Traditionally, the art of problem-solving has been the professional domain of management consultants. However, you don’t have to be pursuing a management consulting career in order to be an adept problem-solver. Below are four mental models for effectively solving business problems like a consultant.
1. Start with a hypothesis.
First, it’s important to define the problem you’re trying to solve by making a hypothesis. Doing so offers clarity in terms of the next steps and the information needed to move forward.
For example, say you’re given the problem of trying to determine why a company is losing market share. You suspect the cause is poor customer experience, so this becomes your hypothesis. You start with that, and then you collect data and perform research that either proves or disproves this hypothesis.
Hypothesis testing is not a new model. Its earliest dates to the early 1700s, when the model was used to understand whether male and female births were equally likely. However, if you’re new to setting up a hypothesis, it might feel unnatural starting out. Eventually, though, you’ll likely come to appreciate the simplicity and clarity with which it allows you to navigate a complex problem.
2. Understand the difference between causation and correlation.
It’s important to differentiate between causation and correlation. Just because two data points move together in the same or opposite direction (correlation), it doesn’t mean that one causes the other (causation).
Using the example above, market share and the quality of customer experience might both be declining at the same time, but poor customer experience might not be causing the decline in the market share. Having the insight to differentiate between causation and correlation will allow you to course correct if necessary. If you find that there’s no causation, then you’ll be able to redefine your hypothesis and begin the process of problem-solving all over again
3. Think “Mutually Exclusive Collectively Exhaustive.”
The underlying idea behind Mutually Exclusive Collectively Exhaustive (MECE) was developed by McKinsey & Company in the 1960s to help management consultants structure and frame business problems. The roots of MECE, however, date back to around 40 B.C., when Aristotle’s work on logic and syllogism was compiled into six collections of Organon.
MECE, in its simplest form, represents an approach to decomposing or segmenting a problem into a collection of ideas that are mutually exclusive to each other but when considered holistically are collectively exhaustive. For example, building upon the business problem above, what are the potential drivers that can cause the company’s market share to decline? You might be tempted to offer a laundry list of plausible drivers, such as customer experience, new market entrants, product quality, and new regulation.
As opposed to just creating a laundry list, MECE breaks out drivers into two categories: internal and external. Internal drivers (such as customer experience and product quality) and external drivers (such as new market entrants and new regulation) are mutually exclusive to each other and together encapsulate all the plausible drivers, and so are considered collectively exhaustive.
4. Use the 80/20 rule.
The 80/20 rule states that, in any business problem, 80 percent of the outcomes stem from 20 percent of the causes. Widely considered as an aphorism, the 80/20 rule does have an academic foundation in the Pareto Principle from the early 1900s, when it was first used to observe the distribution of wealth in Italy in the early twentieth century.
The 80/20 rule, as a model, helps to prioritize actions and focus on drivers that matter the most. Using the example above, there might be five potential drivers causing the decline in the market share: (1) poor customer experience, (2) new market entrants, (3) decline in quality of the product, (4) customers’ evolved preference, and (5) new regulatory requirements. However, new market entrants might be causing 80 percent (or most) of the decline. Consequently, the 80/20 rule helps with identifying and developing a succinct narrative around the crux of the problem.
A final note
While these mental models will help you solve business problems, you can’t solely rely on them under all circumstances. For example, certain problems require focusing on correlation more than causation. Also, redundancy, which MECE strives to eliminate, is sometimes needed. Nevertheless, these models will serve you well as building blocks for structuring even the most complex business problems.
Recipient of the Presidential Award from The White House, Vibhu Sinha is an intrapreneurial and bottom-line driven senior management professional with experience in leadership roles across banking and capital markets, advising institutional clients on corporate strategy, idea generation and pitching, financial planning and analysis, M&A, investor relations, and ESG. Vibhu developed his acumen in Behavioral Psychology at Harvard University as part of the master’s degree program, and also earned an M.B.A. from UCLA Anderson.