Predictive Learning Analytics™: New Rules, New Tools for Increasing Training Transfer

In the previous article, I discussed the concept of "scrap learning" and what it costs organizations in wasted money and time — two precious resources . I also briefly mentioned Predictive Learning Analytics™ (PLA) as a viable solution for reducing scrap learning and increasing training transfer. This article will explain PLA in more detail — what it is, how it works, and the benefits of using PLA.

To start, imagine the possibilities if you could know at the conclusion of a learning program which learners are most and least likely to apply what they learned back on the job.

...Or, imagine if you had data indicating which managers are likely to do a good and poor job of supporting the learning they sent their employees to attend.

...Or, imagine if you had data identifying the root causes of why learners aren't applying what they learned in a training program back on the job.

...Or, imagine if you had an objective way to compare the overall quality of one learning program with another so that you could revise or eliminate those programs that aren't delivering value.

Now all this and more is possible using PLA!

 In short, PLA is a systematic, comprehensive, easily implemented 3 phase 9-step process designed to help L&D professionals maximize the value and potential of corporate learning initiatives by applying data based decision-making to learning (see figure below). In subsequent posts, I will provide a case study and go into more detail about each of the steps.

Benefits of Using PLA

The benefits associated with implementing the PLA methodology are significant and many, and include benefits for both you and your organization:

• Less money and time wasted on learning that is delivered but not applied back on the job - scrap learning
• Increased personal credibility in eyes of business executive stakeholders
• More effective and efficient use of follow-up and reinforcement activities by targeting those participants at risk and least likely to apply what they learned in a program back on the job
• Objective way to identify managers and departments that do a poor job of supporting learning so that their approach can be improved
• Objective way to compare the overall quality of one learning program with another using a single number
• Enhanced reputation among L&D colleagues

In summary, PLA is a game-changer, enabling L&D professionals to proactively and strategically increase training transfer while at the same time increasing their personal credibility with the business executive stakeholders they support. 

Interested in bringing PLA to your organization? Phillips Associates is offering a two-day workshop, Boost Training Transfer Using Predictive Learning Analytics, on March 8-9 in Chicago. For more information contact Ken Phillips at 847-231-6068 or ken@phillipsassociates.com