Last week in my article on Design Thinking I mentioned that such thinking is focused on “wicked problems”, which I defined as “the intractable, complex-system challenges that require parallel iterations of both the ‘problem’ and the ‘solution’, until both become clearer at the same time (and sometimes once you find the ‘solution’ you realize your concept of the ‘problem’ was wrong)”.
A couple of readers picked up on the term and wanted to know if I had coined it, and more about such problems. The term was coined by Horst Rittel and Melvin Webber in 1973 to describe problems in public policy and planning that defy solution by analytical methods. Wicked problems, they said, have these ten characteristics:
The Cognexus Institute provides these examples of Wicked Problems meeting these criteria:
My list of the world’s ten most intractable problems all meet these criteria as well.
The people I have spoken with who deal routinely with such problems have stopped using the terminology that was traditionally applied to complicated but ‘tame’ problems: solution, analysis, cause. They even avoid using the term ‘problem’ because its connotation is something that has a solution. But the terms that are appropriate instead are awkward, because they hit home the impotence of those trying to tackle them: instead of solutions and problems they talk of “approaches to deal with or cope with” a “situation”. And instead of analysis and cause they use complex-system terminology like “pattern recognition” and “correlation”. It’s a humbling vernacular, and it’s not surprising so many have chosen to leave such ‘problems’ for others to ‘solve’, or to use fruitless, complicated-system tame-problem ‘solutions’ that appear to work for awhile, and blame their later failure on other factors.
So how should we “deal with” complex situations, when the current state is clearly unsatisfactory and suboptimal?
Let’s start by looking at three examples of what nature does in such situations. Dave Snowden has described how birds flying in a flock so gracefully are simply following three ‘simple rules’: they fly towards the centre of the flock, veer to avoid colliding with other birds, and match speed to the neighbouring birds in the flock as much as possible. How do they ‘know’ to do this? Instinct.
Second example: Geese follow a number of rules to determine breeding rights and territories. Only one breeding pair is allowed in each (large, well-sheltered) breeding area. Each breeding area is usually maintained unchanged from year to year. Only geese who migrated to the area the previous year are ‘eligible’ to be breeders. Until they are three years old, geese may only ‘play nest’ (the eggs, if laid at all, are not fertilized or incubated). Those who meet these criteria may vie for breeding rights, in a ritual that is usually more noise than fight, and is usually won by the eldest goose and gander which are healthy. The non-breeding geese then migrate further north to all-bachelor summering grounds. The goslings are immediately transfered to an open area (one where predators can be seen coming from far away). Several breeding pairs will meet at this area, and if there are fewer than about four goslings per adult, some of the adults will leave their newborns with the remaining adults and migrate to the northern summering grounds.
How does this complex series of behaviours occur with such predictability? In part it in instinctive, and in part it is evolutionary: Trial and error. If one ‘rule’ leads to better survival, the survivors will perpetuate that rule and teach it to the next generation.
Third example: In the winter, a certain number of the birds that summered in each area will hibernate, a certain number will migrate to a warmer climate, and a certain number will feed on what’s stored away or available all winter long. Birds rarely freeze to death. Somehow they just know how many should stay, how many should go, and how many should sleep. There is no hierarchy at work here, making the decision. The decision on what to do is made by each individual, and the collective wisdom is right.
Now let’s look at human complex situations. Chris Corrigan has been using one complex situation technique, Open Space Technology, very successfully, for a number of years, addressing issues like suicide among First Nations youths. The critical differentiators between this technique and more traditional business techniques are:
There are a number of organizations and journals researching how to cope with complex situations (sometimes called social complexity to differentiate from mathematical complexity). Most of them acknowledge the wisdom of the methods nature uses to deal with complexity, and the value of Open Space Technology. Snowden has developed an interesting model called ABIDE which calls for:
If you put all the principles highlighted in green above together you have what might be the start of a means of coping or dealing with Wicked Problems. Not a system or methodology, mind you — these concepts don’t apply in the brave new complex world — just a means, an approach. Some stuff that seems to work.
If you’re a manager, or a consultant, and this seems way too soft and imprecise for comfort, you’ll just have to learn to ‘deal’ with it. If you’re a fan of the approaches of Freakonomics or the Wisdom of Crowds, a complex approach to Wicked Problems is probably right up your alley.
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I would also recommend the lessons from Adam Kahane’s book, “Solving Tough Problems”.
I’d second that Harold.
Thanks guys — Kahane is referenced several times in Presence, so I’ve already added this to me ‘to read’ list.
I have posted a dissenting viewpoint on my blog. I am not a manager or a consultant, just a lowly engineer who also happens to be a root cause analyst… and this all does seem to lack the amount of rigor I would usually require (i.e., it is soft and imprecise). My way of ‘dealing’ with it was to write a rebuttal. Comments are welcome.
Here’s a direct link to my rebuttal article:Root Cause Analysis for Complex Systems?