Because effective technical debt management requires cooperation from almost everyone, an enterprise-wide definition of technical debt is essential. Absent a shared definition of technical debt, controversy can develop. Controversy is especially likely among those who have previously encountered the concept—namely, among technologists. Policymakers can make invaluable contributions to the design of the cultural transformation that will enable control of technical debt.
Li et al. [Li 2015] found that defining what is and what isn’t technical debt remains an open question in software engineering. Even if we restrict the discussion to software constructed in-house, opinions about what constitutes technical debt do differ. The authors found that in the literature of technical debt, “The term ‘debt’ has been used in different ways by different people, which leads to ambiguous interpretation of the term.”
This finding is perhaps the most significant for policymakers. It suggests that controlling technical debt might require forging an organizational consensus about the meaning of the term technical debt. The people of most organizations come from many different backgrounds. Those with little knowledge of technical debt have few preconceptions. But those who are aware of the issue probably interpret the term technical debt in a variety of ways. Because some of those who do have awareness of the term are likely to have strong opinions about its meaning, one can anticipate a need to resolve these differences.
The effect of an absence of standards
Some technical terms, like RAID, byte, compiler, and kilowatt, have widely accepted standard definitions. Although the term technical debt has found wide use, it has no standard definition. What some people categorize as technical debt, others do not. Those who are accustomed to working with terms that have precise, widely accepted definitions might tend to assume that the term technical debt does have (or should have) one as well. This assumption can create some difficulty for people who don’t realize that others might have differing views of the definition of the term.
For example, there are those who believe that defects are not technical debt. And some believe that no element of a technological asset can constitute technical debt unless it is part of a product that a customer uses. Our definition differs with both of these views.
Last words
Policymakers must be aware that there is a lack of consensus about the definition of technical debt. Our definition, crafted specially for the use of policymakers, might seem unusually broad to technologists and engineers. For that reason alone, it’s advisable to become familiar with the various ways technologists use the term. Understanding their perspective is essential to formulating sound policy deserving of their respect.
[Li 2015] Zengyang Li, Paris Avgeriou, and Peng Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.
Tension between policymakers and technologists, which can manifest as misalignment of their respective priorities, is a significant contributor to uncontrolled growth of technical debt. In this thread, I explore sources of this tension. That exploration introduces concepts that can assist policymakers and technologists in their efforts to control technical debt growth.
Technical debt is not just a technical problem
The objective of technical debt management policy is effective, sustainable control of technical debt. In an enterprise that has achieved this objective, technical debt serves as a strategic tool. That tool assists in attaining and maintaining market leadership. In such an organization, technical debt does exist, and some legacy technical debt might remain in place. But the enterprise manages technical debt growth strategically, if growth occurs at all. The enterprise addresses any technical debt that carries significant MICs. And it pays special attention to technical debt that compromises productivity and enterprise agility. In short, the enterprise addresses technical debt not only as a technological issue, but also as a component of business strategy.
This stance is at odds with the historical position most enterprises have adopted vis-à-vis technical debt. In the historic view, technical debt is a technical problem, if it is recognized at all. Most enterprises relegate technical debt management to the technologists. Frequently, then, technologists view as interlopers any policymakers who enter the discussion about technical debt. Any such policymakers usually arrive late to the discussion. Technologists often view them as less-than-knowledgeable invaders attempting to seize control of a piece of the technologists’ domain. In this way tensions can arise between policymakers and technologists. Such tensions complicate the problem of managing technical debt.
Sources of tension
One possible source of this tension is apparent in a study of the literature of technical debt, which is evolving so rapidly that it has itself become a focus for research. Li et al. [Li 2015] have produced a review of the software engineering technical debt literature. From this review we can extract insights useful to policymakers. They studied only the literature relating to technical debt in software engineering. But their conclusions are, at least in part, applicable to any field in which the components of the finished product are executed within software tools before being committed to operational form. This covers a wide array of knowledge-intensive endeavors, including mechanical system design, electronic design, framing of legislation, process design, architecture, and even book authorship.
Last words
In this thread, I explore the sources of the tension between the modern reality of technical debt as an enterprise issue, and the historical situation of technical debt as a technological issue. This can serve as a guide for policymakers in reframing technical debt. The archaic view of technical debt is as a technological issue dependent for resolution on enterprise resources. The modern view is as an enterprise issue dependent for resolution on technological resources.
[Li 2015] Zengyang Li, Paris Avgeriou, and Peng Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.
