Jake Porway at SSIR: “These days, it’s hard to get away from the hype around “big data.” We read articles about how Silicon Valley is using data to drive everything from website traffic to autonomous cars. We hear speakers at social sector conferences talk about how nonprofits can maximize their impact by leveraging new sources of digital information like social media data, open data, and satellite imagery.
Braving this world can be challenging, we know. Creating a data-driven organization can require big changes in culture and process. Some nonprofits, like Crisis Text Line and Watsi, started off boldly by building their own data science teams. But for the many other organizations wondering how to best use data to advance their mission, we’ve found that one ingredient works better than all the software and tech that you can throw at a problem: collaboration.
As a nonprofit dedicated to applying data science for social good, DataKind has run more than 200 projects in collaboration with other nonprofits worldwide by connecting them to teams of volunteer data scientists. What do the most successful ones have in common? Strong collaborations on three levels: with data science experts, within the organization itself, and across the nonprofit sector as a whole.
1. Collaborate with data science experts to define your project. As we often say, finding problems can be harder than finding solutions. ….
2. Collaborate across your organization to “build with, not for.” Our projects follow the principles of human-centered design and the philosophy pioneered in the civic tech world of “design with, not for.” ….
3. Collaborate across your sector to move the needle. Many organizations think about building data science solutions for unique challenges they face, such as predicting the best location for their next field office. However, most of us are fighting common causes shared by many other groups….
By focusing on building strong collaborations on these three levels—with data experts, across your organization, and across your sector—you’ll go from merely talking about big data to making big impact….(More).