Integrating Safety Stock Policies into Roche’s S&OP Process

Abstract

Globalization, demand uncertainty, and shorter life cycles have increased the risks in pharmaceutical supply chains. To mitigate these risks, firms can carry safety stock. Classic theory on stochastic safety stock strategies assume that demand forecast errors are normally distributed with no bias or, in other words, have an expected value equal to zero. This assumption does not hold when considering over-optimistic, or positively biased, demand forecast, which is a common issue, as indicated by the prevalence of Sales and Operations Planning (S&OP) efforts. We began exploration of the biased forecast impact on safety stock for our sponsor company by understanding the managerial situation. To better frame the problem, we developed a conceptual model of the overall S&OP process based on responses to interviews with the company teams that influence the safety stock target definition. The conceptual model informed a formal model that we used to test the impact of a new safety stock formula that addresses forecast bias. Our results show that even though safety stock can be adjusted with this new approach, there are still many opportunities for improvement along this process. We conclude that in order to make the best informed decision about safety stock levels, Roche’s team should better integrate safety stock decisions into their S&OP process. Also, effort should be allocated to understanding which data is being used, what it means, and whether it is appropriately informing inventory decisions made explicitly by managers or implicitly in information systems. Finally, further analysis shows there is much greater potential to reduce inventory beyond that dictated by safety stock policy. Roche should continue working towards understanding the root causes behind their excess of inventory to achieve long-term substantial impact.