Nine Project Management Fallacies: IV

Nan picked up the last chunk of cookie and ate it. Peter and Trish had long ago finished theirs, but Nan liked making cookies last. "The critical thinking fallacies were my favorites," she said. "I like learning how to think more clearly."

Peter sipped his coffee. "Mmm." He swallowed. "But how do we avoid those fallacies?"

Nan had an idea. "Maybe we should inspect our project plans, like we inspect components."

Trish was intrigued. "Yeah, and I know what I'd put at the top of the checklist."

"OK, I'll bite," said Peter. "What?"

Trish was ready. "The Nine Project Management Fallacies."

Not a bad idea. These last three fallacies (Part IV of a little catalog of the fallacies of project management) are errors of critical thinking. For Part III, see "Nine Project Management Fallacies: III," Point Lookout for December 28, 2005.

The Normative Fallacy

This fallacy holds that when we ask some people their opinions, and most of them agree, then they're correct. Usually we select people non-randomly, choosing those who will give us desirable answers, or those we can trust, or those of high rank.

Non-random polling might provide comfort, but it's hardly scientific, and it almost always leads to biased conclusions.

To get truly useful polling data, you must poll people randomly.

The Availability Heuristic

In risk management, we often estimate the probabilities of certain events. We're using the Availability Heuristic [Tversky 1973] when we estimate these probabilities by sensing the difficulty of imagining or understanding the string of events that lead to the risk.

For instance, when we ask people whether death resulting from being attacked by a shark is more or less likely than from being hit by falling airplane parts, they usually answer that death by shark attack is more likely. Actually, death from being hit by falling airplane parts is 30 times more likely, but people are fooled because it's easier to imagine shark attacks, which are more common.

Estimating probabilities is unlikely to produce reliable results. For this reason, the Availability Heuristic is usually considered an example of a cognitive bias. Use real data, or use huge error bars.

The Grandiosity Fallacy

Confronting a problem, we sometimes address a generalization of the problem instead, hoping to solve a host of similar problems, and thereby solving the original problem almost "for free." Rarely does the reality match the wish.

Grandiosity usually generates two kinds of trouble. First, it's often more expensive and time-consuming than originally estimated. Second, the people of the organization rarely want the general solution. If they did, they probably would have sought it in the first place.

Sometimes customers don't know the value of the general solution, and telling them about it might produce a better outcome. But usually they want only what they asked for. Work with them on that first.

Track the incidence of these nine fallacies in your organization. Use them to inspect project plans. Probably your projects will have fewer surprises, or at least you'll be just a little less likely to be hit by falling airplane parts. First in this series   Top    Next Issue

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For more on cognitive biases, see "The Focusing Illusion in Organizations," Point Lookout for January 19, 2011.

Footnotes

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Coming January 27: Cost Concerns: Comparisons

When we assess the costs of different options for solving a problem, we must take care not to commit a variety of errors in approach. These errors can lead to flawed decisions. One activity at risk for error is comparing the costs of two options. Available here and by RSS on January 27.

And on February 3: Cost Concerns: Bias

When we consider the costs of problem solutions too early in the problem-solving process, the results of comparing alternatives might be unreliable. Deferring cost concerns until we fully understand the problem can yield more options and better decisions. Available here and by RSS on February 3.

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