The Lean Startup Goes to Washington
Evidence-based policy, iteration, and innovation are making their way into government.
In policymaking, as in business, decisions are as good as the information on which they’re based. Policymakers always make decisions with imperfect information, so they must take measures to mitigate risk and improve outcomes. The trick is to do so without stifling innovation. In business, an improved outcome means a higher-performing company with better return on capital. In government, information that improves decision-making improves lives, optimizes taxpayer resources, and enhances productivity.
More and more, the government sector is working to improve the quality of information—or evidence—it is using to formulate decisions and policy.
This is what we call evidence-based policy. Evidence-based policy unlocks existing, but compartmentalized, administrative data from federal agencies to track the impact of policies over time. It can mandate third-party evaluations using tools such as random control trials (RCTs) to conduct studies that measure the impact a particular policy on a given population. It tracks the impact that grantmakers seek to achieve. It strikes a balance between innovation and accountability, giving programs enough freedom to innovate, or, in Silicon Valley terms, giving them “the runway to pivot” but demanding that they track important performance to ensure that they achieve results. At its core, it is about government investing in what works and dialing back what does not.
In the private sector, of course, this is how venture capital works. Venture capitalists risk capital to invest in startup companies before they know those companies will work. They validate hypotheses one step at a time, and invest more over time as they “de-risk” certain elements of the team, technology, and market. In business, investors track performance indicators and host quarterly board meetings.
We’re starting to see the principles of evidence-based policy applied to grant programs at a number of federal agencies. In 2013, the Office of Management and Budget (OMB) issued official guidance to federal agencies, highlighting the benefits of staging grants around evidence and holding programs accountable. The United States Agency for International Development (USAID) created Development Innovation Ventures, a venture capital-style fund that brings financial resources and technical expertise to global startups and policy interventions based on data, performance, and promise. Its open call for applications has allowed USAID to uncover problems and solutions from innovators all over the world who are addressing issues as broad as improving access to clean water through chlorine dispensers or reducing traffic fatalities in Africa via behavioral interventions that nudge passengers to temper drivers.
It’s not the government “doing venture capital,” but it’s improving federal grantmaking by adopting the methodologies of risk mitigation and Lean Startup philosophy.
By understanding what programs can best achieve results, government can help scale those interventions through public-private partnerships. Programs like these exemplify social innovation—they use better information to determine which programs work and can scale, and therefore improve lives, better optimize taxpayer resources, and build enduring ecosystems to solve old problems in new ways.
Evidence-based policy doesn’t mean that government won’t miss, but it does mean there should be a material improvement in the effectiveness of funded programs and a decreased probability that a failing program will continue to get government funding over time. It’s about bringing ideas that have worked elsewhere to Washington, tracking performance indicators, and rigorously measuring outcomes with data. It’s about asking the right questions about the goals of a given program, what metrics to track, and what types of evidence will ensure that the program is having the desired impact on society.
In Silicon Valley, the Lean Startup movement is driving a mantra of “build, measure, learn.” Improving and accelerating feedback loops and using information to iteratively improve outcomes on relevant timelines is central to innovation. In Washington, evidence-based policy and new approaches like Pay for Success bring a Silicon Valley Lean Startup ethos to public service, with the goal of creating stronger communities and generating better returns for the country. With these early examples of success and additional offices signaling interest, we see mounting evidence for this approach finally taking hold in the public sector.