From the top floor of Hotel Revival, I marveled at a sunny 360-degree view of Baltimore. Directly south along the water I could see Port Covington, a former industrial area being redeveloped into a new metro ecosystem. Will this be “Dubai on the Patapsco” or a mirage? To the northwest, I could see Sandtown. This area used to be known as Baltimore’s Harlem and was the center of protests to take on police brutality and express outrage at decades of disinvestment in West Baltimore. A block to the east, I could see the nation’s first Washington Monument in Mount Vernon Place. A statue of George Washington stands atop a column in the center of the square, symbolizing the creation of a new political system.

I thought about the purpose of my visit: to learn more about a complex problem being addressed by the National Fund’s network partner in the region, the Baltimore Workforce Funders Collaborative. They’re creating a new outcome reporting system for workforce programs.  It might sound boring, but these changes in the way data is collected and reported have the potential to reduce racial employment disparities.

People understand redeveloping the waterfront, ending police brutality, or even honoring the first head of a new government. But, how do you explain what it means to fundamentally reshape the workforce development system? How do you explain the decriminalization of poverty, which is what ultimately our partners in Baltimore are trying to do?

Even to receptive ears, talking about my work often generates confused responses:

• I try to make government job training programs better. Oh, do you work for the government?
• I help improve the quality of jobs. So you work in business or HR?
• I engineer the labor market so that… You build markets?

When I was in Ohio a few weeks earlier to watch Paradox Prize pitches and meet with the Baltimore, Atlanta, Cleveland, and Syracuse collaboratives to learn about their systems change work, we faced similar semantic challenges.

As we discussed the work, we found ourselves saying things like, “To achieve our goal of systems change, we will change systems themselves through system changes.” The term “systems change” had become circular, vague, less clear. The term was shorthand for too many things simultaneously: goals, strategies, and tactics.

Our confused discussion reminded me of Nobel Prize-winning physicist Richard Feynman’s distinction between two types of knowledge: knowing the name of something and understanding it. In a thought experiment, Feynman suggests the following: Without using the new word which you have just learned, try to rephrase what you have just learned in your own language.

Building on this, our group decided to adopt the Fight Club rule: the first rule of systems change is don’t use the term “systems change.”

From there, our conversations about the work brought things into focus. We discussed the benefits of seeking short-term incremental changes versus long-term strategic shifts. We weighed potential activities relative to estimated effort versus expected impact. We debated whether we were addressing problems with the most effective strategies. We were finally talking about actual system problems and solutions, not the philosophical essence of systems change.

Most importantly, we had time to ask questions we didn’t know the answer to. That felt like a luxury. In the end, we were asking good questions and thinking about methods and tools that would help us find good answers.

In other words, we spend too much time asking, “What is the workforce system? What is systems change?” Instead, the problem itself should help define the boundaries of the system; you can see which connections are relevant or not. Focus on how, not what.

A first step for any systems change initiative is to identify the problem and understand how it functions systemically. For example, we might ask, when conditions are x, how does our problem get better or worse?

In Baltimore, insight comes not from identifying what—in this case, racial employment disparities—but from seeking to understand how philanthropic investment, workforce programs, and labor market data function interconnectedly to produce those disparities.

The second step is exploring whether you’ve identified the right problem. Behavioral economists posit that uncertainty plus human fallibility equals the risk—or even likelihood—of solving the wrong problem.

Is the development of Port Covington into a technological Disneyland the right problem for Baltimore to solve? Does it respond to or address the unemployment and housing problems in Sandtown, just five miles away?

The third and final step is to consider whether this particular problem is worth solving given (1) other potential problems you could address, (2) the likelihood of resolving the problem, and (3) your ability to have an impact.

Beware any systems change initiative that doesn’t clearly state what the problem is, have clear objectives for resolving it, and explain why they are addressing this problem.

In our eagerness to “do the work,” this pre-work and thinking may seem tedious, even unnecessary. But when you’re faced with 360 degrees of choices, as Baltimore is, these important steps will set you in the right direction.