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Newsroom & Blog

Jul 8, 2019   |   Blog Post

Rapid Modeling for Improved Reproductive Health Supply Chains

Workers at distribution site in Zambezia.

By Dorothy Thomas

Associate, Supply Chain

Supply chains are critically important to the success of any reproductive health program. Efficiently run supply chains can help eliminate barriers so that no woman leaves a health clinic empty handed. However, supply chains are also expensive to operate. The process of identifying more efficient supply chain designs can be a challenging process requiring significant investments in data collection and modeling. Despite the benefits associated with exploring and implementing more streamlined supply chain designs, programs often lack the time, resources, or data to pursue an intensive supply chain re-design.

To address this challenge, the William Davidson Institute and VillageReach have collaborated to develop a light-touch, Excel-based modeling tool that empowers reproductive health program leaders to quickly estimate their supply chain costs and evaluate different scenarios for improved supply chain efficiency. Application of this tool facilitates strategy development by allowing reproductive health leaders to identify and assess the costs of multiple supply chain design options while minimizing time and data gathering requirements. The flexibility of the tool allows it to be configured for application in diverse contexts. We believe this tool can help enable leaders to drive supply chain innovation and make design decisions even in environments where time, data and resources may be limited.

With support from the Reproductive Health Supplies Coalition, Gavi, the Vaccine Alliance and the Bill and Melinda Gates Foundation, VillageReach and WDI have worked together to develop, test and socialize this rapid and flexible cost modeling instrument. You can find the rapid costing tool here.

You can find a demonstration modeling analysis (using data from a Province in a country in Southern Africa) exploring four different supply chain scenarios as well as the resulting cost implications here.

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