In 25 years of professional consulting, I have used the science of policy analysis to complete scores of financial, economic, and/or governance projects with governments and businesses large and small. My consulting work employs statistical analysis, financial modeling, and research design.
Much of my consulting work involves developing new methods for utility policy analysis, including quantitative indices of utility rate equity and affordability.
Policy science for the water sector
The management culture of American water sector is a curious thing. Water sector executives tend to have a scientific mindset when making decisions about resource management, water quality, construction materials, and treatment technology. Most water managers are hard-headed, analytical thinkers when it comes to the physics and chemistry of their business.
It's surprising, then, that so many water sector leaders make policy and management decisions intuitively. Smart, hard-working executives who demand careful analysis of water quality are strangely comfortable relying on instinct and anecdotes when tackling issues like affordability, public communication, personnel management, and political processes.
On these issues, water executives often simply emulate what their peers do or rely on their own trial-and-error experiences, rather than following rigorous research.
We would never design treatment plants that way!
We can do better. My work is driven by the belief that science, not storytelling, should drive policy and management in the water sector. The greatest water quality challenges of the 20th century were chemical, biological, and physical. Those challenges remain, and new water quality threats emerge all the time. But the most formidable obstacles ahead are social, political, and economic. These obstacles can be overcome with rigorous research. Within organizations and across America’s nearly 50,000 community water systems, we can generate and analyze data to follow a M.A.D.E. cycle of decision-making:
Whether it’s affordability, equity, employee quality, board approval, or public trust, if you want something to count, find a way to count it. Some things are harder to measure than others, but good measurement is usually possible with some creativity and persistence.
Understand your current conditions, how you got there, and where you’re headed. Identify the factors that might be causing or alleviating problems. Review the scientific literature to see what it says about the issue.
Select alternatives that offer the best probability of net improvement and establish systems to produce data on processes and outcomes.
Every policy or management decision is a hypothesis that can be tested. Evaluate the impacts of your decisions on the measurements that matter. Did it work? Did it work as expected? Do we need to measure new or different things? Do we need to analyze data in new ways that might lead to different decisions?
You can think of this as the familiar Plan-Do-Check-Act (PDCA) with a scientific accent. Science revolutionized the world’s water and sanitation systems, saved countless lives, and brought about unprecedented prosperity. Social science holds similar promise for the management and governance of these essential systems.