How the process works

At DrivenData, we want to 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 nonprofits 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 nonprofits page.