This Pharmaceutical company is engaged in manufacturing and distributing over-the-counter pharmaceutical products. The demand profile for their products is characterized by high seasonality as well as extreme volatility caused by wholesalers.

Pharmaceutical supply chain demand forecasting case study — reducing forecast error from 50% to 25% MAPE with exception management and VMI

We helped them identify the major drivers of demand volatility. We designed and developed a process to segment customer demand volatility and major demand clusters for better supply chain execution

  • Develop a robust demand forecasting process with an emphasis on exception management.
  • Leverage customer information through VMI and CPFR depending on the size of the customer.
  • This process helped the company achieve monthly revenue forecast errors within +/-2% and annual revenue estimate errors for the division within +/-5%.
  • The division’s item level absolute accuracy improved from 50% MAPE to 25% MAPE within a year after going live with this process.
  • The realized savings included both reductions in inventory as well as improvement in customer service as measured by the First-time Fill Rate.