Data Informed Editor, Scott Etkin, interviews Pasha Roberts, Chief Scientist at Talent Analytics, about how predictive analytics have a major impact on job maps & succession planning.
Data Informed: What kinds of data make up a predictive job map?
Pasha Roberts: Each node in the map is a role, for example, “Underwriter I” or “Inside Sales Representative.” Then, we map the traffic between each role: hires, promotions, demotions, transfers, terminations, and actual performance in the role. This gives us a set of history and probabilities for how people really move and perform through the organization, which is not always how HR has planned it. This emergent order usually brings a lot of insight, but it is nothing new. People have been doing this with Markov chains for a long time.