Poor allocation of risks among the constituents of a supply chain results in a misalignment of incentives, leading to over-reactions, unnecessary interventions, second guessing, mistrust, and distorted information – ultimately degrading its ability to match supply and demand. This study assesses the current allocation of operational risks and their impact on the incentives of different players in the global health supply chain, focusing on the case of fixed-dose artemisinin-based combination therapy for malaria as an illustrative example.
Currently, there is a highly non-optimal allocation of risks in this supply chain, where constituents that have the best knowledge about demand uncertainty, or the highest ability to resolve part of this uncertainty, or have the highest potential to benefit from this uncertainty reduction, do not necessarily carry its corresponding risks. This and other improper risk allocations lead to misaligned incentives for accurate forecasting, sharing demand/supply information in this supply chain. Similarly, an asymmetric risk structure for the quality regulators does not provide them the right incentive to quickly approve more drugs by higher resource commitment.
The authors recommend establishing a global health infomediary to overcome the uncertainty due to the opacity of data from the various supply chain nodes. Funding agencies should also adopt a risk-sharing approach based on rolling partially-flexible purchase commitments, which would lead to an economically optimal sharing of risks and would eliminate some of the incentive misalignments, as well as a broader use of framework contracts. Finally, manufacturers should explore the potential for a joint demand driven supply-hub to respond more rapidly to order and reduce the overall reliance on demand forecasts.
This paper informed the deliberations of the Center for Global Development’s Global Health Forecasting Working Group and is cited extensively in their final report, A Risky Business: Saving Money and Improving Global Health through Better Demand Forecasts.