The Utilization of Customer Point of Use Demand Data

Cardinal Health tasked the Tauber team with improving transparency and collaboration for inventory management with their hospital partners by utilizing hospital point of use consumption data to improve inventory management processes and performance measures.

Using the data, the team developed two solutions. The first solution was a machine-learning predictive model. This model assessed the likelihood that future customer business predictions would actually translate into sales demand based on previous customer usage inputs. In addition, the team proposed to improve forecasting accuracy by using the point-of-use consumption data to generate weekly forecasts. Forecasting accuracy improved by 2% for high-volume products and 7% for low-volume products based on the new data source.

These forecasting improvements could result in an estimated cost savings of $170K at one distribution center over a year period.

View team project summary

Student Team

Daniel Pasternak – EGL (BSE/MSE Industrial and Operations Engineering)

Xinyun Tao – Master of Supply Chain Management


Project Sponsors

Bruce Brinker – Manager, Medical Segment Inventory Planning

Pat Brock – Director, Medical Segment Inventory Management Fulfillment Channel


Faculty Advisors

Peter Lenk – Ross School of Business

Siqian Shen – College of Engineering

Project Photos