Using Predictive Analytics to Optimize Resources

During the panel presentation at NRF, we had several questions about the impact of the current financial and retail situation on loss prevention budgets, staffing, and strategies.  Bill Titus, Vice-President of Loss Prevention for Sears Holding, gave some great examples of how they have used predictive analytics to optimize their resources and prioritize issues.  While this has always been a responsibility for senior leadership, the panelists all agreed the current expense pressures had made this more important than ever and has pushed them to delve even deeper into the data.

Over the last few years, I have had the chance to talk and visit with many companies who place an emphasis on analytics and data.  No one seems to have completely figured out how to predict shrinkage from the metrics (short of cycle-counting which is a good topic for future posts), but they are working hard on it.  Of course, this requires data streams and there are still plenty of organizations that do not have the data necessary to do the analytics and prioritize resources.  If you don’t have the data, you cannot organize it into “information” and if you don’t have “information” you cannot develop it into “knowledge.”  How much emphasis does your loss prevention organization place on analytics?

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