Predictive and prescriptive

- I'm pretty terrible at chess, although I've been told the secret to success is mostly about anticipating what your opponent is planning to do next. Wouldn't it be great to know how someone would react to a situation ahead of time? That would definitely make me a better chess player. Predictive learner analytics occurs when you make decisions based on the information at hand to impact future events and outcomes specific to individual learners as opposed to predictive experience analytics which makes suggestions about how to improve content experiences. In our example of Souder Manufacturing we're aiming to improve financial and operational metrics of the company by better educating the facility managers. Assuming the first cohort has now completed the program, what can we learn about those individual learners that can be used to improve future manager development? Since we are evaluating the growth of our managers via a competency framework designed to demonstrate their overall efficacy as a manager some of those skills and competencies might include inventory management, team building, and enterprise software skills. As part of this framework we've provided a benchmark for each competency so that we can evaluate their progress. It's important to remember that we don't just evaluate for evaluation sake but to inform future decisions. Let's dig deeper into one of the competency examples and explore how a well timed coaching intervention can accelerate an individuals development. In this scenario we examine an individual managers learner profile and determine that they're below the set benchmarks of both enterprise software skills and inventory management. With that information we can create a hypothesis designed to help the manager move stale inventory via standardized workflows in the software. The coaching intervention will improve both their inventory management and software skills. If our hypothesis is validated we can now predict the results of future interventions of this type when needing to address inventory management and pricing strategy within our store manager training program. To find learning strategies that work and produce repeatable impact the process of developing and testing hypothesis can prove very effective. Besides being used to predict how to better improve learner competencies other examples include, reduce the likelihood of failure for an individual, help an individual complete the curriculum faster, and predict ahead of time which individuals will benefit the most from learning. Think about how you can use data about learners to form and test a hypothesis. Can you predict at what stage someone might drop out of a certification program? Or can you predict when someone might be more likely to struggle and need help? Forming and testing these hypotheses is the foundation of predictive learner analytics. It empowers you to continuously improve how learning benefits those who engage with it.