To repair complex systems, many resort to "random twiddling and part replacement" (RTAPR) when they're under time and resource constraints. Sadly, RTAPR doesn't work very well. For example, consider a system that has six commercial off-the-shelf components. Let's suppose that it isn't working right. We decide to replace Module 2, which produces no change — the system continues to misbehave. Some might conclude that this proves that Module 2 is OK, but that conclusion might be mistaken. Suppose that the problem lies in the firmware of Module 2, which controls how it operates on the data it receives from Module 1. Since both of our Module 2 boxes contained the same firmware, the system behavior didn't change when we made the swap. A conclusion that Module 2 was not involved in the fault would therefore be incorrect.
A more careful approach can work better than RTAPR. Here are some guidelines that form the basis of what is usually called the scientific method.
- Perform no random experiments
- Random experiments, especially those involving system configuration changes, are unlikely to produce new knowledge. The more complicated the system, the less productive are random experiments.
- Keep excellent records
- Record the Random experiments, especially if
they involve system configuration
changes, are unlikely to
produce new knowledgedetails of all experiments and results. Typically, you won't refer to these notes until you're completely stumped, but that happens with alarming frequency for complex systems. So write the notes so as to make them clear in that kind of desperate situation.
- Try to replicate unwanted behavior
- (a) If the unwanted behavior is reliably repeatable, observe the results of making a minimal change to the system. Any change in behavior can be revealing. (b) If the unwanted behavior isn't repeatable, try to find a system configuration that makes it repeatable, and then go to (a). In all such experiments, controlling the system's containing environment is essential.
- Base all attempts on hypotheses
- Because the input configuration for a complicated system is also complicated, proving that complicated systems work for all required inputs is difficult. Hypotheses about why the system isn't working are equally difficult to prove. Hypotheses can more readily be disproven than proven.
- Therefore, have a testable hypothesis in mind whenever you change the system configuration. Testable hypotheses are of this form (for example): "The fault might be A. If experiment B produces behavior C, then the fault cannot be A." Repeating this process gradually eliminates possibilities until only the truth remains.
- Fail forward
- Devise hypotheses and experiments that cause your investigation to "fail forward." That is, favor experiments that produce useful knowledge whatever the outcome of the experiment. If you make a change and the system starts working, that should help explain what was wrong. And if that same change causes some other result, that, too, should be enlightening information.
Adhering to these guidelines can be difficult, especially under pressure. If deviation is required, make note of it, and note how deviations affect your conclusions. First in this series Top Next Issue
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More articles on Problem Solving and Creativity:
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- Serendipity in project management is rare, in part, because we're under too much pressure to see it.
If we can reduce the pressure, wonderful things happen.
- Dealing with Deadlock
- At times it seems that nothing works. Whenever we try to get moving, we encounter obstacles. If we try
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- Assumptions and the Johari Window: I
- The roots of both creative and destructive conflict can often be traced to differing assumptions of
the parties to the conflict. Working out these differences is a lot easier when we know what everyone's
- Wishful Thinking and Perception: II
- Continuing our exploration of causes of wishful thinking and what we can do about it, here's Part II
of a little catalog of ways our preferences and wishes affect our perceptions.
- Wishful Significance: II
- When we're beset by seemingly unresolvable problems, we sometimes conclude that "wishful thinking"
was the cause. Wishful thinking can result from errors in assessing the significance of our observations.
Here's a second group of causes of erroneous assessment of significance.
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