Steve Goldberg has been called “probably the most ambitious man in American philanthropy. He expects the nonprofit world to live up to its own hype and solve — yes, solve — the knottiest social problems. And he has a plan to fix it.” – Authors, Matthew Bishop and Michael Green. Markets For Good caught up with Steve to sharpen the conversation on three questions that cross the implications of the “data” conversation with to his perspective as laid out in the book, Billions of Drops in Millions of Buckets. He is also the founder of Caffeinated Capital.
Eric J. Henderson, Curator, Markets For Good (EJH):
What is the data infrastructure implied by the “billions of drops” perspective on aligning funding with performance?
Steve Goldberg (SG):
To see the data infrastructure, we have to start by looking at how service is delivered. One thing all effective social innovations – like home-visiting programs for high-risk pregnancies, transitional employment for ex-offenders, and intensive family therapies for at-risk children and youth – have in common is they’re very ‘high touch’. The intervention doesn’t address one problem, but many contributing factors, forming a complex, but highly integrated service package that must be delivered in close fidelity with the validated model over a long period of time to achieve the desired results.
But with social programs, we face the dilemma of either making a highly effective innovation (like Nurse-Family Partnership) available to a very small percentage of the people in need, or providing a ‘lowest-common denominator’ service to a lot of people that doesn’t work very well (like Head Start).
Scaling social innovation is going to involve the seemingly oxymoronic task of serving exponentially more people without sacrificing highly personalized delivery. E-commerce succeeded because Internet businesses figured out ‘mass customization’, and we have to do the same thing with social innovation. If we take shortcuts and homogenize social innovations, we’ll fall victim to ‘reversion to the mean’ in which programs that worked well under laboratory conditions fizzled when they were expanded.
All of these moving parts will not come together or work in alignment without a lot of timely, accurate and coordinated information, which simply does not happen spontaneously. Scaling high-touch innovations is inconceivable without commensurate progress in data infrastructure.
What is the prospect of real-world course-correction for strategies based on patient funding and long-term commitments?
This is the make-or-break question. Social entrepreneurs have developed incredible innovations over the last couple of decades, but not one of them has scaled. Focusing on meaningful data has brought us to evidence-based interventions on the front end and measurable outcomes on the back end, two things we really didn’t have until just a few years ago. The convergence of social, financial and data innovation create the potential for transformational change.
What’s still missing from the equation, though, is operationalizing the use of rigorous data over the course of long-term investments. We need to track whether large-scale implementation in the field is faithfully applying the lessons of past research, and whether ongoing performance is on target to meet projected outcomes. Patient funding and multi-year, performance-based projects provide the first real opportunity to scale social innovation by enabling data-informed course-corrections.
That requires coherent information architecture, relentless quality control, continuous assessment, vigilant performance management, and real-time reporting.
Do you think the current focus on “data infrastructure” represents a step toward achieving the kind of collaboration (shared goals, shared measures) to face big, complex social problems?
There’s no question about it. Many folks have fought the good fight for years on demonstrating the importance of measuring results and developing practical and affordable ways of going about it at the programmatic and organizational levels. In just the last couple of years, thought leaders like Omidyar Network, Monitor Deloitte, CASE at Duke’s Fuqua School of Business, and the Hewlett Foundation have elevated the discussion to the sectoral level, and organizations like the Strive Network, FSG and New Philanthropy Capital are building new tools and frameworks like collective impact, shared measurement and data labs to make that possible.
When I started writing my book in 2007, it was conventional wisdom that you couldn’t measure impact. Now, few doubt that most nonprofits can and should do so, and we’re on the verge of accomplishing the same thing for large networks of organizations responding to pervasive social problems. With the arrival of financial innovations like social investment, we’re finally going to be able to build the data infrastructure we need to truly scale innovations that work without compromising their effectiveness.