Overview
In low- and middle-income countries (LMIC) around the world, health systems struggle to accurately predict the quantities of contraceptives that are needed at each public sector service delivery site for consumption by clients seeking family planning services. This leads to inefficient ordering and distribution of contraceptives to service delivery sites, and can ultimately result in stockouts, stock shortages, or overstock. This under and over stocking leads to reduced access to contraceptives for users, inefficient allocation of resources in the supply chain, and potential loss of product due to expiration. There are many reasons why predictions about consumption of contraceptives at facilities may be flawed; these include: limited availability or low quality data, limited staff capacity, limited staff time, and weak business processes. Across most LMIC public sector health systems, one key limitation is that historically facilities have ordered based on calculations that primarily or exclusively rely on logistics data from previous time periods to predict future consumption. However, evolving 2 health systems and digital infrastructure have created an opportunity to utilize advanced methods to more accurately predict future contraceptive needs, even for short-term forecasts for service delivery sites. The Intelligent Forecasting Competition seeks to encourage innovation and drive progress through intelligent forecasting methods to predict contraceptive consumption at the service delivery level of the public sector health system in Côte d’Ivoire .