Adopt an enterprise-wide definition of technical debt

Last updated on July 9th, 2021 at 11:25 am

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.

A physical expression of shared commitment, essential to adopting an enterprise-wide definition of technical debt
A physical expression of shared commitment. Effective technical debt management requires both a shared understanding of what it is and a shared commitment to do what’s required to control it.

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.

Other posts in this thread

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.

Cited in:

Confirmation bias and technical debt

Last updated on July 8th, 2021 at 01:35 pm

Confirmation bias is a cognitive bias [Kahneman 2011]. It’s the human tendency to favor and seek only information that confirms our preconceptions. It also causes us to avoid information that disconfirms our preconceptions. For example, the homogeneity of cable news channel audiences is a result of confirmation bias. Another result is the alignment between preconceptions of the audience and the slant of the newscast for that channel.

How confirmation bias can lead to technical debt

Third stage ignition, sending the Mars Climate Orbiter to Mars in December, 1998
Computer-generated image of the third stage ignition, sending the Mars Climate Orbiter (MCO) to Mars in December, 1998. The spacecraft eventually broke up in the Martian atmosphere due to what is now called the “metric mix-up.” The Lockheed Martin team that constructed and programmed the MCO used Imperial units. But the team at JPL that was responsible for flying the MCO used metric units. After the loss of the MCO, an investigation led by NASA uncovered the mix-up.
One of the many changes resulting from this loss was increased use of reviews and inspections. We don’t know why reviews and inspections weren’t as thorough before the loss of the MCO as they are now. But one possibility is the effects of confirmation bias in assessing the need for reviews and inspections. Image courtesy Engineering Multimedia, Inc., and U.S. National Aeronautics and Space Administration
Confirmation bias causes technical debt by biasing the information on which decision makers base decisions involving technical debt. Most people in these roles have objectives they regard as having priority over eliminating technical debt. This causes them to bias their searches for information about technical debt. The bias favors information that would support directly the achievement of those primary objectives. Decisions tend, for example, to discount warnings of technical debt issues. They also tend to underfund technical debt assessments, and set aside advice regarding avoiding debt formation in current projects.

An example

For example, anyone determined to find reasons to be skeptical of the need to manage technical debt need only execute a few Google searches. Searching for there is no such thing as technical debt yields about 300,000 results at this writing; technical debt is a fraud about 1.6 million; and technical debt is a bad metaphor about 3.7 million. Compare this to technical debt which yields only 1.6 million. A skeptic wouldn’t even have to read any of these pages to come away convinced that technical debt is at best a controversial concept. This is, of course, specious reasoning, if it’s reasoning at all. But it does serve to illustrate the potential for confirmation bias to contribute to preventing or limiting rational management of technical debt.

Last words

Detecting confirmation bias in oneself is extraordinarily difficult because confirmation bias causes us to (a) decide not to search for data that would reveal confirmation bias; and (b) if data somehow becomes available, to disregard or to seek alternative explanations for it if that data tends to confirm the existence of confirmation bias. Moreover, another cognitive bias known as the bias blind spot causes individuals to see the existence and effects of cognitive biases much more in others than in themselves [Pronin 2002].

Still, the enterprise would benefit from monitoring the possible existence and effects of confirmation bias in decisions with respect to allocating resources to managing technical debt. Whenever decisions are made, we must manage confirmation bias risk.

References

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

Other posts in this thread

Team composition volatility

Last updated on July 7th, 2021 at 07:51 pm

Now we know what we should have done.
Now we know what we should have done.” This is one kind of incremental technical debt. When the composition of a development team changes over the course of a project, recognizing how the team should have been done things can become more difficult.

Team composition volatility can interfere with technical debt retirement. In many organizations, project team composition evolves from the beginning of the project to its end. In most teams, people who have special knowledge cycle in and out as the work requires. These changes in team composition might not interfere with completing a team’s primary objectives.

But these changes can affect the team’s ability to retire technical debt incurred over the life of the project. Changes in team composition can also limit the team’s ability to retire specified legacy technical debt that it encounters while working toward its primary objectives.

The likelihood of incurring nonstrategic incremental technical debt can also increase when team composition changes. Changes can also reduce the likelihood of retiring all legacy debt specified in the team’s objectives.

