There are 2 ways to be a good product manager, and one way is better than the other.
PM (A): Know the answer to any question.
PM (B): Know how to find the answer to any question.
If a PM want to build a giant application, what is the difference between the two approach ?
PM (A) would need a database of answers to all questions. For every question it received, it would parse it, interpret it, look up the corresponding answer, and return the answer.
PM (B) would need a set of programs that could answer all questions. For every question it received it would need to parse it, interpret it, look up the corresponding program that can answer that type of question, run the program, get the answer, and return the answer.
The difference in the two approach is key:
The benefit of PM (B) is that he needs fewer answer to answer the questions. So he would probably require fewer rows of information to look through. The downside of PM (B) is that getting the answer would be much slower, since it would require a program to be run.
What is the difference in strategy between becoming a PM (A) versus a PM(B) ?
Becoming an PM (A) requires training to store a large set of data. Answers.
Becoming an PM(B) requires being willing to forget answers and to instead work towards general strategies for finding answers.
I think they are actually two very different learning strategies, and that given our minimal short and long term memory capacities a PM has to pick a side.
The application developed by the PM(B) has adopted the “evolutionary” approach: it has no ability to store answers to questions, but has developed a system of solving problems through programs (natural selection) that is way more efficient than the application developed by PM (B).
What are the processes that support PM(A) versus the process that support PM(B)?
PM(A) processes: experiment data, user research data, market research data, highly qualified and experienced people who have been thinking about your problem area for a long time.
The application requires building a catalog of answers.
PM(B)processes: state your core problem and the desires it fulfills, find people who have the desire/problem, propose solutions, get feedback on the solutions, build better solutions.
The application requires running a process.
I strongly believe that PM(B) is more efficient, and less likely to become outdated, than PM(A). PM(A) is faster and has better short-term ROI but PM(B) is better in the long term.
PM (B) strategy in a bullet points:
– Define the problem in terms of desires that are currently unfulfilled
– Propose a variety of solutions to fill unfulfilled desire
– Gather feedback from people who have unfulfilled desires on whether or not the proposed solution helps them
– If desire fulfilled, go to the next step otherwise go to step 2.
– Market your proposed solution to people who have unfulfilled desires
If you think about it, PM(B)’s strategy doesn’t actually require answers to any questions. It only requires quick feedback loops between people who have a problem and possible solutions to the problem.
Similarly, natural selection doesn’t require answers. A specific species doesn’t need to know how to survive, they simply need to have quick enough reproduction cycles and sufficient mutation between generations to find a solution to an environment’s changed circumstances before they run out of the ability to generate answers.
Natural selection (evolution) has solved questions on our planet to lead to a species of animals that can understand the program that ran to generate them.
The PM(B) strategy is optimised at finding a solution before options run out.
The best way to sort problem is to have a process (mutate, gather feedback, select best, repeat) instead of trying to store alternative solutions to future problems. In other words:
PM (B) > PM (A)
To be a good PM, let built a framework able to understand the problem.