You and your team have just solved a problem. It was difficult. It took some creative thinking. The solution now in place, forward progress resumes — for a while. Suddenly, a new problem appears. Progress halts, and you're back in deep yogurt.
Ice on the launch pad on January 28, 1986, the day of the last Challenger Launch (STS-51-L). The unusually cold weather was well beyond the tolerances for which the rubber seals of the solid rocket boosters were approved, and it most likely caused the O-ring failure. In meetings on the night before the launch, Morton Thiokol engineers and engineering managers confronted the problem. One of the candidate solutions was to recommend that the launch be scrubbed. Another was to recommend launch despite the weather. Politics, budget and schedule undoubtedly played roles in their decision. Nevertheless, it would be a mistake to view that decision as an aberration. NASA, as an organization, was seriously flawed at the time, and had made other decisions of equally questionable merit. See, for example, Howard S. Schwartz, Narcissistic Process and Corporate Decay, New York University Press, 1992. (Order from Amazon.com) Photo by Michael Hahn, courtesy U.S. National Aeronautics and Space Administration.
Investigating what happened — and that can take time — you discover that at least some part of this second problem is traceable to the solution you found for the first problem.
It's a pattern so familiar that we have a name for it: "unintended consequences." The term arose in the context of economics, but the concept is so useful that it has been applied in politics, game design, engineering — everywhere.
In problem solving, we can use the concept to help limit the risk that a solution to one problem creates a new one.
Probably there are numerous ways for solutions to create new problems, but here are a few of those more common in my own experience and the experiences of my clients.
- Missing knowledge or incorrect knowledge
- We didn't know what we needed to know to get it right the first time, or some of what we "knew" was wrong.
- Test what you do know for completeness and correctness. How do you know what you know?
- Dogma, politics, budget, and schedule
- We tend to be biased in favor of candidate solutions that are consistent with our cherished beliefs, or which satisfy political, budgetary, or schedule constraints; we tend to eliminate from consideration, prematurely, those that do not. And sometimes, when these factors get in the way, we don't even see some workable solutions.
- What are the dogma, political, budgetary, or schedule factors affecting your problem? How biased are you?
- Dirty work
- We tend to be biased in favor of
candidate solutions that are consistent
with our cherished beliefs or with
external organizational constraints - When the full solution requires that we grapple with parts of the problem that we find distasteful, dull, or pedestrian, we can be so averse to that part of it that we do a bad job of it.
- What part of what you need to do is distasteful or low status work?
- Subtlety and difficulty
- Even when we have access to all the information we need, the problem can be difficult to solve properly. A solid solution might require seeing the world from perspectives with which we have little experience.
- Get fresh eyes. Talk to people who have the perspective you need.
- Illusory similarity
- Sometimes we notice similarities between the problem at hand and problems previously solved. Then, without stopping to prove that they are similar enough, we apply methods that worked in the past.
- Look for proof that this problem is close enough to the problem previously solved. If you can't find proof, ask whether the differences really matter.
If you extend this list for your problem space, beware the unintended consequence of overconfidence. However complete your list becomes, unintended consequences might still emerge. 
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Related articles
More articles on Problem Solving and Creativity:
Forward Backtracking- The nastiest part about solving complex problems isn't their complexity. It's the feeling of being overwhelmed
when we realize we haven't a clue about how to get from where we are to where we need to be. Here's
one way to get a clue.
Rationalizing Creativity at Work: II- Creative thinking at work can be nurtured or encouraged, but not forced or compelled. Leaders who try
to compel creativity because of very real financial and schedule pressures rarely get the results they
seek. Here are examples of tactics people use in mostly-futile attempts to compel creativity.
Newtonian Blind Alleys: II- Some of our decisions don't turn out well. The nature of our errors does vary, but a common class of
errors is due to applying concepts from physics originated by Isaac Newton. One of these is the concept
of spectrum.
What Are the Chances?- When estimating the probabilities of success of different strategies, we must often estimate the probability
of multiple events occurring. People make a common mistake when forming such estimates. They assume
that events are independent when they are not.
Goodhart's Law and Gaming the Metrics- Goodhart's Law is an observation about managing by metrics. When we make known the metrics' goals, we
risk collapse of the metrics, in part because people try to "game" the metrics by shading
or manufacturing the data to produce the goal result.
See also Problem Solving and Creativity for more related articles.
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