Why team composition volatility matters for incremental technical debt

Groups we call teams are responsible for carrying out most product development, maintenance, and enhancement. In this context, team usually refers to, “a small group of interdependent individuals who share responsibility for outcomes.” [Hollenbeck 2012] However, as Hollenbeck, et al., observe, teams vary widely in both skill differentiation and composition stability. My sense is that both factors can potentially influence a team’s ability to retire incremental technical debt. They also affect its ability to achieve its objectives with respect to retiring legacy technical debt.

For example, consider what Fowler calls the Inadvertent/Prudent class of technical debt—“Now we know how we should have done it.” [Fowler 2009] In a project of significant size, some might recognize that different approaches to all or parts of the project would have been better choices. The recognition might come several months or years after completion of the work.

But for the moment, consider only cases in which the recognition occurs during the project, or shortly after completion. In these cases, the people who performed that work might have moved on to other teams. The people who now realize “how we should have done it” might themselves be incapable of making the needed changes, even if they have the budget or time to do the work. Or worse, they might not have the knowledge needed to recognize that a different approach would have been more effective. In either case, recognized or not, the work in question comprises incremental technical debt. Because of team composition volatility, recognizing or retiring that incremental technical debt can be difficult.

Why team composition volatility matters for retiring legacy technical debt

Team composition volatility can also interfere with retiring legacy technical debt. Some projects have specific goals of retiring a class or classes of legacy technical debt. But others with different objectives might also be charged with retiring instances of legacy technical debt as they encounter them. When we reassign team members who have special knowledge required for the team’s primary objectives, some legacy technical debt can remain extant, if retiring that debt requires their special knowledge. It can also remain extant if the reassignment occurs before they can complete the legacy debt retirement. This mechanism is more likely to occur when the legacy debt retirement objective seems subordinate to other business objectives.

Last words

Keeping team membership stable has big advantages relative the technical debt management. Said differently, organizations that must shuffle people from team to team as a consequence of controlling costs by reducing headcount can pay big penalties in terms of increasing loads of technical debt.

References

[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.

Available here; Retrieved January 10, 2016.

Cited in:

[Hollenbeck 2012] John R. Hollenbeck, Bianca Beersma, and Maartje E. Schouten. “Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description,” Academy of Management Review, 37:1, 82–106, 2012. doi:10.5465/amr.2010.0181

Available: here; Retrieved: July 8, 2017

Cited in:

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

Other posts in this thread

Technological communication risk

Last updated on July 7th, 2021 at 07:50 pm

See no evil, hear no evil, speak no evil
Hear no evil, see no evil, speak no evil—the iconic representation of communication failure. Technical debt can result from communication failures due to unwillingness to inform others of what you know, and unwillingness to receive information from others more knowledgeable.

Technologists must convey what they know about long-term technology trends to enterprise strategists and others. In addition to strategists, the interested parties include internal customers of technology, product owners, product managers, project sponsors, and senior management. Within the enterprise, technologists tend to be among those most knowledgeable regarding the relative alignment between enterprise technological assets and long-term technology trends. Yet technologists frequently fail to communicate this knowledge effectively to those who need it, and that can lead to nonstrategic technical debt. I call this phenomenon technological communication risk.

Technological communication risk is the risk that knowledgeable people within the enterprise don’t communicate important knowledge about technology. Within the enterprise are people who need this information and people who possess it. The risk is that people who possess it might be barred from distributing it, and people who need it might be unwilling to receive it. Policymakers can address this problem by working to define roles to clarify communication responsibilities. Role definitions must specify the need for this communication, and the need to be receptive to it.

A clear understanding of long-term technology trends is important in managing technical debt. Any significant misalignment between enterprise technological assets and long-term technology trends creates a risk of incurring new technical debt. As technologies evolve, enterprise assets must evolve with them. The gap between those assets and the state of the art is a source of lost productivity and depressed organizational agility, which is our definition of technical debt.

The root causes of technological communication risk

Some technologists are better informed about technology trends than are their internal customers, product owners, product managers, project sponsors, or senior management. Technologists often do attempt to communicate what they know on an informal basis, but unless such communication is expected and defined as an official duty, their superiors and internal customers don’t always welcome the information, especially if they haven’t heard it elsewhere, or if it conflicts with what they’ve learned elsewhere, or if its implications conflict with established strategic positions.

