The Plausibility Trap

Have you ever accepted a perfectly good explanation for an issue or solution to a problem and then learned later that it was wrong or less than best? You may have stepped in a Plausibility Trap.

You might be looking for the cause of a problem, the way to fix a problem, or an inconsistency that discredits a book. You find an explanation or solution and commit to it. Later, the solution does not fix the problem. Or somebody offers a different explanation that's infuriating because you cannot find any flaws with it and it makes your explanation sound stupid (even though you just know you're right). 

Plausibility Traps Everywhere

Root Cause Analysis helps overcome cognitive bias and plausibility traps by teaching you to look at different facets of a problem before making any decisions. We might want to blame the input to a process, but the environment, another input to the process, the purpose itself, a detailed step in the process, or even a recipient of the product might contribute to the problem. 

We get rushed, however. We fail to discipline ourselves, and seize upon the first solution we think of. We don't weigh possible causes against each other or look into the cause-behind-the cause. 

Tools for Avoiding the Traps

The most critical attribute in decision-making the ability to balance openness to more evidence and possibilities against the pressure to make the decision.

One solution is to use a graphical method such as mind-mapping or fishbone ("Ishikawa") diagrams. They force us to think about different types of influences, and then for each type, what secondary influences could go wrong. 

You can start with a standard list or create your own. For example, manufacturing has the Eight Ms:

• Machine (Technology)
• Material
• Measurement (Inspection)
• Management (Money power)
• Maintenance
• Mother nature (Environment)
• Man power (Brain work)
• Method (Process)

Business Management has PEST Analysis:

• Political
• Economic 
• Social 
• Technological

Each of category above has multiple sub-categories that are outside the scope of this article.

Another tool is the Five Whys. Get an answer to Why? and then ask Why? again. And again. And gain and again, until you arrive at a cause that is not under your control. "Five Whys" is the Americanized version of a Japanese expression, why-why. You go as far back as the first cause that is not under your control, and then respond to the first step that is under your control. 

The beauty of Five Whys is that things that go wrong tend to cause multiple problems. So if you prevent or mitigate that root cause, may you fix other problems you didn't eve know about.

Once you've identified several solutions (or causes, explanations, or steps), you may find that more than one are needed. Here's where you evaluate how likely each solution will help and how much it will help, and then choose not just one solution, but as many as it takes to address most of the challenge. Here, tools such as decision trees, the 80/20 rule, Pareto diagrams, and Tornado diagrams can be useful. 

Examples

Here are two examples from outside business where the people fall into plausibility traps. 

1. The news carries an account of a police officer shooting a suspect. One group leaps to the conclusion that the incident exemplified a racist America and incites people to riot. Later, it turns out that none of the objective facts supported the first group's conclusion. 

2. Somebody reads two accounts of an event or policy in a holy book and concludes that the differences prove the event never happened. Another person considers several ways the two accounts might be reconciled, and one of those ways rationalizes all discrepancies. The first person fell into the plausibility trap by accepting the first explanation that came to mind instead of searching for ways to merge the accounts. The second person realizes that, if the two accounts can be rationalized, then you cannot say they are untrue.

We don't want to fall into "analysis paralysis," but we don't want to fall into the trap of  simplistically accepting the first "plausible" explanation or solution, either. The more important the issue, the more facets and layers you should consider.


Copyright 2018 Richard Wheeler