As we've seen, collaborative problem solving does have risks — new ideas might be crushed prematurely, judges might be intimidated, and more. Risks continue when we move to experimentation or prototyping. Let's now examine how to avoid some of the troubles that can arise during experimentation.
- Design experiments to facilitate learning
- Most experimental efforts are designed merely to determine whether an idea "can work," but that isn't enough. We need to know not only whether the idea can work, but also what its weaknesses are, how severe they are, and how we can address them.
- Regard each experiment as an exploration of the solution and how it interacts with a hostile environment. Try to determine the consequences of its misbehavior, and the cost of eliminating that misbehavior.
- Capture learning from experiments
- Experiments — especially well-designed experiments — create knowledge. Since experiments cost time and resources, we must be prepared to capture all the knowledge they create. We sometimes adjust experiments on the fly in response to what we're learning. Although these adjustments can be helpful if the adjusted experiment is still well designed, that isn't always the case. Sometimes the result of adjusting experiments on the fly is a muddled mess from which we can learn little, if anything at all.
- When conducting experiments to test newborn ideas, provide a means of capturing and storing generated ideas in such a way that they don't interfere with the ongoing experiment. When the new learning does demand immediate adjustment of the current experiments, take care to adjust them in ways that can still produce useful experimental results. That care takes time and effort, which means schedule and budget.
- Protect experiments from transition to production
- One of the most common tales of tragedy is that of the prototype that got sold to a customer. The interference of production with experimentation creates two classes of problems. First, because the prototype was intended as an experiment, it often has attributes and structures that make it unreliable and expensive to maintain or enhance. Second, if the pattern of interference of production with experimentation has occurred before, the experimenters learned long ago that they must take steps to make the prototypes more durable than ordinary experiments would have to be.
- The resultOne of the most common
tales of tragedy is that of
the prototype that got
sold to a customer is that experimentation is more expensive than it needs to be, and maintaining or enhancing fielded products that are former prototypes is more expensive than it needs to be. In short, the result is neither a good prototype nor a good product.
- When conducting experiments to test newborn ideas, conduct experiments. Insulate the experiments from any pressure to convert them into products. Your experiments will be cheaper, and when the time comes to actually build a product, it will be built right.
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More articles on Problem Solving and Creativity:
- Problem Defining and Problem Solving
- Sometimes problem-solving sessions are difficult because we get started solving a problem before we
know what problem we're solving. Understanding the connection between stakeholders, problem solving,
and problem defining can reduce conflict and produce better solutions.
- Rationalizing Creativity at Work: I
- Much of the work of modern organizations requires creative thinking. But financial and schedule pressures
can cause us to adopt processes that unexpectedly and paradoxically suppress creativity, thereby increasing
costs and stretching schedules. What are the properties of effective approaches?
- 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.
- Solving the Problem of Solving Problems
- Problem solving is sometimes difficult when our biases interfere with generating candidate solutions,
or with evaluating candidates we already have. Here are some suggestions for dealing with these biases.
- Tackling Hard Problems: I
- Hard problems need not be big problems. Even when they're small, they can halt progress on any project.
Here's Part I of an approach to working on hard problems by breaking them down into smaller steps.
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