Wicked

It's been a few years since my wife and I went to the theater.  When we lived in Cincinnati, we had season tickets to Broadway in Cincinnati.  Our original plan was to continue our once-a-month tradition and purchase season tickets to the theater in our new city.  Well, then COVID-19 happened and most of the shows were canceled.  I suppose that we've been procrastinating.  It's probably time to start going back to the theater, as one of our favorite shows is coming to town soon.  We've se the show "Wicked" a few times, even once in New York City.

I'm reminded (sorry, my brain just works that way) of something that Keith Grint has called a "wicked problem" (as opposed to a "tame problem").  I've posted about "wicked problems" at least once before. Simply stated, "wicked problems" are both complicated and complex and probably have never occurred before.  The solutions to "Wicked" problems aren't readily apparent, and they may be as complicated and complex as the problem itself.  

"Wicked problems" are particularly prone to what Dietrich Dörner (see my last two posts) calls "the logic of failure".  He recommends the following sequence of steps (an algorithm, if you will) for attacking complex problems.  I would suggest that this sequence could help solve wicked problems too.

Dörner suggests that the first step is to set clear, unambiguous goals.  I like using SMART goals - goals should be specific, measurable, actionable, realistic and relevant, and time-bound.  While Dörner doesn't necessarily state that we should use SMART goals, he does caution against focusing on general goals.  If we do not state our goals clearly, we tend to fall into the trap of what he calls a "repair shop" mentality - we try to fix whatever problems that we can find.  

It's important to delineate all the goals, including what Dörner calls "implicit goals" (goals that are just as important, but perhaps not clearly stated).  For example, "Stop insects from eating crops" is an explicit goal (but of course, not a very SMART one), but by accomplishing that goal, we don't want to destroy the local ecosystem (the implicit goal).  We usually do not take into account these implicit goals, and we may not even know they are a goal.  Dörner uses another example.  For someone who is already healthy, "maintaining health" would be an implicit goal - not clearly stated, but perhaps just as important and relevant.

The second step in Dörner's approach is to gather information and analyze data.  Again, while he does not clearly state it in these terms, he does recommend that we should avoid oversimplifying the problem (the High Reliability Organization principle of "Reluctance to Simplify").  Collecting too much data is just as problematic as not collecting enough.  I like what Jeff Bezos calls the "70% rule" - make a decision when you have about 70% of the information that you need.

Next, Dörner says that we should make predictions and extrapolate from the data that we collected in step 2.  In other words, make a plan and then act on it.  Dörner cautions against something that Carl von Clausewitz called "methodism" (more on this in a future post), that tendency we all have to restrict our actions to the ones that have worked well for us in the past.  Dörner writes, "To be successful, a planner must know when to follow established practice and when to strike out in a new direction."

Finally, after we've executed our plan, Dörner says we should review the results that we achieved and make any necessary changes to our plan.  Several of you may noticed that Dörner's approach is very similar to the PDSA cycle (Plan-Do-Study-Act) used in quality improvement today.  That makes a lot of sense to me - PDSA cycles are often used to tackle complex or wicked problems.

Since I started with the Broadway musical "Wicked", I will end with a quote from the character Elphaba ("The Wicked Witch of the West").  She said, "Some things I cannot change.  But 'til I try, I'll never know."  Complex or wicked problems are like that too.  It would be very easy to say that they are just to hard to tackle, but until we try, we will never know for sure.