Many technologists are aware that their superiors might not welcome their observations about technological trends. And they are also aware that their superiors do not welcome observations about technology-based strategic vulnerabilities or opportunities. For example, a technologist might be reluctant to mention a cybersecurity risk that would be expensive to mitigate. This mechanism is especially strong when deploying adequate cyberdefense would compete for resources with other initiatives already underway. The mechanism is also important when the negative consequences of the vulnerability are unlikely to materialize. And some tend to question technologists’ credibility when they blame the technologists for the vulnerability itself.

Situations like these can lead to the formation of new nonstrategic technical debt in circumstances such as when Management directs technologists to…

  • …produce capabilities using approaches known to the technologists to be technological dead ends.
  • …implement capabilities that don’t exploit known approaches that could open new and vital lines of business.
  • …focus resources on initiatives that in the view of the technologists lack sufficient technological imperative.

Last words

Policymakers can mitigate technological communication risk by establishing internal standards that encourage knowledgeable technologists to share what they know. The parties that most benefit from the information are internal customers, project sponsors, or senior management. Similarly, those standards can encourage people in such roles to take heed when knowledgeable technologists do speak up.

References

[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.

Available here; Retrieved January 10, 2016.

Cited in:

[Hollenbeck 2012] John R. Hollenbeck, Bianca Beersma, and Maartje E. Schouten. “Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description,” Academy of Management Review, 37:1, 82–106, 2012. doi:10.5465/amr.2010.0181

Available: here; Retrieved: July 8, 2017

Cited in:

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

Other posts in this thread

Failure to communicate the technical debt concept

Last updated on July 7th, 2021 at 07:48 pm

A tensegrity 3-prism
A tensegrity three-prism. Read about tensegrity structures. Image (cc) Bob Burkhardt courtesy Wikimedia.

The behavior of internal customers and users of enterprise technological assets can contribute to technical debt formation and persistence. Because of these contributions, introducing effective technical debt management practices requires widespread behavioral changes on the part of those internal customers and users. Accepting these changes, and the initiative and creativity they require, is possible only if people understand the technical debt concept. When they do, they can appreciate the benefits of controlling technical debt, and the consequences of failing to control it. Similarly, when they do not understand or accept the technical debt concept, progress toward effective technical debt management is unlikely. Policymakers can contribute to the planning and execution of the required organizational transformation.

Even when engineering teams are aware of the technical debt concept, and when they do try to manage technical debt, progress can be elusive. Significant progress requires the support and understanding of engineering management, internal customers, and customers’ managements. Everyone must understand that controlling technical debt—and retiring it—is a necessary engineering activity that has a business purpose. Everyone must understand that technical debt arises as a result of everyone’s behavior—not just the behavior of technologists.

Part of the job of Management is to ensure that engineers have what they need to avoid incurring technical debt unnecessarily. Management must also ensure that they have what they need to retire elements of legacy technical debt on a regular basis. Internal customers must understand that communicating their long-term business strategies to Engineering is essential for limiting unnecessary creation of artifacts that become nonstrategic technical debt. Only by understanding the technical debt concept can internal customers learn to avoid the behaviors that lead to nonstrategic technical debt, and adopt behaviors that limit new technical debt.

The tensegrity structure metaphor for technical debt management

Tensegrity structures provide a metaphor for organizations that have mastered the technical debt concept. Tensegrity structures use isolated rigid components in compression, held by a network of strings or cables in tension. The rigid components are usually struts or masts, and they aren’t in contact with each other.

The struts correspond to the users or customers of technological assets. The cables correspond to the engineering activities required to support the customers. The organization is stable relative to technical debt only when the two kinds of elements (struts and cables) work together, each playing its own role, but each appreciating the role of the other.

Advocating for cultural transformation

Advocates of any change to organizational culture are often seen as acting in their own self-interest. That’s a common risk associated with cultural transformation. It’s a risk that can lead to failure when inserting practices related to technical debt management into the culture. The risk is greatest when advocates for change are drawn exclusively from the technical elements of the enterprise. The ideal advocates for these ideas and practices are the internal customers of the technical organizations, and senior management.

