7 Pitfalls to Problem Solving

I was in Texas recently and served as a witness to a traffic accident on one of the busy highway outlet roads.  A man was turning into the intersection and ran into a pickup truck hauling a horse trailer. Unfortunately, there was a horse in the trailer at the time, and the carrier was overturned.  Traffic was building up quickly on both sides.

An officer arrived at the scene and quickly surmised that the horse had broken its leg.  Seeing no other alternatives for the animal, the officer pulled out his gun and shot it.  We all grew very quiet.

Then, turning his attention to the man in the other vehicle, he asked: “So… are you OK?”

At work, we all have to solve problems on a regular basis.  It seems like once one is resolved, another few immediately take its place.  At some point early in my career I came to the realization that none of my schoolwork had prepared me for solving ambiguous, thorny issues. This sort of problem solving is a new skill most of us have to pick up- and is arguably more important than anything taught in our English, math, science or social studies classes.  Once I hit “the real world”, there was little reason for me to spend any more time learning things that didn’t help me with my number one objective: to solve business problems (and stay employed.) Through my journey from employee, to consultant, and then to business owner, I learned how consulting firms operate, how they think and what they teach when it comes to solving problems. Much of this via live experience and trial and error.  In other words, I learned the hard way.

Below are 7 common pitfalls to problem solving that I found most valuable not to do. How many of these do you recognize?

  1. Not thinking 80/20- The Pareto Principle basically says that 80% of the outcome is often caused by 20% of the potential causes. Put another way, 80% of the benefit can be captured with less than 20% of the effort. Which of the contributing factors is causing the most impact? Target those.
  2. Assuming you understand the objective/ starting with a bad problem statement– Let’s assume your company has asked you to improve profit.  But what you assume they mean is cutting costs.  These are different objectives, albeit related. In most cases, cutting costs too much will hurt overall profitability.  Problem statements should have two key ingredients, if nothing else: an object to improve and the measured performance “deviation”.
  3. Overlooking what the problem is NOT– Being willing and able to eliminate key areas of analysis that do not pertain to the problem is key to isolating the root cause. For example, if your hypothesis depends on raw material costs having increased but the data says costs have decreased, you need to tweak your hypothesis. The human mind is second to none in its ability to rationalize, however, and we have a strong urge to make things fit (even when they don’t.) Another everyday example: the power to your house goes out, yet the rest of your neighborhood is brightly illuminated.  What potential cause does this one fact eliminate?
  4. Wasting valuable time with unneeded analysis– Most companies outside of Google or Apple do not have unlimited resources to work on things, so conducting all the analysis you want on a problem is not going to be a practical endeavor.  Therefore, prioritizing what data you do need is very important to solving the problem in a reasonable amount of time.  There’s a very well-known phrase called “boiling the ocean” that describes this notion well.  As the metaphor goes, there are two ways to get a cup of hot water: 1) Get one cup of water, put it on the stove and boil it and 2) Boil the entire ocean and scoop one cup of the boiling water. What key information is needed to solve the problem? Be as efficient as possible.
  5. Using the wrong mix of quantitative vs. qualitative questioning– Quantitative analysis deals with math and understanding numerical relationships. Qualitative analysis explains why the numbers are what they are.  You will need a healthy mix of both, probably at a ratio of 70:30. For example, quantitative analysis tells us our selling price erosion is the reason for shrinking revenues.  Qualitative analysis tells us it’s because we have a new competitor that is servicing the same market for less with an optimization technology. Too much reliance on either one of the analysis types will always give you an incomplete answer.
  6. Deploying the wrong framework- Starting with the wrong approach is akin to building an apartment complex on top of a house foundation: it just won’t fit and somewhere on down the line the structure will fall over.  Questions to ask yourself is: am I dealing with an actual unknown cause or do I need to make a decision on an action to take? If it is indeed a problem, is it a profitability issue or a strategic business situation (new market, acquisition, repositioning, etc.)? Or maybe the problem is a performance issue with an asset not running at the same level as before. It could be neither of these and more of a process improvement problem that involves variation control and 6 Sigma technologies.  Apply the right tool and the right answer is a lot more forthcoming.
  7. Forgetting to “destructively test” the potential root cause– Going back to the resource limits addressed in #4, if you have unlimited time and money, ignore this last rule.  For the rest of us, this easy trick will make a difference. Prior to launching into an experimental fix- but after you have a favorite root cause theory- mentally test how that root cause specifically accounts for the defect or deviation, how it explains when it occurred when it did, why it occurs where it does and if it explains the patterns that it leaves behind. If it can’t explain all of the known facts of the problem, then either your theory needs revising or the “facts” are not really facts.  This exercise is called destructive testing and is one big, logical time saver.

People love to solve problems. However, people will avoid problem solving situations when they are unsure of how to approach the issue. If we keep in mind the practical rules of problem solving, we shouldn’t shy away from any business puzzle.

Just don’t put the cart before the horse.