How Does Mckinsey Consultants Analyse And Solve Problems?

3 Attributes of Mckinsey Way of Problem Solving

Consultants who succeed love to solve problems. A part of them is always asking, “Why is something done this way? Is this the best way it can be done?” They are fundamentally skeptical about everything.

As a management consultant led by ex-Mckinsey partners, I have learnt how to solve problems in the so-called Mckinsey Way.

The Mckinsey way of problem-solving process has three major attributes:

• Fact-based
• Rigidly structured
• Hypothesis-driven

Attribute #1: Fact Based

Facts builds credibility, because your client knows you are not advising them based on gut instincts.

Having drawn up an initial hypothesis for the problem, the team races to gather the facts necessary to support or refute it.

Attribute # 2: Rigidly Structured

To structure your thinking when solving business problems, you must be complete while avoiding confusion and overlap.

MECE stands for “mutually exclusive, collectively exhaustive”. MECE structures your thinking with maximum clarity (hence minimum confusion) and maximum completeness. MECE starts at the top level of your solution- the list of issues making up the problem you have to solve. When you think you have determined the issues, take a hard look at them. Is each one a separate and distinct issue? Is so, then your list is mutually exclusive. Does it also include every aspect or item relevant to the problem- that is, have you thought of everything? If so, then your issues are collectively exhaustive.

You can have “other issues” as a category to ensure the issue list isn’t more than 5 top-line issues (of course, three is best), and not fewer than two.

Attribute #3: Hypothesis-driven

Step 1: Defining the initial hypothesis (IH)

“Figure out the solution before you start”. Every time we receive a business problem, every one in the team would breakdown the business problem into smaller components and list out different solutions in a MECE way. These solutions are just hypothesis. They are yet to be proved or disproved by fact gathering.

In 2020, our team received a business problem- How to reduce the packaging material cost in our clients’ warehouse.

We broke then the business problem into 4 components (aka Key Drivers).

• Cardboard box standardization
• Procurement centralization to achieve economy of scale
• Introducing new materials to replace current ones
• Digitizing material inventory management

These are 4 directions that we wanted to explore to resolve the problem. Each teammate is responsible for one hypothesis.