Seven Planning Pitfalls: III

In two previous posts, I examined four reasons why planning complex projects is so difficult. In the first of these two posts, I explored how we can be limited by our ability to imagine what we're planning, and by our access to knowledge of past failures. In the second post, I considered external influences. One set of external influences is associated with a group of cognitive biases known as priming effects. A second set of external influences includes fads, dogma, regulations, and traditions.

Continuing this exploration of difficulties encountered in planning complex projects, I turn now to internal causes of trouble, namely, patterns in the way we think when we're constructing plans.

Magical number 7

In one of most-cited papers in the entirety of the psychology literature, George Miller reported experimental results regarding numerical limits to human cognition. [Miller 1956] There are limitations to the number of "chunks" people can hold in short term memory. And there are limits to our ability to distinguish among a defined set of stimuli to govern a choice among a defined set of associated responses. These limits, coincidentally, appear to lie in the range of 7±2 items.

The effects of these limits on planning activities are both subtle and profound. For example, a widely believed maxim in the presentation architecture community is known as the 6x6 rule. It states that presentation slides should contain no more than six bullet points of not more than six words each. Although it is motivated by Miller's observations, experimental confirmation of its value has been elusive.

However, the limits Miller described are real. They can play a role in planning efforts for complex projects that have parallel efforts that number more than 7±2. For example, managing a project with 19 parallel streams of tasks would tend to become unwieldy because project managers might not be able to keep the various attributes of so many work streams in their minds.

The usual approach for dealing with this is to "chunk" the effort into pieces that are more manageable in number. Then if necessary, chunk each piece. This approach is usually called analysis and synthesis.

Some of what we attribute to "poor planning"
is perhaps better regarded as an inevitable
result of how humans thinkAnalysis and synthesis can be problematic, because the chunks sometimes interact with each other in unexpected ways, outside the descriptions we use for the synthesis.

Ambiguity effect

The ambiguity effect is a cognitive bias that affects how we make decisions under uncertainty. [Ellsberg 1961] When choosing among options that have favorable outcomes, we tend to favor those options for which the outcome is more certain, even if less favorable. And we tend to avoid options for which the probability of a given favorable outcome is unknown, even if all possible outcomes of that option are favorable.

When devising plans for projects, the ambiguity effect can be costly indeed. For example, when considering a novel approach that offers great savings in cost and schedule, we might compare it unfavorably to a more familiar approach that's slower and more costly. The ambiguity effect causes us to favor the conventional approach more than might be justified by the uncertainties of using an unconventional approach for the first time.

Mitigating the ambiguity effect requires careful estimation and objective computations.

The planning fallacy

In a 1977 report, Daniel Kahneman and Amos Tversky identify a particular cognitive bias, the planning fallacy, which afflicts planners. [Kahneman 1977] [Kahneman 1979] They discuss two types of information used by planners. Singular information is specific to the project at hand; distributional information is drawn from similar past efforts. The planning fallacy is the tendency of planners to pay too little attention to distributional information and too much attention to singular information, even when the singular information is scanty or questionable. Planners tend to underestimate cost and schedule by failing to harvest lessons from the distributional information, which is inherently more diverse and reliable than singular information.

The tendency to attend too little to distributional information afflicts us all as people, but it can afflict organizations as well. For example, many organizations conduct retrospectives or "lessons learned" exercises in connection with projects. But the information they collect, valuable though it might be to subsequent projects, isn't always archived in ways that facilitate its use by the leaders of those subsequent projects. It might be scattered, or stored within the project that generated it, rather than collected with other similar volumes into an organized library. In some organizations, it is actually classified and its use is restricted.

Such practices intensify the effects of the planning fallacy.

Knowing these patterns, and others like them, provides enormous advantages to planners. They can check their plans for these effects, and when they find indications of their presence, they can revise those plans to mitigate the effects. Of course, you have to plan on taking these steps from the outset. And that plan is itself subject to these same effects. First in this series   Top    Next Issue

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Footnotes

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Related articles

More articles on Cognitive Biases at Work:

Perfectionism and Avoidance

Avoiding tasks we regard as unpleasant, boring, or intimidating is a pattern known as procrastination. Perfectionism is another pattern. The interplay between the two makes intervention a bit tricky.

Neglect of Probability

Neglect of Probability is a cognitive bias that leads to poor decisions. The risk of poor decisions is elevated when we must select an option from a set in which some have outstandingly preferable possible outcomes with low probabilities of occurring.

Cognitive Biases at Work

Cognitive biases can lead us to misunderstand situations, overlook options, and make decisions we regret. The patterns of thinking that lead to cognitive biases provide speed and economy advantages, but we must manage the risks that come along with them.

Motivated Reasoning

When we prefer a certain outcome of a decision process, we risk falling into a pattern of motivated reasoning. That can cause us to gather data and construct arguments that erroneously lead to the outcome we prefer, often outside our awareness. And it can happen even when the outcome we prefer is known to threaten our safety and security.

Seven More Planning Pitfalls: II

Planning teams, like all teams, are susceptible to several patterns of interaction that can lead to counter-productive results. Three of these most relevant to planners are False Consensus, Groupthink, and Shared Information Bias.

See also Cognitive Biases at Work and Project Management for more related articles.

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Some meeting agendas include exploring issues related to upcoming decisions. Although we believe that these discussions are purely rational and lead to rational decisions, some contributions evoke emotional responses. Here are five examples. Available here and by RSS on May 12.

And on May 19: Pre-Decision Discussions: Reasoning

When we meet to resolve issues related to upcoming decisions, we sometimes rely on reasoning to help find solutions. Contributions to these discussions generally use mixtures of deductive, inductive, and abductive reasoning. How do they differ, and what are their strengths and risks? Available here and by RSS on May 19.

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