Case Study: Drug Substance Campaign Optimization

Goal: to understand the impact of changeovers and holding costs on inventory management for drug substance production.

High level summary

• Analysis for a manufacturer producing 2 years supply of material in long campaigns, generating large amounts of excess inventory.
• Project looking at the timing and length of campaigns to optimize production and minimize cost.
• Working in conjunction with Finance and planners, Bio-G evaluated different methods for optimizing inventory quantities.
• The strategy suggested by Bio-G decreased inventory while maintaining same service levels to customers.
• Savings of $5MM a year in direct operational costs, with no investment.

The Brief

The traditional paradigm for operating large scale bulk manufacturing plants is to maximize their throughput, a strategy that involves long campaigns with very few changeovers. Plants have been traditionally rewarded for this strategy since each additional gram of material lowers the per-unit production cost.

Figure 1. Inventory levels over time for two campaign strategies

However, supply chain planners have begun to realize that such a paradigm generates a large amount of excess inventory that must be stored for months or years before it is shipped to patients. Single campaigns can produce up to 1-2 years of inventory that must be stored, using not just premium warehouse space but tying up valuable capital.

In worst cases, a classic 'bullwhip effect' arises where bulk manufacturing is highly unresponsive to actual customer demand, creating either large gluts of supply or supply shortfalls. The key challenge for manufacturers is therefore to trade off campaign lengths with overall plant capacity to minimize not just production cost, but holding costs throughout the supply chain network.

Figure 2. EOQ model: optimal trade-off of holding costs & campaign length

How We Did It

Bioproduction Group's methodology was to establish a strategy based on a variant of the classic 'Economic Production Quantity' (EOQ) model, adapted for the biopharmaceutical manufacturing environment. "EOQ-style modeling was simple, understandable and produced great results", comments Principal Rick Johnston. "Intuitive findings are important when you're trying to drive such a large-scale change."

Working with finance planners, the Bio-G team suggested a strategy for each product that balanced raw materials, insurance and other real costs against the loss of plant capacity resulting from more changeovers. The result was a simulation model that incorporated detailed costing and time aspects, to show cash inflows and outflows over time. Not content with a deterministic solution, the team used simulation modeling to show that the risks to the business were the same as, or lower than, the existing strategy.

Results

Bio-G's recommendations were to dramatically increase the number of campaigns, halving the campaign length for many products. The resulting strategy minimized inventory on-hand, resulting the manufacturer meeting lean targets in terms of raw materials and drug substance. More importantly, the output of the simulations showed that these lower inventory targets could be met without increasing the risk to the business, and in many cases decreased the overall risk of stockout. The value shown was $5MM a year in direct costs saved, with no capital outlay required.