Issue trees

What is an issue tree?

An issue tree is a fundamental tool used to create a mental map of a core question following the M.E.C.E principle. 

Issue trees are perfect for problem-solving, as they help you divide problems and break them into manageable pieces so you can solve them. 

An issue tree has three major characteristics (fractal, layers and issues), and each part resembles another. It is structured in hierarchical layers, each following the M.E.C.E principle. Issues don't overlap conceptually, but when added to the issue tree, they cover every possibility of a problem. 

You can go as deep as you want for each issue added to the tree. However, each issue must be fully explained by the problems or questions in the next layer.

The four major components of an issue tree

There are several ways to break down a core question using an issue tree. 

The four most common structures⁠—mathematical formula, process, business framework and segments⁠—are the most powerful and the ones we will focus on. 

To demonstrate each of the four structures, let's use a real-life scenario from the early 2000s. When Netflix started gaining steam in the DVD hire (and later streaming) business, Blockbuster CEO James Keyes asked himself a core question: How can Blockbuster increase the profitability of its stores?

Here's how Issue Trees can answer that question. ⬇️

Component 1: Mathematical formula

The mathematical formula issue tree breaks down the question to get a numerical answer. 

To try and get to the bottom of Blockbuster's core question, the issue tree may look to calculate profitability per store (minus costs) like so: 

The first layer is closest to the core question. It captures customer numbers multiplied by $ per customer/average ticket size. Using this information, Blockbuster can ask more specific questions on the second layer of the issue tree, like the number of people in a store multiplied by % of those who purchased something. 

Component 2: Process

The second issue tree uses a process to analyze each issue separately. 

In Blockbuster's case, profitability per store = customers coming to the store multiplied by spend in store. Costs like storage and rental are then subtracted to get a realistic operating figure: 

Each bucket can also be further split into smaller categories to ensure all issues from the core question are covered.

Component 3: Business framework

The third method is to use a traditional or existing business framework to examine the core question.

For example, Blockbuster can use the four Ps of marketing (products, place, price, and promotion) to break each issue down into more detailed pieces: 

This framework also works well by replacing the four Ps with the five Cs⁠—context, customers, company collaborators and competition⁠—depending on the business problem.

Component 4: Segments

The last method uses segments for analysis. 

In Blockbuster's case, segmenting customers can help analyze which persona the company should focus on to solve its core question. The company's main four customers are highly profitable customers, moderately profitable customers, breakeven customers and negative margin customers. Using a segment issue tree, each customer base can be further divided into revenues and costs (or any other metric) to help Blockbuster understand how to reach (or eliminate) certain customers. 

⚡ Prezent Pro Tip: Get the most out of an issue tree with these three tips:

1. Start with the core question: The issue tree exists to add structure to solving a problem. Defining your core question is the most important starting point. 
2. Structure the core questions into sub-questions: Break down problems and roadblocks using one of the four methods to make each issue more manageable.
3. Follow M.E.C.E at every layer. Reduce duplicate work and keep your team focused using the M.E.C.E principles we've already discussed. 

How to build an issue tree using M.E.C.E

An issue tree is a rigorous mental map of the core question, and they work best when the M.E.C.E principle is followed to create them. 

The main problem with an issue tree is its complexity. Companies try to build a detailed mental map of a core question and a problem, which can lead to issue trees becoming overly complex and challenging to work with. Here's an example of this happening with an issue tree for a return on investment capital (or ROIC). As more layers and nodes are added, the tree becomes complex and hard to solve:

The various branches and notes make it easy to get lost in the details of the tree. To avoid this, we need to use a technique called pruning. Branches of an issue tree are cut off to stop the complexity of the diagram exploding. 

So, how should we decide which branches to prune? 🤔

A simple approach is to look at each branch and prioritize the important ones based on two assessments:

1. Estimate the level of effort to solve that branch 
2. Estimate the impact of solving that branch on the overall solution

If the two assessments are placed on an axis, it creates four branches we can use to quickly decide which need pruning. Here's the final result:

It's easy to see which branches need pruning and which ones we should keep. For example, the high-impact/easy branches are no-brainers to keep, while low-impact/hard branches need to be ignored or eliminated.

Pruning Blockbuster's issue tree using M.E.C.E

Let's go back to the Blockbuster core question we attempted to solve earlier: How can blockbuster increase the profitability of its stores? 

This is what the issue tree looks like if we try and solve the question using a mathematical formula: 

We're left with four branches at the end. If we then apply the prioritization approach, we can figure out which (if any) branches need pruning. In this case, the branch with the low impact and high effort is the people who come to the store⁠—this can be pruned. The other branches, # of products purchased, % of in-store shoppers and $ per product, can stay. 

This simple exercise could've helped Blockbuster focus on answering its core question and stay competitive against Netflix. 
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Expert Corner: Bob Dvorak solves problems that matter

Bob Dvorak spent ten years as a senior partner at McKinsey, leading teams in tech, media operations, sales and marketing.

He then founded Adaptam—a software development company in San Francisco. Dvorak says he has consistently used issue lists to solve major problems and develop solutions in business.

"An issue tree is kind of laying out the logic and steps⁠—it requires a lot of thought, a lot of restructuring and a lot of work," he says. 

"I tend to do the issue list, and then I test to see what's different and what's most important." 

Once this work is done, Dvorak's next goal is to find the most efficient way to solve a problem requiring the least amount of work. Here's how Dvorak does that using these three steps:

• Diagnose. He quickly discerns all the issues around a problem. This requires going down the list and laying out all of the issues (usually in a spreadsheet)
• Group. Next, add each of these issues into groups to make them more manageable 
• Choose. Finally, test each issue to figure out what's worth solving and what's really going to matter when answering the core question

Leaders who want to answer core questions have a similar theme, whether it's an issue tree or an issue list: breaking down the questions into manageable pieces is the key.

Complex problems are better solved in pieces

Core questions are notoriously complex to solve. 

To find the real issue of a problem, we often have to dig deep. If we don't have the right strategy, we risk asking the wrong core question and not solving our problem. 

Using strategies like issue trees, M.E.C.E, and prioritization graphs make this process a lot easier. Leaders can eliminate unhelpful issues so it's easier to focus on questions and scenarios that will bring them closer to answering their core questions. 
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Want to learn more about solving problems? Check out Prezent's detailed article on structuring problems here.