References

[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.

Available here; Retrieved January 10, 2016.

Cited in:

[Hollenbeck 2012] John R. Hollenbeck, Bianca Beersma, and Maartje E. Schouten. “Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description,” Academy of Management Review, 37:1, 82–106, 2012. doi:10.5465/amr.2010.0181

Available: here; Retrieved: July 8, 2017

Cited in:

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

Other posts in this thread

Failure to communicate long-term business strategy

Last updated on July 8th, 2021 at 01:11 pm

Failure to communicate long-term business strategy can lead to increased technical debt. This happens because engineering decisions that aren’t aligned with business strategy can result in what later becomes technical debt. As business strategy veers away from the assumptions underlying those misaligned engineering decisions, engineers must alter implementations to track the strategy. Technical debt can form during those alteration efforts.

Moreover, the resources that support those alteration efforts might have been unnecessary if senior managers had kept technologists better informed about long-term business strategy. In some cases, the result would have been a reallocation of those resources to other pursuits, including technical debt retirement. To ensure alignment of engineering decisions with long-term business strategy, engineering decision makers must be aware of long-term and intermediate-term enterprise strategy. When they are aware, they can anticipate the engineering needs of the enterprise. And they’re more likely to make decisions that are compatible with strategy.

Strategists can benefit from keeping technologists informed

A plug-in electric vehicle being recharged
Recharging a  plug-in electric vehicle. The dominance of petroleum-powered vehicles is nearing its end. Further investment in the petroleum-based fuels infrastructure is now  inconsistent with what the global economy has chosen as its strategic intent. Electric vehicles are still out of the reach of most consumers, but they would be wise to favor long range vehicles. As electric vehicles become ascendant, petroleum filling stations will become more widely spaced. The wider spacing reduces the metaphorical interest charges on the technical debt of yet-to-be-retired petroleum powered vehicles. During the transition to electric power dominance, a long-range petroleum-powered vehicle offers clear advantages over its shorter-range cousins.
The effect is bi-directional. Strategists can benefit from understanding the effect their strategies have on technological activity. For example, consider the process of choosing among strategic options. A favorable outcome is more likely if strategists know the effects of each option on the technical debt portfolio.

To gain effective control of technical debt, senior management must regard the technical elements of the enterprise as strategic partners [Woodard 2013] [Ross 2000] [Brenner 2016a]. Policymakers can make important contributions to enhancing communication between strategists and technologists.

For example, when engineers know the general direction of the enterprise, they can focus efforts on assets that are compatible with future needs. Inversely, when they’re unaware of the business strategy, they’re more likely to make decisions that they must later rescind.

What about legacy technical debt retirement?

Analogous considerations apply to legacy technical debt  retirement efforts. Major technical debt retirement efforts are often subject to review for alignment with enterprise strategy. But we tend not to review incidental retirement efforts that occur in the context of routine maintenance or development. Consequently, engineers might allocate effort to incidental debt retirement unnecessarily if the asset is due for overhaul or replacement. Communicating long-term strategy effectively is likely the most reliable way to prevent such misspent effort.

Last words

Some managers elect to communicate business strategy to technologists only when they “need to know.” Often, technologists needed to know long before that.

References

[Brenner 2016a] Richard Brenner. “The Psychology and Politics of Technical Debt: How We Incur Technical Debt and Why Retiring It Is So Difficult,” Cutter Business Technology Journal, 29:3, 2016, 21-27.

Cited in:

[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.

Available here; Retrieved January 10, 2016.

Cited in:

[Hollenbeck 2012] John R. Hollenbeck, Bianca Beersma, and Maartje E. Schouten. “Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description,” Academy of Management Review, 37:1, 82–106, 2012. doi:10.5465/amr.2010.0181

Available: here; Retrieved: July 8, 2017

Cited in:

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Woodard 2013] C. Jason Woodard, Narayan Ramasubbu, F. Ted Tschang, and V. Sambamurthy. “Design Capital and Design Moves: the Logic of Digital Business Strategy,” MIS Quarterly 37:2, 537-564, 2013.