Stovepiping can lead to technical debt. Actual stovepipes are the tubes that vent exhaust from stoves. These tubes serve as a metaphor for the flow of information in “stovepiped” organizations. In stovepiped organizations, information can flow predominantly (or only) up or down along the parallel chains of command. But information can flow only rarely (or never) from a point in one chain of command across to some other chain of command [Waters 2010]. The stovepipe metaphor is imperfect, in the sense that in actual stovepipes, smoke and fumes rarely flow downwards. By contrast, in organizations, some information does flow down the chains of command. But the metaphor does clarify the problem of limited flow of information. Transferring whatever the organization learns in one metaphorical stovepipe into other metaphorical stovepipes is difficult.
Two forms of stovepiping
Stovepiping can occur in both organizational structures and in engineered systems. These two forms of stovepiping are intimately related, and both can lead to uncontrolled formation of new technical debt, or increased persistence of existing technical debt.
In organizational structures, stovepiping occurs when elements of different organizational units with similar capabilities act relatively independently. An example is the dispersal of some elements of the IT function out into IT’s customers. When independent organizations have similar technical needs, they’re at risk of generating new technical debt. The debt they generate results from independently implementing technological capabilities that duplicate each other.
Stovepiping occurs in engineering, for example, when the organization manages and maintains independently two distinct technological assets [McGovern 2003]. In that situation, distinct engineering efforts working on those assets might happen to solve the same problem, possibly in two different ways. Then each party might be either ignorant or possibly disparaging, of the other’s efforts.
How stovepiping relates to technical debt
In whichever way duplication of technological capability comes about, it can increase levels of technical debt. Alternatively, it can increase persistence of existing technical debt. These effects happen because the organization might need to execute future maintenance or enhancement efforts multiple times—once for each instance of the technical artifact. That exposes the organization to additional cost, additional load on its staff, and additional risk of creating defects and incurring liability. Compare this situation to one in which all units that need a particular asset share it. Duplication is expensive.
The problem is actually even more worrisome. First, suppose there exists a defect in one version of a technological artifact. The people who are aware of the defect might not realize that another version of the artifact exists. If that second version also has an analogous defect, its defect might go unrecognized for some time, with all the usual attendant negative consequences. Second, suppose there is a necessary extension of the artifact’s capabilities. The maintainers of one version might recognize the need for the extension and implement it. Meanwhile, the maintainers of other versions might not recognize the need for the extension. They might not take action until something bad happens or a possibly urgent need arises. It’s easy to conjure other unfavorable—and costly—scenarios.
Stovepiping in technological systems
In engineering more generally, stovepiping can occur internally in systems, even though only one business unit is involved, and even though the stovepiped artifacts serve purposes invisible to the world outside the system. This can occur whenever there is weak communication between the teams designing or maintaining the portions of the system that host the similar artifacts. For readers familiar with the Apollo XIII incident, the incompatibility of the two carbon dioxide scrubbers in the command module and the lunar excursion module serves as an example of the risks of technical stovepiping.
When distinct business units or functions operate their own engineering or IT organizations, there’s an elevated probability of duplicating technological assets. The same effect can occur when they depend on a shared engineering function but require similar work. This happens when the organizational structure or the timing of the work encourages separate engineering efforts. Engineering or IT functions operated separately under the control of distinct business units or functions can clearly produce duplicated capabilities. However, duplication can also occur when the engineering function is shared across distinct business units or functions. This happens when the actual people and teams performing the work differ for different efforts. And it can happen too when communication is weak between those teams, whether or not the efforts are conducted contemporaneously.
Last words
Because identifying these forms of technical debt after they appear is notoriously difficult, preventing their formation is preferable. Prevention is possible if the enterprise establishes mechanisms that facilitate consultation and sharing among elements of different, separately operated technology development or maintenance functions. In other words, the organization must “break” the stovepipes—no mean feat, politically speaking.
Another challenge, of course, is providing resources for such sharing mechanisms, because preventing technical debt is rarely recognized as a value generator. If it were so recognized, the resources would likely appear. Changes in cost accounting might make such recognition more likely.
References
[Li 2015] Zengyang Li, Paris Avgeriou, and Peng Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.
[McGovern 2003] James McGovern, Scott W. Ambler, Michael E. Stevens, James Linn, Vikas Sharan, and Elias K. Jo. A Practical Guide to Enterprise Architecture, Upper Saddle River, New Jersey: Prentice Hall PTR, 2003.