How the process works
At DrivenData, we bring cutting-edge practices in data science and crowdsourcing to some of the world's biggest social challenges and the organizations taking them on. We host online challenges, usually lasting 2-3 months, where a global community of data scientists competes to come up with the best statistical model for difficult predictive problems that make a difference.
Framing a problem
Our first step is to frame a good predictive question, one that can be solved by the data at hand and has measurable, real-world impact. We work with organizations to understand their needs and identify productive partnerships.
Hosting the data science competition
The next phase is to host an online, open-innovation competition where freelance developers and data scientists submit statistical models. Using our competition platform and evaluation engine, the models are ranked based on how well they predict data withheld from the competitors.
Integrating the best statistical model into the organization's workflow
Finally, we want to close the loop. We work with the organization to leverage the top model—as insight, a fresh statistical approach, or a tool for analyzing new data—enabling them to more effectively and sustainably carry out their mission.
Let's get specific
Consider a nonprofit microlender. Using data on loans and outcomes, DrivenData would run a competition to predict default. A good model predicts which loans involve the most risk. A better model might determine the loan amounts that minimize the probability of default. Using the winning solution, the lender can decrease negative outcomes for recipients and improve its long-term impact. You can find more examples on our information for Partners page.
Moving beyond measurement
When mission-driven organizations think about data, the conversation often begins and ends with measuring impact. This is an important question that requires data, but there are so many more ways that organizations can use data to drive impact.
Approaches in machine learning, predictive analytics, and artificial intelligence are transforming the way organizations solve problems across industries. To learn more check out our brief introduction to machine learning for social impact.