ABSTRACT
This chapter describes the tools, team members, data infrastructure, and planning needed to develop an analytics environment within a retailer's loss prevention team. The analytics infrastructure often refers to the staff, services, applications, utilities, platforms, software, and systems that are used for housing the data, accessing the data, preparing data for modeling and analytics, estimating models, validating models, and taking actions. A successful analytical infrastructure is predicated on getting the right analytics people. Since big data analytics is a burgeoning field, even the top data scientists are still honing their analytical skills. The use of analytics and predictive modeling is a critical component in the future of loss prevention. The ability to assess patterns in data, measure loss prevention programs, and make decisions in real time will become fundamental in solving complex issues related to customers, sales, and loss. Additionally, social media data is beginning to be used by loss prevention teams to help investigate cases.
