Turning Data into Impact: Matt Gillingham on the Future of Analytics, Data Quality, Equity, and More

Today we sat down with Matt Gillingham, vice president of digital innovation and analytics to talk about how digital can help move the needle on some of the toughest challenges we're facing today.

Matt, can you tell us a little bit about yourself?

I lead Abt’s data science, analytics, and product solutions. I’m an economist by training and spent two-plus decades in healthcare analytics—particularly Medicare, Medicaid, and commercial healthcare data.

What do you see as some of the biggest challenges we face with data quality and analytics?

Transcript: “There are a lot of challenges we face with data quality and analytics. First and foremost, the world is literally awash in data, right? We've become very adept at collecting data and storing data and even having the computational power to process that data. So data right at this point is an extremely valuable asset, perhaps one of the most valuable assets in, in policy-making research, in education policy … That's great, right? We have a lot of data to look at, but the sticking point remains going from all of that data to good evidence. Good evidence that informs policy. Let's take data quality, for example, we need to ask ourselves questions like even though we have a lot of data, is that data complete? Where might the holes be? And can we close those holes quickly with other forms of data? May be primary data collection, perhaps additional secondary administrative data sources, or even maybe we can close those gaps, methodologically.”

How can we address some of these challenges and help audiences understand and apply information learned from data?

Transcript: “First and foremost, from a digital perspective, there are a lot of ways we can make data accessible and more digestible to decision makers. Examples include creating pre-stage analytic files that can be quickly tapped to generate insights. There are also a lot of analytic tools available—business intelligence tools to pull information out of data quickly. And of course, there's visualization, right? To make very complex analytics, insights digestible, but that's not enough.

Really the Abt difference is program expertise. And it's not just program expertise in some roles; it's forming teams of multidisciplinary experts—and everybody on that team understands the program, details, the policy details, the content of the data, why the content of the data is what it is, and even knowledge of how our clients use that data, how they process the data all the way down to the analytic platforms and tools they have available. Being able to combine all the data, with the technology, the processes, and putting that in the hands of teams that know the policy context, the program context—that's really the difference-maker.

We don't stop our work. After we hand insights off to decision makers, we stay with them through the journey, providing technical assistance and change management services that help that decision maker actually put those insights in—make action steps out of them—and have those action steps drive real needle moving change.”

We hear a lot about the importance of centering equity in our digital approach. How do we do this effectively?

An irony we encounter advising governments on equity in policy and programming is that the data we rely on is often biased; data, algorithms, machine learning, and AI all tend to reflect the biases in society. So, one of our critical functions as a digital technical assistance (TA) provider is understanding bias embedded in data, as well as unrooting and preventing discrimination in our tools and analyses.

How do we do that? Data science can solve so many problems, but it really takes people—empathy and human-centered approaches—to undo them. Team diversity matters a lot. We need lived experiences to inform our solutions. That’s why Abt is building a pipeline of future analysts and researchers certified in equitable evaluations through a soon-to-launch certificate program with a major university. And it’s why we focus our TA on solutioning with the populations our clients aim to reach and serve. We have to understand and design systems with them to move the needle.

To advance health equity and access to care in states’ Medicaid programs, for example, a user-centered digital approach means looking at the different pain points that beneficiaries, case managers, program and policy administrators, providers, managed care coordinators, and community-based organizations experience when interacting with the systems and data that are intended to connect and serve beneficiaries. It’s important to ensure beneficiaries receive the right services from the right provider at the right time. Identifying true root causes impacting well-being – using data science and analytics, without bias—helps all people impacted by the Medicaid ecosystem.

And finally, what do you value most about working at Abt?

Transcript: “When you work with Abt, you're not just getting access to leading experts in the field. You're also working with people: humans who believe in the work that they're doing, who believe in the mission of Abt to address the wellbeing of some of the world's most vulnerable populations—and who believe in the mission of the agencies that they're working with. You're not just working with experts; you're working with people who care about the work they do and the impact it makes.”

The questions we’re answering, the problems we’re solving to help governments and other clients—provide more efficient, higher quality health care for seniors, or fairer loans and financial services for minorities, or more accurate disease surveillance systems, or statistics for safer justice and correctional systems—the list goes on and on. These things wake us up early and keep us up at night. We go the extra mile because of the purpose and potential this work creates. If you’ve worked with Abt’s digital team, you know we are technologists on a mission.