Program: Data Science Master's
Host Company: Express Scripts
Location: St. Louis, Missouri (onsite)
Student: Michael Schulz
The project objective was to develop predictive forecasting models for pharmacy warehousing data. Express Scripts’ primary business function is that of a pharmaceutical benefits manager or PBM. Being a PBM often requires innovation in driving down drug costs for patients and clients. One way to do this is to leverage predictive analytics in spaces where existing processes are extensively automated around fulfillment operations. A seasonal ARIMA model and an Exponential Space Smoothing model were created in order to provide a predictive analytics option to the warehousing space with regards to pharmacy warehousing labor team costs and optimization operations. Individual labor activity data was rolled up and used as a source for the predictive models. These models should permit further analytical exploration of datasets within the pharmacy warehousing space.