What is the McKinsey 7-Step Problem Solving Process?

What is the McKinsey 7-Step Problem Solving Process

What is the McKinsey 7-Step Problem Solving Process?

Think about all the harebrained ideas and strategies that big companies pursue. Why do they make such obviously silly decisions? They don’t have a disciplined process for analyzing problems and finding good solutions.

I will delve into the famed McKinsey 7-step problem-solving process today.

Legendary management consulting firm McKinsey & Company takes problem-solving extremely seriously. They have developed and refined a structured 7-step methodology that all McKinsey consultants use to methodically work through challenges. As former McKinsey partner Charles Conn states,

“By following steps, we can more clearly understand what problem it is we’re solving, what are the components of the problem, which components are most important to pay attention to, which analytic techniques to apply, and how to synthesize learnings into a compelling solution story.”

This methodology is used by top consultants to methodically work through even the trickiest issues. While no framework is perfect, this one at least forces you to slow down and think things through deliberately.

What is the 7-Step Problem Solving Process?

The McKinsey 7-step problem-solving process is a methodology developed by the prestigious consulting firm McKinsey & Company. It provides a structured way to think through difficult situations and develop solutions.

The 7 steps are:

  1. Define the problem
  2. Structure the problem
  3. Prioritize root causes
  4. Develop initial hypotheses
  5. Test key hypotheses
  6. Synthesize and converge on solutions
  7. Outline execution plan

By rigorously working through each phase, you avoid missing key details or jumping to flawed conclusions. It results in more thorough and effective problem-solving.

The 7 Steps Explained

Let’s dive into each of the 7 steps in more detail:

Step 1: Define the Problem

You can’t solve a problem until you truly understand what the heck it is. This deceptively simple first step is critical.

Ask: What is the actual problem we’re trying to solve here? What are the symptoms and effects we’re seeing? What are the goals and objectives? Get crystal clear upfront.

Many problem solving efforts fail right out of the gate because there was never precise agreement on the problem itself. Properly defining the problem ensures everyone is aligned and working towards the same endpoint.

Step 2: Structure the Problem

Once you know the core problem, you need to break it down into its components. Diagram it visually using tools like issue trees and prioritization matrices.

The goal is to uncover root causes rather than just treating symptoms. Look for relationships between different factors. Structuring makes the inherent complexities more understandable.

Step 3: Prioritize Root Causes

With the problem neatly structured, identify the 2-3 main root causes to prioritize. These are the areas where focusing your efforts will have the biggest impact.

Don’t spread yourself too thin by trying to tackle everything at once. Find the highest leverage points that will drive a disproportionate amount of the solution.

Step 4: Develop Initial Hypotheses

Time to start formulating potential solutions! Based on your diagnosed root causes, generate hypotheses about what changes could alleviate or eliminate the core issues.

Don’t jump straight to recommending solutions yet, but form educated guesses about promising directions to explore further. Hypotheses help avoid getting anchored on any single remedy too early.

Step 5: Test Key Hypotheses

Validate your hypotheses through research, analysis, experiments, and testing. Gather data and feedback to determine which ideas have merit versus which should be discarded.

This step is all about objectively evaluating your potential solutions before committing major resources. Ruling out the bad ideas early saves immense time and effort.

Step 6: Synthesize and Converge on Solutions

Now that you’ve pressure-tested your options, you can put together a concrete plan of attack. This is where you finally propose your recommended solutions to the problem.

Based on your testing results, synthesize the optimal combination of remedies into an integrated solution roadmap. It should comprehensively address the core issues at their root.

Step 7: Outline Execution Plan

The final step is determining how actually to implement your solutions. What resources are required? What roadblocks might you face? How will you track progress?

Build out a detailed plan for execution, including key milestones, owners, budgets, etc. Careful planning in this step paves the way for a smooth rollout.

When to Use McKinsey’s 7-Step Process

The 7-step methodology is most valuable for complex, ambiguous problems with unclear paths. It provides a rigorous framework to impose order on messy situations.

For straightforward issues with obvious solutions, the process may be overkill. It works best when dealing with:

  • Strategic pivots or directional shifts
  • Organizational change or restructuring
  • Operational optimization or process redesign
  • Financial performance troubleshooting
  • Any mission-critical business challenge

Whenever you’re facing a high-stakes quandary that impacts key outcomes, applying a proven process like this can mitigate risks of overlooking key factors or making rash decisions.

