As the lead for the recently formed data analytics team, Pete will be using machine learning and predictive/prescriptive analytics to create models to evaluate and improve the effectiveness of social programs for BCTs’ clients.
Q: How did you begin working in the field of evaluation?
Pete: I began my evaluation career over 20 years ago at Case Western Reserve University’s Center on Urban Poverty. I was the Project Manager for the first ever application of the “theory of change,” evaluating the Cleveland Community Building Initiative.
Q: How did you originally get interested in the field?
Pete: I grew up as the son of a social worker and after I graduated from college, I became a social worker as well but I was also interested in statistical analysis. As a case manager for the homeless, I began to see how data was able to change the way decision-makers make better decisions, including data about the effectiveness of social programs. Inspired to learn how to use data to advance social good, I decided to go grad school, where I earned a MSSA as well as a PhD (ABD) in Social Work from Case Western Reserve University.
Q: Once you finished your studies, what were some of the applications that you saw for data analysis?
Pete: At that point, many foundations and non-profits were starting to express interest in evaluating the effectiveness of the projects that they were funding. The earliest work I did was studying the impact of programs and community building efforts to improve early childhood outcomes and school readiness for philanthropies like the Graustein Memorial Fund and the W.K. Kellogg Foundation.
Q: You have spoken quite a bit about the subject of “precision analytics”. Can you explain how that differs from statistical analysis?
Pete: Statistical modeling applies mathematics to the analysis of data to describe and visualize overall trends and population-level aggregations and results. Precision analytics uses machine learning, which can learn from so much more than numbers, including stories and narratives, in order to determine what will work for you. Precision analytics supports real-world, here-and-now decision-making on a case-by-case, situation-by-situation basis. In personal terms, my work in precision analytics is allowing the researcher and evaluator in me to finally deliver insights to the former social worker I used to be, working on frontlines meeting and helping individuals, right where they are.
Q: Why did you decide to come to BCT Partners?
Pete: I had met Randal Pinkett (CEO and Founder of BCT Partners) many times in my career and I was impressed by his commitment to social justice as well as his accomplishments both personally and professionally. I also had met Lawrence Hibbert (Managing Partner and Founder of BCT Partners) and I realized that this commitment to positive social change was a passion that was shared by all of the Principals in the company. I was also looking for a company that was interested in applying machine learning to the field of social work and I found that BCT Partners was not only committed to that but also had the ability to scale a practice devote to it in a meaningful way.
Q: What are some of the biggest obstacles that you see in applying machine learning to the field of social work?
Pete: I don’t think of obstacles – I think of opportunities. Our biggest opportunity is to help educate non-profits, government agencies and foundations on how to use machine learning to substantially improve outcomes. Most people think of data as purely statistical. We have an opportunity to help people see how data can be used to tell a story and in a very cost-effective way.
Q: Any parting words?
Pete: I am very excited enter the next phase of my career at a place like BCT Partners that is making a real difference in the world.