Evaluate Learning With Predictive Learning Analytics

A positive return on investment for training programs is a top concern for C-level executives and should be for L&D professionals too. Scrap learning-the time and money wasted on most training programs that are delivered but not applied on the job-is 45-85 percent. In this issue of TD at Work, Ken Phillips, CPTD, details how to measure, monitor, and manage scrap learning with Predictive Learning Analytics. PLA is a systematic, credible, and repeatable way to reduce scrap learning and maximize training transfer. Phillips:

Explains the PLA model and provides formulas for calculating scrap learning
Outlines how L&D practitioners can use the model in their organizations
Provides a case study