Meta-Problem cycle
There are several key categories of information that help us to navigate the meta-problem.
See some worked examples, following the below key steps, here.
Key steps
Dilemma
The high-level issue you are trying to address. This might be inspired by something that bugs you or some evidence you have that something could be better in the world.
Dilemmas can range from relatively trivial to existential: from making mealtimes with the kids less stressful, to reducing homelessness or increasing global sustainability.
For those who want to understand why we start with a dilemma instead of the traditional idea of a "problem," read more here.
Supporting Goals
The improvements you would like to make in the world to address the dilemma. There are usually many choices, and some may conflict with each other. For example, if the dilemma is reducing homelessness, your supporting goals might include more low-cost housing, changing the zoning laws, accessible mental health care, and so on.
Selecting the best set is done later in the meta-problem cycle after you learn more about what's possible.
For a strategy to identify a comprehensive set of goals, learn more here.
Problem Space
While goals tell us what we want, our next step is to understand what is holding us back from making progress on them. Are there obstacles in the system that we need to remove before we can make progress? How much effort for how much return? Et cetera.
This approach is borrowed from calculus as we explore the neighborhood of the current dilemma.
For those who want to dive deeper, you can read a mathematical explanation of the problem space here.
High-Yield Problems
Sometimes solving one problem helps make progress towards several goals. In this step, we identify these “two-for-the-price-of-one” problems.
Meta-Problem
In this step, you select which of the many possible options in the high-yield problem step is the best set to address the dilemma. Which problem will best support the goal? Which problem will deliver the best outcome for the least amount of time, effort and money?
For a technical version of the meta-problem, you can read more here.
Implement & Learn
Observe and learn as you go. New information may reveal itself as you implement your chosen solution, so check continuously that you’re still solving the right problem