Published on February 9th, 2015 | by Joshua New0
5 Q’s for Erek Dyskant, Co-Founder of BlueLabs
The Center for Data Innovation spoke with Erek Dyskant, co-founder of BlueLabs, a data analytics company based in Washington, DC. Dyskant discussed how innovative uses of data can improve healthcare outcomes and how data science can be used for social good.
Travis Korte: Can you introduce BlueLabs and some of the projects you work on?
Erek Dyskant: BlueLabs is an analytics, data, and technology firm that was co-founded by leaders of the groundbreaking 2012 Obama for America analytics team. We help organizations solve big problems, find creative ways to utilize data, and implement data-driven strategy. Our work ranges from helping small campaigns maximize their resources to helping national service providers improve health outcomes by having relevant interactions with millions of citizens. One of our current projects involves analyzing and visualizing healthcare data from the hospitals in Camden, New Jersey, to help inform the conversation about how people in Camden use health services, how increased access to insurance through Affordable Care Act is changing that, and where there are opportunities for both traditional providers and community organizations to address unmet needs.
Korte: Tell us about the collaboration with Camden hospitals. What are the goals of the project and when will we be able to learn a little about how it’s going?
Dyskant: This is one of our favorite projects because it combines all of our best skills—analysis, tech development, and data visualization. The project presents fascinating challenges in terms of analyzing healthcare usage, creating an infrastructure using near real time data, and then weaving that into a compelling story about the health of the Camden community. There are three major goals for our work with Camden hospitals. First, we’d like to present this complex hospital data in an understandable and compelling way. Second, we’d like to enable experts and policy makers to utilize the data to further the conversation about healthcare policy both in Camden and more broadly. Finally, we’d like to see practitioners and community groups take charge of this kind of data for educational and advocacy purposes.
Korte: What are some of the ways you’ve repurposed techniques used in political campaign analysis and targeting and applied them outside the field of politics?
Dyskant: Our team led the charge on the 2012 Obama campaign to develop unique methods of determining both what can change people’s behavior and who is most likely to. This type of modeling, called persuasion modeling, can be applied to any organization, and we’re just scratching the surface of what it can do. It can help advocacy groups call supporters to action, non-profits raise money, or corporations move consumers toward their product.
Beyond specific techniques, just like political campaigns, all our clients have complicated programs with multiple channels of engagement, and engage with a broad range of consumers who each have different needs. While we push the limits methodologically, we always work to understand how our clients use our data products to improve their programs, and tailor our work to meet those needs.
Korte: One of the things you work on is building data science teams for other organizations. What makes a good data science team?
Dyskant: A good data science team combines creativity, diversity, open-mindedness, and hard work. What I look for in data scientists is a combination of technical execution skills, statistical expertise, and finally an ability to articulate their theory of change. I want to hear a data scientist tell me the mechanism behind how their innovative work product changed the world for the better.
Korte: It seems like data scientists are particularly willing, among other professions and even among other subfields of tech, to give back and participate in social good projects. What do you think is behind that?
Dyskant: Our mission at BlueLabs is to help make the benefits of the data revolution available to those working to do social good. Just like any scientist, we take a hypothesis, test it, test it again, and review the outcomes. And we know we can make a difference. We can see the change in people’s behaviors based on the outreach of a campaign or organization. We know that there’s a “tipping point” out there, and we have the experience with crafting data-driven strategy to make that change.