Cited in:

Other posts in this thread

Nontechnical precursors of nonstrategic technical debt

Last updated on July 8th, 2021 at 01:09 pm

Nonstrategic technical debt is technical debt that appears in the asset without strategic purpose. We tend to introduce nonstrategic technical debt by accident, or as the result of urgency, or from changes in standards, laws, or regulations—almost any source other than asset-related engineering purposes. In this thread I examine a variety of precursors of nonstrategic technical debt that aren’t directly related to technology. Sources of these precursors include:

  • Communication between and among people
  • Organizational policies relating to job assignments
  • Cognitive biases [Kahneman 2011]
  • Performance management policy
  • Incentive structures
  • Organizational structures
  • Contract language
  • Outsourcing
  • …and approaches to dealing with budget depletion.

Precursors vs. causes

The cables of the Brooklyn Bridge are an example of nonstrategic technical debt
Some of the suspension cables of the Brooklyn Bridge. Washington Roebling, the chief engineer, designed them to be composed of 19 “strands” of wire rope [McCullough 1972]. Each strand had 278 steel wires. Thus, the original design called for a total of 5,282 wires in each of the main cables. After the wire stringing began, the bridge company made an unsettling discovery. The wire supplier, J. Lloyd Haigh, had been delivering defective wire by circumventing the stringent inspection procedures. In all, Roebling estimated that 221 U.S. tons (200 metric tons) of rejected wire had been installed. This was a significant fraction of the planned total weight of 3,400 U.S. tons (3,084 metric tons). Because they couldn’t remove the defective wire, Roebling decided to add about 150 wires to each main cable. That extra wire would be provided at no charge by Haigh [Talbot 2011]. I can’t confirm this, but I suspect that Roebling actually added 152 wires, which would be eight wires for each of the 19 strands. That made a total of 286 wires per strand, or 5,434 wires. The presence of the defective wire in the bridge cables—which remains to this day—is an example of technical debt. The fraud perpetrated by Haigh illustrates how malfeasance can lead to technical debt.
I use the term precursor instead of cause because none of these conditions leads to technical debt inevitably. From the perspective of the policymaker, we can view these conditions as risks. It’s the task of the policymaker to devise policies that manage these risks.

McConnell has classified technical debt in a framework that distinguishes responsible forms of technical debt from other forms [McConnell 2008]. Briefly, we incur some technical debt strategically and responsibly. Then we retire it when the time is right. We incur other technical debt for other reasons, some of which are inconsistent with enterprise health and wellbeing.

The distinction is lost on many. Unfortunately, most technical debt is nonstrategic. We would have been better off  if we had never created it. Or if we had retired it almost immediately. In any case we should have retired it long ago.

It’s this category of nonstrategic technical debt that I deal with in this thread. Although all technical debt is unwelcome, we’re especially interested in nonstrategic technical debt, because it’s usually uncontrolled. In these posts I explore the nontechnical mechanisms that lead to formation of nonstrategic technical debt. Schedule pressure is one exception. Because it’s so important, it deserves a thread of its own. I’ll address it later.

Last words

Here are some of the more common precursors of nonstrategic technical debt.

I’ll be adding posts on these topics, so check back often, or subscribe to receive notifications when they’re available.

References

[Brenner 2016a] Richard Brenner. “The Psychology and Politics of Technical Debt: How We Incur Technical Debt and Why Retiring It Is So Difficult,” Cutter Business Technology Journal, 29:3, 2016, 21-27.

Cited in:

[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.

Available here; Retrieved January 10, 2016.

Cited in:

[Hollenbeck 2012] John R. Hollenbeck, Bianca Beersma, and Maartje E. Schouten. “Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description,” Academy of Management Review, 37:1, 82–106, 2012. doi:10.5465/amr.2010.0181

Available: here; Retrieved: July 8, 2017

Cited in:

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[McConnell 2008] Steve McConnell. Managing Technical Debt, white paper, Construx Software, 2008.

Available: here; Retrieved November 10, 2017.

Cited in:

[McCullough 1972] David McCullough. The Great Bridge: The epic story of the building of the Brooklyn Bridge. New York: Simon and Schuster, 1972.

Order from Amazon

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Talbot 2011] J. Talbot. “The Brooklyn Bridge: First Steel-Wire Suspension Bridge.” Modern Steel Construction 51:6, 42-46, 2011.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Woodard 2013] C. Jason Woodard, Narayan Ramasubbu, F. Ted Tschang, and V. Sambamurthy. “Design Capital and Design Moves: the Logic of Digital Business Strategy,” MIS Quarterly 37:2, 537-564, 2013.

