Growing From Knowledge-Based to Performance-Driven Learning

Over the last 20 years, I’ve worked closely with hundreds of Learning and Development (L&D) organizations.  A consistent observation I’ve made is that the majority of learning deployed to organizations is purely knowledge-based.  In fact, many L&D professionals I’ve worked with report that 70% to 85% of the learning they provide their organizations is designed to only build knowledge.

Most L&D professionals realize that learning focused on only knowledge-based outcomes will do little to measurably impact performance.  So why does most learning fall into this category?  I’ve found it’s not lack of expertise to create performance-based learning; it’s most often due to environmental constraints that make it rarely possible to do so:

  • TIME: The business served by L&D demands (and deserves!) a quick turn-around on their requests for the development of learning initiatives. This time constraint is a big one.
  • RESOURCES: The resources needed by the L&D function to develop and deploy learning are often spread too thin. I rarely meet with an organization that tells me they have sufficient staff to meet the optimal turn-around time for learning initiatives with training that is based on true performance-based outcomes.
  • BUDGET: Closely tied to the resource constraint is the budget. Whether learning initiatives are funded centrally by L&D or directly by the line of business, there are too many learning requirements and too few available dollars.

Too little time, too few resources and too little budget.  Something’s got to give.  And what almost always gives is the quality of the learning.  The compromise becomes “well let’s at least get the knowledge in their heads and hope that impacts performance.”  And we’ve all learned that hope is not a strategy!

Let’s review a Performance-Based Learning process based on neuroscience that has consistently made a significant impact on employee performance.  To make it easy to remember, we call it

The “4As” Process.

Here is a brief summary of the important role played by each step:

 As discussed above, most learning begins and ends by processing knowledge into short-term memory.  Hermann Ebbinghaus’ “Forgetting Curve” and over a century of further research confirms that this doesn’t work.  A few weeks after the learning, over 80% of the knowledge is forgotten.  The learning must take an important step further by enabling learners to truly anchor new knowledge through highly-interactive learning activities, beginning the neuro-encoding process required to transfer the knowledge from short-term to long-term memory.

ASSIMILATE:  While the “facts” included in the knowledge (such as the features of your new product) are important, the learner must build neuro-relationships between those facts in order to cognitively solve problems or answer customer questions about those new product features.  This requires different learning activities and question types (such as grouping challenges rather than multiple choice questions) which are designed specifically for this purpose.

APPLY:  Focusing on the skills, not just the knowledge, is what ultimately transforms job performance.  The learning must provide activities which allow the employee to practice the application of the knowledge in role-specific scenarios of increasing complexity.  This builds the ability to correctly apply the embedded knowledge within job-specific skills and behaviors.

ASSESS:  Whether it is assessing learning effectiveness at its conclusion or assessing learning retention at intervals after the learning, assessing knowledge gain and skill performance provides key measures that are important.  Assessments should go beyond a score, however.  Assessing should identify knowledge and skill gaps where further learning or additional reinforcement is required.

I have reviewed and discussed this process with hundreds of organizations, and implemented it with dozens of them.  Initially, their response is almost always:  “We get it.  That makes sense.  But remember those time, resource and budget constraints we talked about?  Those haven’t gone away, so we don’t have the ability to grow our learning from its current knowledge-based focus to true performance-based learning.”

mLevel, as an organization, has focused exclusively on how to help organizations ramp up the performance impact of their corporate learning in very cost effective ways.  For example, we’ve helped global organizations reduce their turn-around time on learning requests from the business by 75% or more (while simultaneously increasing the performance impact of the learning).  We’ve enabled other organizations to leverage technology that allows subject matter experts (SMEs) to create effective, instructionally-sound performance-based learning to reduce the load on scarce L&D instructional designers and content authors.

If there were a way to cost effectively ramp up the effectiveness of your learning in order to measurably increase the performance impact of your organizational learning, would you investigate it?

If the answer is “Yes”, reach out to me at  Let’s schedule some time to talk.

About Bryan Austin

Bryan Austin is mLevel’s Vice President of Learning Innovation.  Throughout his 25-year career with industry-leading organizations like Skillsoft, NETg, AchieveGlobal and Kaplan, Bryan has dedicated himself to helping organizations develop high performing employees through innovative learning solutions.  A hallmark of Bryan’s approach is his keen ability to think outside of the box and create engaging, skill-based learning experiences that accelerate employee growth and productivity.

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1 thought on “Growing From Knowledge-Based to Performance-Driven Learning”

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    The assessment strategy is key, create authentic and competency-based assessments (note, I did not say “tests”) and align them to the operational, business defined rubrics and you will see the performance meter move.

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