Point Lookout: a free weekly publication of Chaco Canyon Consulting
Volume 21, Issue 4;   January 27, 2021: Cost Concerns: Comparisons

Cost Concerns: Comparisons

by

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.
stacks of gold coins

Problem solving in organizations is usually a collaborative exercise. It begins with assembling a group of people representing what we believe will be the necessary fields of knowledge and areas of responsibility. That group then follows one of the many available problem-solving frameworks, possibly flipping between two or three of them. And they employ any of the various problem-solving tools that fit for them and that might apply to the problem at hand.

Cost is one attribute of any solution that problem-solving groups must consider. Although cost concerns are real, and although we must consider cost, my own experience observing groups solving problems suggests that cost concerns often arise too early. Indeed, cost concerns can arise so early that they stifle the problem-solving process. Premature concern with costs might even lead groups to abandon their problem-solving effort prematurely.

But even when we can defer cost considerations until after we develop several potential problem solutions, our approach to cost comparison can lead to biased assessments of the relative desirability of our solution options.

In this post and the next, I examine a collection of ways our treatment of cost concerns can bias our search for solutions to problems. I begin with an examination of how using cost comparisons can introduce bias in our choice of solution options.

In pursuit of that objective, it's useful to begin by assuming that the problem-solving team has successfully deferred cost considerations, and it has developed several possible solutions. As part of their deliberations, they now want to compare the costs of the various options. They believe, in my view correctly, that comparing the costs of the available options can provide information useful for selecting one of them, or for guiding further investigation.

Still, comparing the costs of different solutions can yield biased and misleading results. Here are four traps that await problem-solving teams as they compare costs of options for solving their problem.

Failing to assess the cost of the status quo
One source of bias is the failure to assess the true cost of the status quo. The status quo — that is, the current situation without a solution to the problem — is always an option. When we don't recognize the true costs of deferring solving the problem, the effect is similar to the effect of assuming that doing nothing is free. Because Zero is almost always lower than the cost of any of the actual problem solution options, the assumption that doing nothing is free causes the status quo to seem to be the lowest-cost option. In this way, failure to assess the true cost of the status quo is one means of excluding all potential problem solutions.
If your organization has a problem of long standing that the organization seems to lack the will to solve, it's possible that people are failing to recognize the true cost of doing nothing.
Emphasizing direct costs over indirect costs
A second source of bias in cost estimation is excessive emphasis on direct costs to the exclusion of indirect costs. For example, suppose we estimate the cost of deploying Solution A as including only its direct costs — the cost of creating Solution A. If we take this approach, we might be ignoring the costs of disruptions of operations that occur when we actually deploy Solution A. If those disruptions depress revenue, for example, the amount of that lost revenue must be included as a cost of Solution A. A second class of indirect costs, often overlooked, is the net value of the opportunities that we could have exploited if we had applied elsewhere the resources that we used to create and deploy Solution A. Fair comparisons of the various options must include both direct and indirect costs.
Insufficient Comparing the costs of the available options
can be useful for selecting one of them, or
for guiding further investigation. But
comparing costs can yield biased
and misleading results
attention to indirect costs can lead to a pattern of choosing what seem to be lower-cost solutions that ultimately lead to lost opportunities or messy situations. Poorly chosen solutions eventually consume significant portions of organizational resources. If this is a familiar pattern, investigate past proposals to determine how well they accounted for indirect costs.
Comparing total costs while ignoring recognition dates
A very common and perhaps the simplest way to compare the respective costs of available options is to compare total cost. But perhaps as important as total costs are recognition dates of various cost components. For example, an option whose total costs are higher, but whose costs are recognized in Tax Year A might have far less impact on the organization than an option that has lower total costs recognized in Tax Year B.
Other factors can be even more important. For example, the timing of the need for certain kinds of resources can make a more costly option more desirable, because of scheduling issues for necessary resources.
Basing decisions on comparisons of total costs can be very misleading. Comparisons that account for the timing of cost recognition and resource availability can become very complex and counter-intuitive. Specialized expertise is required.
Being misled by the hyperbolic discounting cognitive bias
As I've noted in a previous post, a cognitive bias called hyperbolic discounting causes us to undervalue future benefits relative to present costs [Laibson 1997] It can also affect how we compare benefits of different solutions, when those benefits become available at different times. But the more insidious effect of this cognitive bias in this context is how it affects cost comparisons.
Assume for a moment that we actually succeed in avoiding the trap of comparing total costs while ignoring cost recognition dates. That is, we actually try to account for the recognition dates of the cost elements when comparing problem solutions. The hyperbolic discounting cognitive bias might then cause us to overvalue (that is, to perceive as more undesirable) cost components that are recognized closer to the present, as compared to cost components that are recognized at more distant points in the future. Said differently, we tend to be overly attracted to cost profiles in which the costs occur later. This preference is stronger than could be justified by rational discounting. The result is that because of hyperbolic discounting, outside our awareness, we push off into the distant future issues that would be less costly to address in the present or nearer future.
Another mechanism also contributes to this organizational bias in favor of cost deferment. Some decision makers are so ruthless that they're willing to make or support decisions that greatly expand the organization's technical debt, because they know that the harm caused will become evident only long after they've departed for their next position. I call this "surfing the debt tsunami." Sadly, the behavior isn't restricted to issues related to technical debt. Ruthless decision makers can employ this tactic in the context of any problem solution that produces long-term costs significantly greater than its near-term costs.

Cost comparison is one part of the problem-solving activity that is vulnerable to risk of error. Next time, I examine why problems that require large-scale solutions are especially vulnerable to the risk of premature concern with cost.  Cost Concerns: Scale Next issue in this series  Go to top Top  Next issue: Cost Concerns: Scale  Next Issue

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Footnotes

Comprehensive list of all citations from all editions of Point Lookout
[Laibson 1997]
David Laibson. "Golden eggs and hyperbolic discounting," Quarterly Journal of Economics 112:2 (1997), 443-477. Available here, Retrieved 25 October 2018. Back

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