Cited in:

Related posts

The concept of MICs

Last updated on July 8th, 2021 at 11:52 am

Using the term interest to refer to the metaphorical interest charges of a technical debt is risky. The risk arises from confusing the properties of financial interest with the properties of the metaphorical interest charges on technical debt. Using an alternative term that makes the metaphor obvious can limit this risk. One such term is metaphorical interest charges, or for convenience, MICs.

Loose change
Loose change. The MICs on technical debt accumulate in two ways: (a) as “loose change,” namely, small bits of lost time, delays, and depressed productivity; and (b) as major blows to enterprise vitality in the form of lost revenue, delayed revenue, and missed market opportunities. Hard to say which category does more damage.
MICs aren’t interest charges in the financial sense. Rather, the MICs of a technical debt represent the total of reduced revenue, incidental opportunity costs, and increased costs of all kinds resulting from carrying that technical debt. (Actually, now that I think of it, MICs can include financial interest charges if we find it necessary to borrow money as a consequence of carrying technical debt.) Because the properties of MICs are very different from the properties of financial interest charges, we use the term MICs to avoid confusion with the term interest from the realm of finance.

What exactly are “metaphorical interest charges?”

Briefly, MICs are variable and often unpredictable [Allman 2012]. MICs differ from interest charges on financial debt for at least eight reasons. For any particular class of technical debt:

I examine each of these properties in more detail in the posts listed above.

References

[Allman 2012] Eric Allman. “Managing Technical Debt: Shortcuts that save money and time today can cost you down the road,” ACM Queue, 10:3, March 23, 2012.

Available: here; Retrieved: March 16, 2017

Also cited in:

[Brenner 2016a] Richard Brenner. “The Psychology and Politics of Technical Debt: How We Incur Technical Debt and Why Retiring It Is So Difficult,” Cutter Business Technology Journal, 29:3, 2016, 21-27.

Cited in:

[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.

Available here; Retrieved January 10, 2016.

Cited in:

[Hollenbeck 2012] John R. Hollenbeck, Bianca Beersma, and Maartje E. Schouten. “Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description,” Academy of Management Review, 37:1, 82–106, 2012. doi:10.5465/amr.2010.0181

Available: here; Retrieved: July 8, 2017

Cited in:

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[McConnell 2008] Steve McConnell. Managing Technical Debt, white paper, Construx Software, 2008.

Available: here; Retrieved November 10, 2017.

Cited in:

[McCullough 1972] David McCullough. The Great Bridge: The epic story of the building of the Brooklyn Bridge. New York: Simon and Schuster, 1972.

Order from Amazon

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Talbot 2011] J. Talbot. “The Brooklyn Bridge: First Steel-Wire Suspension Bridge.” Modern Steel Construction 51:6, 42-46, 2011.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Woodard 2013] C. Jason Woodard, Narayan Ramasubbu, F. Ted Tschang, and V. Sambamurthy. “Design Capital and Design Moves: the Logic of Digital Business Strategy,” MIS Quarterly 37:2, 537-564, 2013.

Cited in:

Related posts

MPrin for missing or incomplete capability

Last updated on July 7th, 2021 at 02:53 pm

In some instances, the metaphorical principal (MPrin) of a technical debt is a missing or incompletely implemented capability. For example, absence of a fully automated regression test suite can create difficulties for testing a complex system. Defects can slip through. That would result in reduced productivity and velocity. In this case, the projected cost of implementing, testing, and documenting the test suite, and training its users, would constitute the initial MPrin of the outstanding technical debt. This definition differs from some definitions, because it includes testing, documenting, and initial training. In general, from the enterprise perspective, when identifying the MPrin associated with missing or incompletely implemented capabilities, we must include all artifacts necessary to eliminate reductions in productivity and velocity.

But even if we include these items in the conventional definition, MPrin at retirement can exceed the savings at the time we incurred the debt. For example, in the interval between origination and retirement the assets involved can change. Moreover, if retiring the debt causes a revenue stream interruption, the MPrin, which includes the lost revenue, can be significantly larger than the initial MPrin.

