As AI takes over additional tasks, we will increasingly focus our efforts on skills like complex problem-solving. This is one of the reasons problem-solving makes LinkedIn’s list of the most-in demand skills of 2024. The challenge with problem-solving is that it feels unique and turnkey. You solve every problem differently – or do you?

The Case for a Standardized Approach to Problem-Solving

The do-it-differently every time approach to problem-solving makes problem-solving difficult for individuals and teams. Without a standard approach like the ones we teach in our corporate program, you must think about how to solve the problem in addition to thinking about solving the problem. This also means you approach each problem differently, missing your opportunity to get up the experience curve on a single problem-solving approach.

But, you might say, if problem-solving is inherently about creativity and novelty, then wouldn’t using a standardized approach actually undermine our efforts? There are 2 types of problems:

1. Problems others have already solved
2. Problems no one has solved

In type 1 problems, analysis of others’ success is more important than creativity, while type 2 problems require creativity. However,  even when working on type 2 problems, creativity should not be subject to chance. Hoping an idea will come is not a reliable way to solve problems. Creative problem-solving requires a process to increase the likelihood of identifying a creative solution, which we teach here.

4-Step Process for Solving Problems

Many people jump directly to generating solutions when faced with a problem. Instead, follow these 4 steps:

1. Define the problem
2. Describe the desired outcome
3. Identify the cause
4. Generate solutions

We remember this as POCS: problem, outcome, cause, solution. Time spent getting clear on the problem, outcome, and cause helps get to solutions faster and helps produce stronger solutions.

Let’s review each of these in turn.

Define the Problem

At my first job, when I or fellow managers would propose recommendations for changes to make in our warehouse, our regional manager would ask, “What problem are you trying to solve?” Ideas can gain distance from the problems they were originally generated to solve if you aren’t clear on the problem. This can lead teams to waste resources implementing solutions that solve minor or no problems.

Start the POCS process by defining the problem. For example: Let’s imagine you are a small business owner and you’re bleeding cash each month for the last 3 months. Your problem definition is: We are losing money each month.

Describe the Desired Outcome

When we have a problem, we often assume the desired outcome is known because the problem is tangible and the outcome must be to remove the negative feeling associated with the problem.

We often think like this: “We’re losing money! Of course, the outcome is clear. We need to stop losing money.” However, this is not specific enough to determine the set of potential solutions. To use our example: Is the desired outcome to break even each month, to reduce our monthly loss, or to make money? And over what timeframe do we expect to achieve that outcome?

The desired outcome should be a measurable goal that has the following template: From X to Y in Z timeframe. This goal structure is borrowed from the Four Disciplines of Execution. In this case, let’s say that our desired outcomes is: from losing an average of $100,000/month to making in profit $150,000/month in 4 months.

By clearly defining a measurable goal, you create a clear test for your potential solutions: Does this solution enable me to achieve the desired outcome?

Identify the Cause

Problems exist on a cause-and-effect continuum where there are layers of causes beneath the problem and layers of effects (or symptoms) beyond it. Your problem definition determines where you are on that chain – what we call: your problem depth. With every problem, you can go to greater depths, exploring more and more layers of causes that come before it.

How do you unpack the layers of causes beneath your problem? You can use a simple tool popularized by Jeff Bezos at Amazon: 5 Whys. You begin to use 5 Whys by asking why your problem exists and offering an answer. For example:

Why are we losing money each month?

Because our expenses went up 15% in the last 3 months.

Then you ask why again: Why did our expenses go up 15% in the last 3 months?

Because we had to change to a new international supplier who must pay tariffs to import their products to us.

Why did we change to a new international supplier?

Because our old supplier refused to do business with us.

Why did our old supplier refuse to do business with us?

Because we weren’t paying them on time.

And you continue in this way until you’ve asked 5 why questions – or gotten to a depth that feels insightful and addressable. You know you’ve hit a helpful cause depth when you say to yourself: “Ah interesting. We can do something about that.”

Generate Solutions

Consider the difference in options for solutions when you know just the problem definition: We are losing money each month – and when you’ve identified the cause: We are losing money because we weren’t paying our former low-cost supplier on time.

In the first instance, you could think of hundreds of ideas and have little idea whether they would work. In the second, you have a much narrower set of options for solutions that feel practical and achievable.

The task of generating solutions then becomes coming up with ideas that address the cause and enable the achievement of the desired outcome.

What Comes After POCS

Once you generate a compelling solution, this becomes your hypothesis: your educated guess on what you can do to solve the problem. You’re not done.

If you want a robust, likely-to-succeed solution, you must then build out the logic and evidence behind your solution and run it through several tests. We teach how to build robust solutions and mentally test them in our corporate training programs and our online class for individuals.