Data on Purpose

Data on Purpose Photo

If ever there was a way to kick off two days’ worth of presentations around a topic that some people would rather stand in line at the DMV while watching paint dry than discuss, it would be with Nancy Lublin. Lublin is the CEO of and the CEO/Founder of Crisis Text Line, and earlier this month—Tuesday, June 2nd and Wednesday, June 3rd—Lublin kicked off the Stanford Social Innovation Review’s “Data on Purpose” conference. The conference convened CEOs, directors, program managers, educators, and nonprofit professionals at the Arrillaga Alumni Center on the Stanford campus to discuss the ins and outs of creating social change with data. Speakers and panelists (data nerds) from far and wide gathered with the goal of exploring the ways in which data can be, and is currently, being used by foundations and nonprofits for social good.

From 9AM to 9:55AM on the first morning of the conference, Nancy Lublin led the audience through the data informed methods of to the development and success of Crisis Text Line. Her presentation style combined with inherent charisma and a genuine understanding of the importance of her work and the way data fuels it, sent the room into a state of statistically inclined jubilation. (Lublin probably could have recruited two-thirds of us as summer interns in that moment if she’d asked nicely.) The story basically goes like this:, adhering to a data-focused, user-centric model, responded to an unexpected need for a service that connects young people in need of emotional support with resources and someone they could reach out to on their terms—i.e. via text message—by launching Crisis Text Line. The result of this evolution has been monumental. In four months, Crisis Text Line was fielding approximately 24,000 messages per day from all 290 area codes in the United States. Today, smart data combined with complete trust in that data, allows Crisis Text Line to organize messages and understand its users in a way that tangibly helps people. As far as data on purpose goes… this is it. As Lublin put it, “data makes us better at what we do,” and what they do is dramatically impacting the lives of young people all over the country.
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Lublin’s opening keynote set the tone for the rest of the conference, and provided one profound answer to the question, what is the power of good data? From there, panels and break-out sessions ranged from topics that covered, “How to Create a Data Driven Organization,” to, “Data Mining for Social Impact,” to, “Using Data Visualization to Change the Conversation.” The overarching tone of the conference essentially boiled down to three questions:
  • What can data teach us?
  • How do people communicate around data?
  • What is the power of good data?

There is, of course, no single answer or cardinal approach to these questions, but the ideas and discussions they fostered resulted in some incredible stories and valuable nuggets of wisdom. Every keynote, panel, and break-out session provided a unique perspective on the best ways to work with and use data for social good.

For example, in his keynote address titled, “How to Create a Data Driven Organization,” Jim Fruchterman, founder and CEO of Benetech, made the point that if we focus on data for program improvement, “we will enable people to ask more important and better questions.” In other words, it’s not simply about “measuring outcomes,” if we empower people at the front lines of communities (like program managers) to be more involved with data, things will begin to shift for the better. Other panelists discussed topics such as data security, how to use data as a forecaster of critical social issues, and why it’s important to understand what specific data language your organization speaks.
In no time, a collective excitement could be detected among attendees. Everybody seemed ready to discuss and share what they were learning. That’s one clear indicator of a successful conference. Another might be that 22 days later the content and impressions left by the panelists still resonate. As Nancy Lublin said, “what we do matters,” and it’s important that we not only measure data, but that we also store it, analyze it, and apply it directly to the meaningful work that we do.