The buzz around talent and talent management, performance management, and human capital management (HCM) has grown from a mere whisper three years ago to continual murmurs in 2012 to a building roar in 2013 and 2014. Is this important to eLearning professionals? How does it affect our work?
You have probably noticed that executives these days are paying attention to Big Data and the predictive analytics that can be applied to it. Quants—specialists who perform the quantitative analysis involved—provide strategic guidance to companies, based on big data. This is having a major effect on the thinking and the decision criteria of top business leaders. It is essential for learning and development (L&D) professionals to understand this, to understand how data is driving HCM, and to position L&D within the business context. If you want a seat at that famous strategic table, you’d better be able to speak the language.
In this article, I will provide an overview of these developments. I will also suggest seven key practices that will make the difference between success and simply failing to thrive. I believe L&D professionals and their managers should begin to implement these now. Over the next several months, Learning Solutions Magazine will be publishing additional articles that dive deeper into HCM and its implications for eLearning.
Data analytics, automation, and integration
While financial measures traditionally expressed as return on investment (ROI) or in balanced scorecards are still important, it is more and more the consideration of predictive data around the impact of an investment on performance and outcomes that drives executive decisions (including those involving investments in L&D). It isn’t necessary for L&D professionals to be able to do the mathematics of quantitative analysis, but it is important to understand the thinking and to be able to collect and use performance data to support L&D initiatives. It is also important to fine-tune our thinking about the way we identify, design, and guide those initiatives.
These changes are driven by disruptive technologies and by the problems involved in managing a generationally diverse workforce. The disruptive technologies include not only predictive analytics but also the increasing automation and integration of key business functions and processes, including human resources (HR).
Automation of HR began with software for payroll and compensation, but now is beginning to affect other processes with strategic implications, such as talent acquisition (recruiting) and talent management (including workforce planning, onboarding, and succession planning). HR functions, especially the ones dealing with talent, are also becoming more integrated, although this is far from universal among companies and is more true for large companies than small ones. The trend is clear, though.
In the field of training, we have added the Experience API specification (xAPI) to our technologies, to complement the earlier SCORM standard. SCORM provided the means to document completion of formal in-house training events and courses, and to integrate this information into an organization’s learning management system (LMS). The xAPI specification provides a way to document all of an individual’s learning experiences, whether formal or informal, in-house or external, and to compile it into a learning record store (LRS). At this point, unfortunately, in most organizations there is as yet little or no integration of these systems with other HR functions and processes.
Why does this matter? It matters because these HR and L&D systems accumulate huge amounts of data. Properly integrated and analyzed, this data can provide strategic insights and business intelligence valuable to senior leadership—the executives who make the decisions about where to invest resources, including capital.
It can be very difficult to understand where we are headed, why traditional training is passing away, and how our ways of thinking about learning are (and must be) changing. But understand we must.
The learning (and performance) ecosystem
A first step is to consider how our knowledge about what works has evolved. Research, particularly in neuroscience, is giving us valuable new information about how learning happens. One effect of this is that we better understand that learning is not linked to isolated events in organizations. Our frame of reference for L&D must include more than formal instruction, or on-the-job training or coaching. Our criteria for success must go beyond “completions,” and beyond criterion test results (traditional Kirkpatrick Level 2).
Now, as the result of advanced research in neuroscience, we have a better understanding of the ways in which learning takes place in the context of life and work. Learning takes place outside of classrooms. Learning takes place with peers as well as with supervisors and coaches and trainers. Performance can be shaped on the job through performance support.
The learning ecosystem is the appropriate frame of reference, and actual business performance is the payoff that decision makers care about! (What we have called Kirkpatrick Level 4 and the Phillips’ Level 5 are no longer sufficient for executives.)
As my colleague David Kelly has said in a recent blog post, “In today’s digital world, a web of learning resources surrounds every individual. It’s an environment wherein each resource connects to others, creating an overall structure in which all learning takes place. The learning ecosystem is the combination of technologies and support resources available to help individuals learn within an environment.” And, I would add, that same combination of technologies and support resources helps individuals perform within an environment. It is business-relevant performance with which we must primarily be concerned.
