Thesis/Capstone
Publication Date
Authored by
Evan M. Humphrey, Federico E. Laiño
Advisor(s): Inma Borrella
Topic(s) Covered:
  • Forecasting
Abstract

This capstone assesses the feasibility and potential value of implementing Demand Sensing in the supply chain of a major consumer medical device company- Johnson & Johnson Vision Care. Specifically, we explore the potential benefits  of  incorporating  downstream  Supply  Chain  data into forecasting, reducing latency between Sales and Operations Planning (S&OP) cycles, and quantifying demand shaping actions. The motivation for this project was to find new sources of efficiency within a constrained production environment . Our  approach  was  twofold:  first,  to statistically examine the accuracy of the current forecast system and second, to assess the pragmatism of Demand Sensing. The results of our statistical analysis suggest using alternative methods for forecasting slow-moving SKUs. Our research into advanced forecasting  methods provide real world recommendations regarding the benefits and drawbacks of Demand Sensing approaches.  We constructed  three initiatives - one for each Demand Sensing approach that can be used independently, or in any combination, to create Demand  Sensing  forecasting system. The three initiatives are called Latency Reduction (LR), Downstream Data  Integration (DDI)and Measuring the  Impact of Demand  Shaping Actions  (DSA).