A Rapid Cost Modeling Tool for Evaluating and Improving Public Health Supply Chain Designs

Effective and efficient health supply chains play a vital role in achieving health outcomes by ensuring supplies are available for people to access quality health services. However, supplying health commodities to service delivery points is complex and costly in many low- and middle-income countries. Thus, governments and partner organizations are often interested in understanding how to design their health supply chains more cost efficiently. Several modeling tools exist in the public and private market that can help assess supply chain efficiency and identify supply chain design improvements. These tools are generally capable of providing users with very precise cost estimates, but they often use proprietary software and require detailed data inputs. This can result in a somewhat lengthy and expensive analysis process, which may be prohibitive for many decision makers, especially in the early stages of a supply chain design process. For many use cases, such as advocacy, informing workshop and technical meetings, and narrowing down initial design options, decision makers may often be willing to trade some detail and accuracy in exchange for quicker and lower-cost analysis results. To our knowledge, there are no publicly available tools focused on generating quick, high-level estimates of the cost and efficiency of different supply chain designs. To address this gap, we designed and tested an Excel-based Rapid Supply Chain Modeling (RSCM) Tool. Our assessment indicated that, despite requiring significantly less data, the RSCM Tool can generate cost estimates that are similar to other common analysis and modeling methods. Furthermore, to better understand how the RSCM Tool aligns with real-world processes and decision-making timelines, we used it to inform an ongoing immunization supply chain redesign in Angola. For the use cases described above we believe that the RSCM Tool addresses an important need for quicker and less expensive ways to identify more cost-efficient supply chain designs.