Contraceptive access is vital to safe motherhood, healthy families, and prosperous communities. Greater access to contraceptives enables couples and individuals to determine whether, when, and how often to have children. In low- and middle-income countries (LMIC) around the world, health systems are often unable to accurately predict the quantity of contraceptives necessary for each health service delivery site, in part due to insufficient data, limited staff capacity, and inadequate systems.

When too few supplies are ordered, service delivery sites may run out, limiting access to contraceptives and family planning. When too much product is ordered, unused contraceptives are wasted if they are left to expire.

Accurate forecasting of contraceptive consumption can save lives, money, and time by ensuring health service delivery sites have what they need when they need it and by reducing waste in the supply chain.


With Intelligent Forecasting: A Competition to Model Future Contraceptive Use, USAID seeks to identify and test more accurate methods of predicting future contraceptive use at health service delivery sites. Our goal is to ensure appropriate stocking of contraceptives and family planning supplies and to better understand the benefits of intelligent forecasting models for improving contraceptive availability and supply chain efficiency.

Launched in July 2020, the competition has two phases. First, a Forecasting Prize was awarded to the highest-performing intelligent forecasting models that predicted the consumption of contraceptives over three months. Second, a Field Implementation Grant will be awarded to a team of innovators to customize and test a high-performing intelligent forecasting model in Côte d’Ivoire.


After testing the accuracy of nearly 80 models from 40 competitors during the prize round of the Intelligent Forecasting Competition, USAID is excited to announce the selection of two winners! These innovators will receive $25,000 in prizes for creating models that more accurately predict future use of contraceptives at health clinics in Côte d’Ivoire.

The winners were announced on November 12, 2020 at the Center for Global Development’s virtual event, Improving Global Health Forecasting: Data Science, Advanced Algorithms & Partnerships. You can view the results for all models submitted by competitors for the Intelligent Forecasting Prize here.

Inventec Corporation - First Place Intelligent Forecasting Prize Winner

Competitors from Inventec Corporation’s AI Center in Taiwan not only developed the highest-performing model for this competition, but had three of the four best-performing models.

Inventec Corporation participated in the Intelligent Forecasting Competition because: “We want to improve human well-being by applying AI logistics forecasting."

Inventec AI Center advances Inventec Corporation’s smart manufacturing capabilities, as well as pioneers future AI technologies and products in areas such as smart health and smart computing hardware. Inventec AI has solved smart manufacturing problems such as the logistic management process for forecasting parts needed for manufacturing the products, built systems for automatically qualifying products for mass production, and developed novel methodologies for efficiently creating AI models for visual inspection. In pioneering future AI technologies and products, Inventec’s AI Center is investigating smart health for the wellbeing of mankind, smart computing including AI chips, architectures, and infrastructures for the ever-more demanding needs of AI computing.

Rasyid Ridha - Second Place Intelligent Forecasting Prize Winner

Rasyid Ridha, an analyst from Indonesia, not only developed one of the highest-performing models for this competition, but also had all three models perform in the top ten.

Rasyid participated in the Intelligent Forecasting Competition because: “I love playing with data. Forecasting is a very hard problem and I want to deal with it to further improve my skills. In addition, I am very passionate about creating something related to data that can be impactful for others.”

Rasyid is an analytics professional with over four years of experience and strong expertise in R programming. He is skilled in data visualization, statistics, customer analytics, and machine learning, and he is passionate about building scalable analytical products and solutions that create long-lasting impacts. In 2018, Rasyid won first place in the Withdrawal Forecasting category at the Finhacks Data Challenge: ATM Cash Optimization, which is the biggest national data science competition about cash withdrawal forecasting in Indonesia. Rasyid currently works as a business intelligence analyst at a technology company in Indonesia.


In July 2021, team Macro-Eyes was awarded the Intelligent Forecasting Field Implementation Grant to customize, pilot, and iteratively improve their model, which will be implemented at health service delivery sites in Côte d’Ivoire. Congratulations!

Macro-Eyes will partner with Michael Konan and the University of Novi Sad/Faculty of Technical Sciences Hybrid Forecasting Approach (HFA) group, led by Dr. Dejan Mircetic, to maximize the success of their forecasting model and ensure it is locally-informed and incorporates diverse perspectives. Macro-Eyes, Michael Konan, and the HFA group separately competed for the Intelligent Forecasting Prize and learned about each other through the co-creation event hosted by USAID. These organizations decided to join forces to survey Côte d’Ivoire’s health systems landscape and create an accurate and appropriate modeling solution for integration into the local pharmaceutical logistics system.

Learn more about the members of this team.


* This competition is an addendum of the Global Health BAA. To refer to the original BAA, click here.

A woman consults with a pharmacist
Photo Credit: USAID Kenya
Family Planning