This post is influenced the book Bulletproof Problem Solving, written by two McKinseyites, Charles Conn, and Robert McLean. I recommend picking it up if you want a deep dive into problem solving frameworks.

Problem disaggregation

“Problem disaggregation” can be summarised as: breaking down a problem into logical components so that it can be understood.

Problem solving is effectively understanding a situation well enough so it can be resolved. It’s often said that a well understood problem is already half solved.

To demonstrate the importance of understanding a problem before trying to solve it, Abraham Lincoln famously said “Give me six hours to chop down a tree and I will spend the first four sharpening the axe.”

In this sense, problem disaggregation is a tool that exposes the different parts of a problem, making it easier to understand, prioritise, and work with.

How to disaggregate any problem

The best way to learn the disaggregation process is by example, so let's look at a simple example followed by a more complex one.

Example 1: Simple problem

Problem

You need to get from your hotel to the airport with all your luggage in time for a flight home.

Context

You're in a country you've never visited before, and you don't speak the language. You know there are several transport options available, each with tradeoffs.

Components

• Transport options: Uber, Taxi, Coach.

• Time: you've got 3hrs until boarding.

• Luggage: one large suitcase and a small bag.

• Assistance: one helpful member of hotel staff speaks English.

Confidence values

With the components identified, they can be compared to give a confidence rating for each transport option.

Confidence is subjective but it's still measurable. By weighting each variable based on its subjective importance, the different components can be independently measured.

Example 2: Complex problem

This example is borrowed from Bulletproof Problem Solving.

Problem

A family is moving home. Where should they live?

Components (weighted)

• Proximity to good schools [0.35]

  • …2x sub variables

• Nice environment [0.25]

  • …3x sub variables

• A cool, friendly town [0.25]

  • …6x sub variables

• Not too far from everything [0.15]

  • …1 x sub variable

Weighted score

Further use cases

I hope you've found learning about disaggregation theory as revealing as I did when I first stumbled into it.

The disaggregation framework is a real Swiss Army knife. It's useful across domains, and with problems of different complexities. It can be applied to business questions like "should we market to segment X or Y," or "which product idea higher risk".

If you want to learn more about framing the problem well, read my previous post which explains how to define problem statements.

Catch you soon,
– Jason

PS – You can explore the data used in this post in this Google sheet!