“Cut the Scrap with Predictable Learning Analytics” by Ken Phillips, PhD, CPLP
First cohort – EVER! – to attend a Ken Phillips session on Predictive Learning Analytics!
MANY THANKS to the fine folks at the Hawkeye Chapter, Association for Talent Development (ATD)
What is arguably the number one issue facing the L&D profession today?
The answer: “Scrap Learning.”
Scrap learning is a term coined by Knowledge Advisors to describe the difference between learning that is delivered, but not applied back on the job. It’s also a critical business issue because learning that is delivered but not applied is a waste of organization resources.
So, how big is the problem?
Two benchmark research studies help put this in perspective.
In 2004, Rob Brinkerhoff, professor at Western Michigan University, found that slightly less than 20% of participants never apply what they learn in a training program back on the job and another 65% try what they learned but revert back to their old ways for a whopping 80% scrap learning figure.
More recently, a 2014 Conference Executive Board (CEB) white paper reported that in the average organization, 45% of all learning delivered ends up not being applied.
The message is clear: scrap learning is a huge problem for L&D!
The question then becomes: “What can be done about it?”
The answer: Use Predictive Learning Analytics and Predictive Modeling Methodology created by Ken Phillips, PhD, CPLP to reduce the amount of scrap learning associated with a learning program.