Some organizations have made real progress in controlling and retiring their accumulated technical debt. Many others have struggled, finding the goal elusive at best. And still others have failed even to make a start on the project. It's just too much of a challenge. Although there has been some progress, the goal of retiring existing technical debt and controlling further accumulation seems to be able to resist most technical approaches.
The fundamental question could be this: Why do we have such difficulty allocating resources to the twin problems of retiring our existing technical debt, and managing new technical debt formation? Perhaps the roots of these problems lie not within the technologies we use, but within the users of the technologies — within us.
If some of the causes of our resource allocation problems have roots in human psychology, then the field of behavioral economics might have some valuable lessons that could apply. And mental accounting is one fruitful line of research that could be relevant.
As a preliminary, let's consider a specific definition of technical debt. Your definition might differ, but here's mine:
Technical debt is any technological element that contributes, through its existence or through its absence, to lower productivity or to a higher probability of defects during development, maintenance, or enhancement efforts, or which depresses velocity in some other way.
Technical debt is therefore something we would like to revise, repair, replace, rewrite, create, or re-engineer for sound engineering reasons. It can be found in — or it can be missing from — software, hardware, processes, procedures, practices, or any associated artifact, acquired by the enterprise or created within it.
With that background, let's now turn to what the research in mental accounting has to offer.
Research in mental accounting has developed a number of models of behavior relative to resource allocation and acquisition. Although the work is focused almost exclusively on consumer behavior, the analogies to organizational resource management are clear enough to support conjectures in special cases such as technical debt management.
Setting aside the models of mental accounting, conventional economic theory predicts that organizational decision makers will always behave rationally. They'll make decisions that maximize the present value of resource streams, and minimize the present value of expense streams. That decision makers don't behave in this way is clear, especially in the field of technical debt management. So a natural question arises: Can we amend the principles of economics to obtain predictions that more closely resemble actual decision maker behavior?
Mental accounting offers a number of such possible amendments. In this post, I explore just two that happen to be related: pain of paying, and the credit card effect.
Pain of paying
Pain of Research in mental accounting has developed
a number of models of behavior relative to
resource allocation and acquisitionpaying is the negative emotional experience that occurs when we actually pay for goods or services. Researchers have found that consumers who experience a higher level of pain of paying tend to carry lower levels of debt than do consumers who experience lower levels of pain of paying. [Rick 2008]
It's reasonable to suppose that knowledge of the financial consequences of acquiring new technical debt would cause decision-makers to experience the analog of consumer's pain of paying. Applying the concept of pain of paying to organizational technical debt, we can surmise that organizations would tend to carry lower levels of technical debt if they accurately estimate the effort required to avoid incurring new technical debt. Similarly, they might carry lower levels of technical debt if they more accurately estimate the decreases in productivity that result from carrying technical debt.
The credit card effect
Researchers in mental accounting have observed what has come to be called the credit card effect. [Prelec 2001] They have observed that consumers are more willing to pay for a good or service if they can pay for it using a credit card rather than cash. They have also found that restaurant tips are larger when the consumer pays using a credit card.
Experimental evidence suggests that the credit card effect is due to transaction decoupling — a temporal separation between the acquisition event and the payment event. This separation enables enjoyment of the good as if it were free in the context of the acquisition event. In the context of the payment event, the pain of payment can be somewhat alleviated by the passage of time, and the fact that the payment for the good might be only a small part of the balance due, which can include payment for many other acquisitions.
I suspect that this effect is part of the reason why retailers are so happy to offer gift cards. Gift cards offer even greater separation between the acquisition event and the payment event — not only temporal, but also personal.
In the organizational context, technical debt offers something analogous to consumer credit card debt. Payment for goods acquired by incurring technical debt might never happen unless the organization takes a decision to retire the debt. Moreover, the "interest" payments on technical debt occur, for the most part, in the form of depressed productivity and schedule slippage. Because neither of these effects appear anywhere in the organizational chart of accounts, decision makers don't experience a pain of payment for interest charges on technical debt.
To make progress in controlling technical debt, we might consider finding ways to cause decision makers to experience the pain of paying. And it might be helpful to make the carrying charges for technical debt more visible. Technical debt will likely remain difficult to manage as long as the penalties for incurring technical debt are invisible or nil. Top Next Issue
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More articles on Cognitive Biases at Work:
- Wishful Significance: I
- When things don't work out, and we investigate why, we sometimes attribute our misfortune to "wishful
thinking." In this part of our exploration of wishful thinking we examine how we arrive at mistaken
assessments of the significance of what we see, hear, or learn.
- The Rhyme-as-Reason Effect
- When we speak or write, the phrases we use have both form and meaning. Although we usually think of
form and meaning as distinct, humans tend to assess as more meaningful and valid those phrases that
are more beautifully formed. The rhyme-as-reason effect causes us to confuse the validity of a phrase
with its aesthetics.
- Bullet Point Madness: I
- 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.
- 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.
- 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.
Forthcoming issues of Point Lookout
- Coming November 30: Avoiding Speed Bumps: II
- Many of the difficulties we encounter when working together don't create long-term harm, but they do cause delays, confusion, and frustration. Here's Part II of a little catalog of tactics for avoiding speed bumps. Available here and by RSS on November 30.
- And on December 7: Reaching Agreements in Technological Contexts
- Reaching consensus in technological contexts presents special challenges. Problems can arise from interactions between the technological elements of the issue at hand, and the social dynamics of the group addressing that issue. Here are three examples. Available here and by RSS on December 7.
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