November 16, 2024
In the past, I haven't spent enough time picking the right problems to work on. Pretty quickly after starting to explore why, I noticed that I have loose definitions for both "right" and "problem".
Before we even have a chance to find the right problems, we need a way to think about what problems are to begin with.
To start — it's easier to understand problems in specific contexts like solving a math equation, finding a profitable way to deliver a good or service, handling traffic in a distributed system, etc., but it's a generic definition of problem which evades me.
The first step I took to find a generic definition was to make a big list of different problems in business, science, engineering, self-improvement, personal relationships, and economics; then read them a few times and let them sizzle in my unconscious while I went about life. While I was watching 21st Jump Street with a couple of friends, a framework came to me and I'm taking a moment to write it down:
We can define a generic problem with a few arguments:
S and a function f that describes its dynamicsS' that satisfies a specific condition or goalCThe problem: find or design a transformation f such that f'(S) = S', optimizing for C.
Finding f': This often requires a process of diagnosis (understanding f), design (proposing f'), and implementation (applying f').
I like this abstraction since it fits the essence of most problem-solving scenarios while preserving its intuitive appeal.
Everyday life: Current state S = keys are lost. The solution function f' implements steps to find keys (e.g., retrace steps, check common locations, call last known location), leading to desired state S' = keys are found. Constraints C might include time available to search, physical accessibility of spaces, and mental state affecting memory recall.
Business: Current state S where f(customer engagement strategy) = high churn. The solution function f' implements improvements to customer engagement (e.g., personalized outreach, better onboarding, proactive support), leading to desired state S' = low churn. Constraints C might include budget limitations, team capacity, and technical feasibility.
Engineering: Current state S where f(solar panel design) = low efficiency. The solution function f' implements improvements to the design (e.g., new materials, better light absorption techniques), leading to desired state S' = high efficiency. Constraints C might include material costs, manufacturing feasibility, and durability requirements.
This definition of problem even works for the problem of finding the right problems!
Problem: Current state S where f(all possible problems) represents our unfiltered view of problems. The solution function f' implements a filter based on our values, capabilities, and impact potential, leading to desired state S' = high-value problems worth solving. Constraints C include our time, resources, skills, and the requirement that solutions create lasting positive change.
When I think about the problems that I want to spend my life on, they share a few characteristics:
S → S'),f to f' is ambiguous).That said, just having interesting problems in my vicinity isn't enough. My role in solving the problems is also important — I need real ownership to give my life to solving a problem. Ownership means something very specific to me: It means that my success or failure is judged on outcomes over a sufficiently long time horizon such that I can make unpopular and seemingly insane bets with enough time for them to win out in the end.