A Tool for Helping Companies to Safely Reduce WIP

Editor’s Note: Every year, 40 or so students in the MIT Center for Transportation & Logistics' (MIT CTL) Master of Supply Chain Management (SCM) program complete one-year thesis research projects. The students are early-career business professionals from multiple countries with 2 to 10 years of experience in the industry. The research projects are sponsored by and carried out in collaboration with multinational corporations. Joint teams of company people, MIT SCM students, and MIT CTL faculty work on real-world problems chosen by the sponsoring companies. In this series, we summarize a selection of the latest SCM research. The researchers for the project described below, Karim Kamareddine and Yihong Yao, analyzed tradeoffs between working capital and production capacity for their SCM thesis Analyzing Tradeoffs between Working Capital and Production Capacity for Multi-stage Manufacturing Processes. The work was carried out for a major pharmaceutical company, and the project was supervised by MIT CTL's Dr. Jarrod Goentzel.

As part of its efforts to cut costs, a leading pharmaceutical company set itself an annual goal to reduce working-in-progress (WIP) inventory.

Achieving such a goal required the company to find the right balance between minimizing inventory to deliver cost savings, and maintaining enough inventory to support a high level of customer service.

Finding this balance is a common challenge, but the pharmaceutical company also had to account for the fact that given the nature of its products, lowering service levels could put peoples' lives at risk.

One way to reduce WIP and minimize these risks is to invest in new production facilities, a strategy that would incur significant cost. To help the company find the best solution, MIT CTL researchers evaluated different scenarios to find the optimum strategy.

A manufacturing problem
The company's high level of WIP inventory stems from the nature of the manufacturing process.
This process is comprised of multiple modular stages. Each proceeding stage cannot begin before the prior one is complete. And there a significant amount of time is spent changing over from one stage to the next, because each time the relevant production facility must be disinfected to prepare it for the next stage in production.

The company manufactures product in large batch sizes to avoid frequent changeovers. However, the practice generates high levels of WIP inventory, and increases working capital without leaving any room for production flexibility.

A strategic tool
Clearly, the WIP challenge revolves around a trade-off between batch size and changeover frequency. But tweaking either parameter has ramifications for working capital and production capacity. Moreover, if the company wants to reduce WIP it needs more changeovers, but such a policy requires investments in additional production capacity.

A series of scenarios with multiple production stages and different production frequencies were tested. The base metric chosen to compare the different investments was net-present-value (NPV). However, 21 KPI's and input parameters were developed to narrow the selection process even further.

The relationship between the variables is not linear, and the best results were found to depend on the objective that the company wants to pursue.

The scenario analysis helped the company to evaluate these options. The more production capacity it invests in, the more flexibility it creates in production processes in terms of finished goods lead-time and additional capacity.

A key takeaway is that the scenario analysis is a strategic tool that can help enterprises make large investment decisions, and reduce WIP with minimal risk. Companies find quantitative analysis useful, but when faced with such decisions, supplemental tools such as the scenario analysis help guide enterprises through the decision-making process.

For further information on the SCM thesis authored by Karim Kamareddine and Yihong Yao contact Dr. Bruce Arntzen, Executive Director, MIT Supply Chain Management Program, at [email protected].

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