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 issue in this series   Top    Next Issue

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Footnotes

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More articles on Cognitive Biases at Work:

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Decision makers in modern organizations commonly demand briefings in the form of bullet points or a series of series of bullet points. But this form of presentation has limited value for complex decisions. We need something more. We actually need to think.

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When we say that people have "clout" we mean that they have more organizational power or social influence than most others do. But when people with clout try to use it in realms beyond those in which they've earned it, trouble looms.

Lessons Not Learned: II

The planning fallacy is a cognitive bias that causes us to underestimate the cost and effort involved in projects large and small. Efforts to limit its effects are more effective when they're guided by interactions with other cognitive biases.

Additive Bias…or Not: I

When we alter existing systems to enhance them, we tend to favor adding components even when subtracting might be better. This effect has been attributed to a cognitive bias known as additive bias. But other forces more important might be afoot.

See also Cognitive Biases at Work for more related articles.

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