How I Problem-Solve
Problem-solving is a skill that applies to any position and every industry. Problem-solving enables us to identify and exploit opportunities in the environment and exert (some level of) control over the future. Problem solving skills and the problem-solving process are a critical part of daily life both as individuals and organizations. Developing and refining these skills through training, practice and learning will provide the ability to solve problems.
You can use many different approaches to problem-solving, but I’ll work through four distinct stages, understanding each step of the process helps me to solve some of the most complex business problems and cone up with a workable solution.
1. Start with a hypothesis.
First, it’s important I define the problem I’m trying to solve by making a hypothesis. Doing so offers clarity in terms of the next steps and the information I need to move forward.
For example, I’ve been given the problem of trying to determine why a company is losing market share. I suspect the cause is poor customer experience, so this becomes my hypothesis. I start with that, and then I collect data and perform research that either proves or disproves this hypothesis.
I’m not new to setting up a hypothesis. I come to appreciate the simplicity and clarity with which it allows me to navigate a complex problem.
2. I 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 me to course correct if necessary. If I find that there’s no causation, then I’ll be able to redefine my hypothesis and begin the process of problem-solving all over again
3. I Think “Mutually Exclusive Collectively Exhaustive.”
The underlying idea behind Mutually Exclusive Collectively Exhaustive (MECE) helps me structure and frame business problems. MECE is 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? I 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 allows me to break 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. I 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.
The 80/20 rule, as a model that helps me 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 me with identifying and developing a succinct narrative around the crux of the problem.
A final note
While these mental models will help me solve business problems, I can not solely rely on them under all circumstances. For example, certain problems require focusing on correlation more than causation. Also, redundancy, which I strives to eliminate, is sometimes needed. Nevertheless, these models serve well as building blocks for structuring even the most complex business problems.
