PMs continuously face ambiguous problems. It's your job to apply a structured approach to decompose the problem, and navigate the optimal path towards a solution.
Framing Questions – Can you frame the problem correctly and find the most important question? skip to section
Mental Models – Do you have a wide range of tools to help you analyze a situation and make a decision? skip to section
Cognitive Awareness – Can you avoid common errors in judgement? skip to section
Too often we start with solutions before we determine if we're asking the right questions. When faced with a complex problem, try to simplify your analysis down to the core, important tradeoffs.
Excerpt from Eigenquestions: The Art of Framing Problems
Aside from being an interesting snapshot from the internet historical archives, this story demonstrates an important learning: the power of a good frame — a critical success factor for teams and an important skill to master. By reframing the question as "consistency vs comprehensiveness," we made a clear decision and created a frame for a series of hard decisions down the line.
What is framing, and why does it matter? Framing is the process of breaking down a problem into a set of choices, tradeoffs, and options that enable a team to make a call and move forward.
At Coda, framing is an important skillーone we look for in candidates and teach to new employees. When done well, framing can steer the company, product, and team through tricky situations. When done poorly, we can feel stuck, frustrated, and like we're debating for an unnecessarily long period of time or are zeroed in on the minutiae of a decision.
First, articulate the why behind your actions. This should set the overall context and help you focus on what's important.
Then it helps to write down what you know to be true. A useful framework for this is First Principles. Rather than reasoning by analogy, you break down a problem to what you're sure is true and reason up from there.
If you're not familiar with this concept, watch Elon explain how he used it to understand battery production.
Battery packs are really expensive
What are batteries made of?
What is the cost of the individual materials?
Can we find a cheaper way to combine them?
When looking at a problem, don't start with a solution based on what you already know. Try to strip out existing biases and constraints to get to the core truth. Start your solution from there.
Once you've asked the right questions and gotten to the core, you'll need tools to help you think through various scenarios. Mental models are frameworks for better thinking. They help us think smarter and faster.
Excerpt from Mental Models: The Best Way to Make Intelligent Decisions
A mental model is simply a representation of how something works. We cannot keep all of the details of the world in our brains, so we use models to simplify the complex into understandable and organizable chunks.
The quality of our thinking is proportional to the models in our head and their usefulness to the situation at hand.
The more models you have—the bigger your toolbox—the more likely you are to have the right models to see reality. It turns out that when it comes to improving your ability to make decisions variety matters.
The OG of mental models is a fellow named Charlie Munger who, along with his business partner Warren Buffet, invested in businesses. When he needed to make sense of the world, mental models proved superior to remembering isolated facts.
No one can know everything, but you can work to understand the big, important models across multiple disciplines – at least at a basic level. They collectively add value to both access the situation and come to a reasonable conclusion.
For Charlie, this meant understanding disciplines like biology, psychology, history, and engineering to become a better investor. For you, it means having a checklist of things to think about to help improve prioritization, scoping, and shipping.
It won't always be possible to clear up all the ambiguity around a certain decision. You'll need to get comfortable making educated assumptions based on data, and learn how to test those assumptions in the lowest cost way that still gives you reasonable certainty over the results.