Strengths and Weaknesses

Like any framework, the McKinsey 7-step approach has its pros and cons:


  • Imposes logical structure on fuzzy situations
  • Helps uncover root causes vs. just symptoms
  • Forces disciplined, hypothesis-driven thinking
  • Results in comprehensive, data-backed solutions
  • Useful for complex, cross-functional issues


  • Can be overly rigid for simpler problems
  • Doesn’t account for time/resource constraints
  • Overemphasis on analysis can lead to “paralysis”
  • Relies heavily on assumptions and judgments
  • Mostly internally focused; lacks outside perspective

No model is perfect, but the 7 steps at least provide guard rails for tackling thorny problem-solving challenges in a structured way.

Dealing with Uncertainty

One of the defining challenges of problem-solving in today’s ever-changing business landscape is the pervasive presence of uncertainty. Rapidly evolving markets, disruptive technologies, geopolitical instability, and a host of other factors continuously introduce new unknowns.

This makes it critical that any structured problem-solving methodology has mechanisms built in to explicitly identify, analyze, and manage uncertainties throughout the process. The McKinsey 7-step approach achieves this in multiple ways:

Step 1: Define Uncertainty in the Problem Context From the outset, a crucial part of problem definition is fleshing out the key sources and degrees of uncertainty surrounding the issue. What are the volatile factors that could significantly impact the situation? What future scenarios need to be accounted for? Explicitly calling out ambiguities upfront prevents them from being overlooked.

Step 2: Uncertainty Branches in the Structure When disaggregating the problem into structured issue trees, distinct branches can be created to separately examine different uncertain elements and scenarios. This allows for rigorous mapping of how these uncertainties could affect other components of the problem.

Step 3: Prioritize Based on Impact x Uncertainty The prioritization phase provides an opportunity to assign intentional weight and emphasis to uncertain factors based on their potential impact and likelihood. High-impact branches with large uncertainties may get prioritized over more certain but lower-impact areas.

Step 4: Design a Hedging & Learning Plan
Part of the work plan development involves designing analyses and techniques to reduce key uncertainties through research, modeling, tests, and experiments. It also involves mapping out contingency plans to hedge against various possible outcomes related to uncertainties that cannot be fully resolved upfront.

Step 5: Test Assumptions & Scenarios
As the kernel hypotheses around uncertain factors are pressure-tested through analysis, the team is forced to confront and revisit the validity of assumptions. Results may invalidate certain scenarios envisioned earlier while raising new potential uncertainties to consider.

Step 6: Integrate Uncertainty into the Synthesis
When synthesizing the final solution and recommendations, it is imperative to attach confidence intervals, risk factors, and contingency triggers. The team should make clear which aspects of the solution are higher or lower conviction based on remaining uncertainties.

Step 7: Build Feedback Loops in the Execution Plan Dealing with uncertainty is not a one-and-done exercise. The execution plan must include mechanisms for continual monitoring of uncertain factors, course correction if needed, and a feedback loop to refine the solution as new information emerges over time.

By systematically integrating uncertainty at each phase, the McKinsey 7-step methodology imposes a disciplined process around identifying, prioritizing, analyzing, and managing ambiguities. This maximizes the robustness of solutions in our increasingly unpredictable world.


Q: Where does the McKinsey 7-step process come from? A: It was developed by the elite management consulting firm McKinsey & Company as a structured approach for their engagements.

Q: How long does it take to go through all 7 steps?
A: The duration varies widely depending on the complexity of the issue and the scope involved. For a major strategic overhaul at a large company, it could take months. For a smaller operational issue, potentially just weeks.

Q: Do you have to follow the steps exactly as laid out? A: No, the 7 steps are simply a general guiding framework. Experienced practitioners will adapt and modify the process as needed for each unique situation.

Q: Is this process only for business problems? A: No, the same core principles can be applied to all kinds of problems outside of business as well, from public policy to personal goal-setting. The fundamentals of structured problem-solving translate widely.

Q: What skills are required to use this process effectively? A: Key abilities include analytical thinking, data synthesis, attention to detail, project management, and communication. Prior consulting experience isn’t necessarily required with the right training.

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