Guest post by Caroline McAndrews, Director of Research & Documentation, Building Movement Project

Figuring out what data to collect, how to collect it, and how to make sense of it in order to build impact was the theme of the 90-second poster presentations from discussion leaders at the Data 360 session. In her opening, Fay Twersky of The William and Flora Hewlett Foundation touched on one of the biggest challenges in the room – not just collecting information, but engaging others in using and analyzing it, and ultimately employing it to make better decisions.

Each speaker had a unique perspective on the use of data ranging from the importance of using comparative data (putting your data in a broader context), to sharing information (both raw data, as well as tools for understanding and visualizing results), to determining its place in creating change. They spoke about the unique role that nonprofits organizations, foundations, volunteers, and data scientists can play in making information more accessible, in funding and providing resources to organizations, and in analyzing and understanding the change we’re making and trying to make.

After 40 minutes in small groups, it was clear that there are many hurdles to overcome, but there is already movement towards using and sharing data widely. Participants shared the major insights they had arrived at, including:

• As important as data is, we still need “knowledge brokers” that can make meaning from the data.
• Data collection should be built in to the front-end of every initiative.
• We can’t underestimate the importance of how we communicate data, particularly visually.
• The power of sharing data across organizations depends heavily on alignment at the outset of collection.
• Just as important as understanding what your data says is understanding what it doesn’t say.  Too often, “confirmation bias” or the desire to see our initiatives as responsible for certain outcomes leads to assumptions about what the data can actually tell us, particularly around causality.
• It is important to align our stories to the data, so that they actually communicate what we find, rather than using data to fill in the story we want to tell.
• If more people would share how they do things and the methodology they use, then we could figure out what is and isn’t working much faster.  One example of this is the Fail-fest at dosomething.org.  Similar resources include their Tuesday morning live data streams and the Knowledge Hopper blog at Bridgespan.

Overall, there was a lot of excitement in the packed room and people seemed eager to figure out how to share and use these resources.  At the end of the day, this is about creating the change we want to see in the world.  As Kevin Bolduc from The Center for Effective Philanthropy said, ambition is our biggest asset, not data; but we need the data to figure out how we’re going to get where we need to go.