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