Unique problems of incompletely implemented capability

A concrete building under construction
A concrete building under construction. Concrete takes about a month to cure and reach full strength. If we waited for full curing before pouring the floor above, multistory concrete construction would be slow and expensive. So we start on the next floor after only a few days. Because the floors can’t support themselves for about a week, we shore them using lower floors. The shoring constitutes a technical debt resulting from the “incomplete implementation” (partial cure) of each floor. We retire that debt by removing the shoring as we go. More about shoring and re-shoring
Technical debt associated with incompletely implemented capability presents unique problems. We can retire it in three distinct ways. First, we can complete the implementation. The MPrin associated with this approach can grow beyond the initial cost of completion, for the usual reasons. Second, we can cancel the capability. If we do, retiring the debt completely would require removal of all artifacts that we no longer need. Finally, we can choose a middle path. In the middle path we adopt some parts that have been completed. But we reject other parts, and we add whatever is necessary to create a limited version of what we originally planned.

Special challenges of non-physical assets

Invisibility is an important attribute of non-physical assets such as software, procedures, legislation, regulations, and so on. Technical debt associated with incomplete implementation is difficult to manage in such assets. For example, the image above shows several levels of a concrete building under construction. The vertical members between the levels are part of a shoring system that supports the levels of the building. Shoring is necessary until the concrete floors cure well enough to support themselves. Shoring constitutes a kind of technical debt that must be “retired” before the building is complete. The teams constructing the building could never forget to remove the shoring because it obstructs installation of the windows and walls.

But things are very different with non-physical assets. It’s easy to forget to remove intermediate artifacts, or elements that were part of attempts that didn’t work out. Many non-physical assets are perfectly functional carrying that kind of technical debt. That debt becomes evident with time, as the asset becomes increasingly difficult to maintain, extend, or defend.

It’s this property of non-physical assets that makes technical debt management so much more difficult than it is with physical assets. Not more important, just more difficult.

References

[Allman 2012] Eric Allman. “Managing Technical Debt: Shortcuts that save money and time today can cost you down the road,” ACM Queue, 10:3, March 23, 2012.

Available: here; Retrieved: March 16, 2017

Also cited in:

[Brenner 2016a] Richard Brenner. “The Psychology and Politics of Technical Debt: How We Incur Technical Debt and Why Retiring It Is So Difficult,” Cutter Business Technology Journal, 29:3, 2016, 21-27.

Cited in:

[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.

Available here; Retrieved January 10, 2016.

Cited in:

[Hollenbeck 2012] John R. Hollenbeck, Bianca Beersma, and Maartje E. Schouten. “Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description,” Academy of Management Review, 37:1, 82–106, 2012. doi:10.5465/amr.2010.0181

Available: here; Retrieved: July 8, 2017

Cited in:

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[McConnell 2008] Steve McConnell. Managing Technical Debt, white paper, Construx Software, 2008.

Available: here; Retrieved November 10, 2017.

Cited in:

[McCullough 1972] David McCullough. The Great Bridge: The epic story of the building of the Brooklyn Bridge. New York: Simon and Schuster, 1972.

Order from Amazon

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Talbot 2011] J. Talbot. “The Brooklyn Bridge: First Steel-Wire Suspension Bridge.” Modern Steel Construction 51:6, 42-46, 2011.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Woodard 2013] C. Jason Woodard, Narayan Ramasubbu, F. Ted Tschang, and V. Sambamurthy. “Design Capital and Design Moves: the Logic of Digital Business Strategy,” MIS Quarterly 37:2, 537-564, 2013.

Cited in:

Related posts

MPrin when standards or regulations change

Last updated on July 7th, 2021 at 11:15 am

The MPrin of technical debt that forms as a result of a change in standards or regulations is the cost of bringing affected assets into compliance. It matters not whether the standards in question are internal to your organization or external. The conventional definition of the MPrin for this kind of technical debt includes only the cost of aligning to the new standards or regs, the assets directly affected. But the conventional definition is incomplete. If we account for all work properly, the MPrin should also include ripple effects. Ripple effects are the changes in other assets that we must perform to maintain compatibility with the assets affected directly by the change in standards or regs.

