Often, when employees hear terms like “Data Analytics,” “AI,” or “Machine Learning,” they either think of something from a sci-fi movie or a bunch of nerds magically spinning millions of data points into millions of dollars. What is often missing is the foundational mindset around experimentation and iteration that goes into making solid predictions. HR is usually part of the problem, assuming that analytics is a rest-of-the-business problem or something left for the HRIS. As learning practitioners, we have the opportunity to model the analytic mindset, but we might not know where to begin.

This session will provide an overview of how Discover Financial Services is currently changing its company culture to include data literacy enterprise-wide and how L&D has started putting these practices into place, starting from scratch. These include quantifying brainstorming sessions, using thematic analysis in SME interviews, rating vendor catalogs, and using Behavior Anchored Rating Scales (BARS) in the RFP process.

The importance of using evidence-based techniques to measure impact using objective data to counteract biases.