind pay-walls – but this should never be a concern of the end-user.
The Experience design tools are super important, as they can empower many contributors in the organization to create and share effective inspiration, resources, learning objects and adaptive learning pathways to the end-users. Also, they can set the rules for end-user sharing resources with one another.
This illustrates how specific services – often delivered from a range of platforms – can also be integrated into (more or less) seamless experiences.
This illustrates a highly important new focus area: Making learning services available directly in the non-HR IT platforms that people use extensively (such as Microsoft Teams – that is growing rapidly). “Learning in the flow of work” is a popular concept these days – so why not integrate learning into the platforms the user visits many times every day, instead of trying to get them into a learning portal?
The second visualization focus on some of the critical and supporting infrastructure in the back end:
Illustration of some of the supporting back-end infrastructure.
Personalization & adaptive support
A driving idea here is to systematically collect user- and team specific data from a range of sources (self-tests, feedback, actual behavior, 3rd party sources, etc.) and utilize this data to create adaptive learning journeys and experiences. Many use this approach within a specific course or program – but few systematically collects and uses such data across different programs. But such ability can be highly important and valuable.
Content metadata and categorization
A huge barrier for utilizing content from many sources into integrated user experiences is the fact that most suppliers/sources use fundamentally different principles for tagging and mapping content objects. To address this challenge you need an infrastructure and some methodologies that makes it easier, and partially automated, to map 3rd party content to an organization-specific skill-, topic- or competency model, and to add organization specific tagging to 3rd party content.
Core HR system integration
Maintenance of users including e.g. organizational association, roles, geography and other background data is typically mastered by a core HR system or similar.
Activity records and analytics
Data capturing has two dimensions:
When tying together the two dimensions we learn what works, and we can let insights gained direct future investments and better understand what behavior to stimulate, and what stimuli works for different challenges and target groups.
As “Learning Record Stores” makes their way into the ecosystems, these services will take over parts of the data recording.
Campaigns and nudging
There is always a significant gap between the good intentions of individual users and their actual learning behavior. But there are many ways to minimize the gap by engaging campaigns and nudging activities that users find helpful and that helps them in achieving both their activity goals as well as their long-term objectives.
The learning architecture you work with today probably looks a bit different from the above. And maybe no-one will ever build exactly this structure. But that’s not the point. The point is that you should make the effort to define all the different services that your ecosystem must combine into one, integrated ecosystem. And this should happen before you chose your line-up of suppliers.
When you do this right, you will be able to combine best-of-breed providers into a solution that provides seamless end-user experiences to a degree that no Big player will ever be able to.
Finally, let me note that the above is just a snapshot of what I see today. There are so many ways of describing and viewing ecosystems, and if you have a better, or just different approach I would love to hear about it!
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