The phrase standards or regs is beginning to bother even me. I’ll switch to standards when I mean standards or regulations (or regs) except when I say so explicitly.

Cost drivers of changes in standards

A view of the left side guard on a truck operated by the City of Cambridge, Massachusetts
A view of the left side guard on a truck operated by the City of Cambridge, Massachusetts. Side guards prevent vulnerable road users (pedestrians, bicyclists, and motorcyclists) from being swept under trucks and crushed (and often killed) by the truck’s rear wheels. Cambridge has a pilot program affecting city-operated trucks, but Boston is requiring all contractors to install side guards. This change in regulations creates a technical debt for all truck operators whose vehicles lack side guards. [Volpe 2017] City of Cambridge photo courtesy U.S. Department of Transportation.

Aligning existing assets to new standards can have expensive consequences. We must include all costs in the calculation of MPrin. Unfortunately, some costs are often overlooked or accounted for in other ways. For example, testing might require a service interruption or product availability delays or interruptions. And that could entail a revenue stream delay or interruption. That lost revenue is certainly a consequence of the debt retirement effort.

Deferring retirement of this class of technical debt can expose the enterprise to the risk of MPrin growth in two ways. First, when we defer debt retirement, the number of instances of violations of the new standards can increase as we develop new assets in compliance with the obsolete standards. Second is the potential for increases in the number of ripple effect instances when we defer debt retirement. These instances arise from increases in the number of artifacts that require updating. The issue isn’t that they aren’t compliant with the new standards. Rather, it is that we must align them with the components we modify to comply with the new standards. In this way, MPrin at debt retirement time can greatly exceed the savings we realized when we first incurred the debt.

Last words

However, as with most technical debts, deferring retirement of this class of debt can sometimes be wise. For example, if the assets that bear the debt are about to be retired, the debt they carry vanishes when we retire those assets.

References

[Allman 2012] Eric Allman. “Managing Technical Debt: Shortcuts that save money and time today can cost you down the road,” ACM Queue, 10:3, March 23, 2012.

Available: here; Retrieved: March 16, 2017

Also cited in:

[Brenner 2016a] Richard Brenner. “The Psychology and Politics of Technical Debt: How We Incur Technical Debt and Why Retiring It Is So Difficult,” Cutter Business Technology Journal, 29:3, 2016, 21-27.

Cited in:

[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.

Available here; Retrieved January 10, 2016.

Cited in:

[Hollenbeck 2012] John R. Hollenbeck, Bianca Beersma, and Maartje E. Schouten. “Beyond Team Types and Taxonomies: A Dimensional Scaling Conceptualization for Team Description,” Academy of Management Review, 37:1, 82–106, 2012. doi:10.5465/amr.2010.0181

Available: here; Retrieved: July 8, 2017

Cited in:

[Kahneman 2011] Daniel Kahneman. Thinking, Fast and Slow. New York: Macmillan, 2011.

Order from Amazon

Cited in:

[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.

Cited in:

[McConnell 2008] Steve McConnell. Managing Technical Debt, white paper, Construx Software, 2008.

Available: here; Retrieved November 10, 2017.

Cited in:

[McCullough 1972] David McCullough. The Great Bridge: The epic story of the building of the Brooklyn Bridge. New York: Simon and Schuster, 1972.

Order from Amazon

Cited in:

[Pronin 2002] Emily Pronin, Daniel Y. Lin, and Lee Ross. “The bias blind spot: Perceptions of bias in self versus others.” Personality and Social Psychology Bulletin 28:3, 369-381, 2002.

Available: here; Retrieved: July 10, 2017

Cited in:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Talbot 2011] J. Talbot. “The Brooklyn Bridge: First Steel-Wire Suspension Bridge.” Modern Steel Construction 51:6, 42-46, 2011.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Volpe 2017] Volpe National Transportation Systems Center. “Truck Side Guards Resource Page,” October 2017.

Available: here; Retrieved: November 22, 2017

Cited in:

[Woodard 2013] C. Jason Woodard, Narayan Ramasubbu, F. Ted Tschang, and V. Sambamurthy. “Design Capital and Design Moves: the Logic of Digital Business Strategy,” MIS Quarterly 37:2, 537-564, 2013.

Cited in:

Related posts

Show Buttons
Hide Buttons