Organizational learning and performance strategy
Now all of this is only a preamble to the bigger subject of human capital management, which as I said at the beginning of this article we will address in Learning Solutions Magazine in coming months. In fact, probably the majority of organizations where readers of this magazine work are not currently fully engaged in the transition to HCM. In the majority of cases, organizations are not collecting and analyzing data for strategic purposes or for business intelligence. The majority of companies do not yet have full integration of the systems.
But we don’t have to wait to begin positioning L&D.
The biggest change required of professionals in the learning business is to begin thinking strategically instead of reactively and tactically. To think and act strategically requires that we connect what we do with the organizational results that matter to our executives and leadership. It also requires that we adjust what we do and how we do it so that we take advantage of the technologies now available to us. Guided by what we learn from research, and enabled by ubiquitous technologies, here are seven things we can do right now to build a learning ecosystem that will align with developments in HCM.
Social learning first
Develop your strategy for use of social and collaborative designs for learning, and make these your first option where appropriate (and remember they may be appropriate more often than you expect). We know that social and collaborative learning is highly effective; it is how people learn most of what they know about their work, and best of all, it doesn’t cost much, if anything, to incorporate it into your learning ecosystem.
Develop your strategy for performance support at the moment of need (delivered on mobile devices, embedded in systems and software, provided contextually in the workplace, and complementary to the formal and informal learning experiences in your learning ecosystem). This is also another relatively low-cost element of the learning and performance ecosystem.
Use appropriate off-the-shelf courses (thoughtfully)
Fine-tune your selection and assignment of off-the-shelf (OTS) courses. Look for industry- and association-provided content as well as vendor-developed courseware, and match the person to the course. Consider OTS before in-house development, not as a default for the masses, but where proven high-quality courseware is available that specifically matches individual talent-development needs.
Develop formal instruction in-house only when it makes sense
Consider your business case (not “use case”) for in-house-developed courses and content. It is vitally important to be able to show why in-house development and formal instruction (including use of OTS) is more appropriate and provides more value than the other alternatives named above. This is the most expensive element of your learning and performance ecosystem.
Apply research before tradition
Provide practice, booster tests or activities (see Art Kohn’s column next week) and (where appropriate) spaced repetition as part of your learning design, for all modalities—whether informal or formal. Pay close attention to research and use the results that apply to your situation. There is a lot of urban myth and ancient lore embedded in many eLearning designs, and it needs to go away if it doesn’t stand up to scrutiny.
Track learning experiences against results
Connect learning experiences with performance results. This will require integrating your learning management system, learning record stores, and performance management systems. Your executives will want to know how you expect to measure progress. Don’t make your pitch without an evaluation plan!
Teach managers how to develop talent
Develop the skills of your managers for guiding talent, and making appropriate use of learning resources and the performance management system. Training, as we used to say, is never enough. Neither is informal learning or performance support. You must have the competent, proactive support of the managers and supervisors.
Counts of butts-in-seats and course completions are meaningless to decision makers. Individuals who are merely informed or who can pass a test or who “know the right answer” do not give an organization what it needs. What an organization needs is individuals and teams that can perform.
Design your learning ecosystem to develop what your organization needs: individuals who can perform. Supporting your organizational learning strategy and connecting to talent management efforts will provide that res ult.
Kelly, David. (November 18, 2013). What is a Learning Ecosystem? Twist. 18 November 2013.
McKinney, Rob. “eLearning Helps Equip Managers for Demanding New Expectations.” Learning Solutions Magazine. To be published 2 April 2014.
Messner, Wolfgang. Making the Compelling Business Case: Decision-Making Techniques for Successful Business Growth. Houndmills: Palgrave Macmillan, 2013.
Pease, Gene, Boyce Byerly, and Jac Fitz-enz. Human Capital Analytics: How to Harness the Potential of Your Organization’s Greatest Asset. Hoboken: John Wiley & Sons, 2013.
I also recommend Silk Road’s “The State of Talent Management 2014.” While this is a vendor-created document and access requires registration, it is extremely well done and informative. If you would like to see an overview of the report content, you can view a presentation of the report by Ed Vesely on YouTube. You can download the report itself from the Silk Road website.