Organizational culture and technical debt

Last updated on July 7th, 2021 at 03:18 pm

A bonsai tree
A bonsai tree. We cannot control the growth of bonsai in detail. We can only make suggestions, and hope that the tree will follow our guidance. So it is with organizational culture.

Organizational culture affects—and is affected by—everything the organization does. It is complex beyond imagining. It creates leaders and leaders shape culture [Schein 2016]. Fortunately, for our narrow purposes—namely, improving how we manage technical debt—we need not explore every available model of culture. All we need to know is how to adjust cultures so that they’re more amenable to technical debt management efforts. Even so, that’s an ambitious objective.

Organizational culture is the collection of values, beliefs, and principles the people of the organization share. Some of these elements are within the awareness of the organization’s people. But some might not be. Culture excludes behavior; behavior is a result of the combined effects of personal choices and organizational culture.

With respect to technical debt, our objective is ambitious because it is at once specific and general. It is general in the sense that as a goal, we would like to devise prescriptions for all organizational cultures as they strive to be more effective in managing technical debt. It is specific in the sense that we’re concerned only with those cultural factors that affect technical debt management.

The case for considering cultural effects on technical debt

But aren’t there enough technical problems to keep us occupied before we get involved in all that culture change stuff? The answer to that, I believe, is yes. But we can make more rapid progress if we allow considerations of culture to guide our technical investigations.

Some of our best minds have been working on the technical debt problem for more than two decades, mostly from the technological perspective. True, we haven’t given the issue the attention and resources it deserves. That might be changing now, but one can reasonably ask a simple question: If some of the causes of the technical debt problem are cultural, and if we begin to make some technological progress in reducing the burden of technical debt, wouldn’t the cultural causes begin to dominate at some point? If that were to happen, the effectiveness of our technical solutions would appear to decline, even though they might be “right,” because technical solutions cannot address cultural problems.

It seems only prudent to prepare for that case by examining the role of culture in creating technical debt and preventing or delaying its retirement.

A reasonable goal might be to define a set of attributes an organizational culture should have if the organization wants to limit the contributions of culture to the formation and persistence of technical debt. I suspect that for most cultures, change would be required, because most organizations now carry more technical debt than they would care to acknowledge.

As with all culture change efforts, we seek, in the end, to modify the behavior of the people who live within that culture. We want to modify aspects of the culture so as to lead its people to be more likely to make choices that are consistent with prudent technical debt management.

Where to from here

With that goal in mind, I’m opening a thread in this blog that I hope will stimulate your thinking and mine about how organizational culture and technical debt interact. This post will contain an outline of these ruminations. Here’s what I have so far:

References

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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Where the misunderstandings about MICs come from

Last updated on July 8th, 2021 at 12:50 pm

The differences between technical debt and financial debt are numerous and significant. We often overlook them, in part, because of the metaphor itself. Managing technical debt as we would manage financial debt is risky for two reasons. First, such an approach would most likely fail to exploit properties of technical debt that can be advantageous. Second, such an approach would likely cause us to overlook opportunities because of reticence about addressing the technical debt problem to the extent necessary for effective control.

The right tool for the wrong job
Managing technical debt using approaches drawn from finance is analogous to using the right tool for the wrong job.
The debt metaphor itself is probably at the root of the misunderstanding. The financial metaphor evokes the conventional concept of fixed or slowly varying interest rates. But the reality of technical debt involves loss of enterprise agility or lost revenue. Connecting these two ideas is intuitively challenging.

For the more familiar kinds of financial debts, the interest rate and any rules for adjusting it are set at the time of loan origination. Moreover, financial debts are unitary in the sense that each loan is a single point transaction with a single interest rate formula. For example, the interest rate formula for the most common kind of credit card balance is the same for every purchase. Technical debt isn’t unitary. Each kind of technical debt and each manifestation of that kind of technical debt is, in effect, a separate loan that can carry its own independently variable MICs.

Last words

The cost of carrying technical debt can vary with time. It can vary for a given class of technical debt, or it can vary instance-by-instance. Costs depend on the nature of the work underway on the assets that carry the debt. This fact is a source of flexibility useful for planning technical debt management programs. To manage resources, planners can exploit this flexibility to set priorities for enterprise efforts. For example, planning technical debt retirement programs to retire all instances of a given class of technical debt might not be the best choice.

When making technical debt management decisions, respect the constraints that technical debt imposes. Exploit the flexibility that technical debt provides.

References

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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MICs can change when other debts are retired

Last updated on July 8th, 2021 at 12:49 pm

The MICs and MPrin of a particular class of technical debt can change when we retire other seemingly unrelated classes of technical debt. In most cases, we need engineering expertise to determine technical debt retirement strategies that can exploit this property.

Financial debts usually have associated interest rates that are used to compute the periodic interest charges. Typically, the interest charge on a financial debt for a given period is the periodic interest rate multiplied by the principal, and then scaled for the length of the time period. But there are no “rates” for technical debt. Their existence would imply that MICs were proportional to the analog of “principal,” which, in the case of technical debt, is the cost of retiring the debt—the MPrin. MICs depend only weakly on the cost of retiring the debt. Instead, they depend more strongly on the impact of the debt on ongoing operations.

How financial sophistication can be a handicap

Decision makers who understand the world of financial instruments at a very sophisticated level might tend to make an understandable error. They might overvalue arguments favoring technical debt management in ways analogous to how we manage financial debts. Financial sophisticates might find appealing any argument for technical debt management that parallels financial approaches. Such programs are unlikely to work, for two reasons. First, the uncertainties associated with estimating MPrin and MICs are significant. They make technical debt management decisions more dependent on engineering and project management judgment than they are on the results of calculations and projections (see MPrin uncertainties and MICs uncertainties).

Second, the familiar concept of interest rate doesn’t apply to technical debt. For technical debt, the interest charges depend on the interaction between ongoing activities and the debt, rather than the cost of retiring the debt. And that means that MICs (and MPrin) of one class of debt can change when another class is retired.

Implications of this effect

The possibility that retiring one class of technical debt can alter the financial burdens presented by another has both favorable and unfavorable implications.

MICs can change when other debts are retired
An example illustrating one way in which MICs on one kind of technical debt can change as a result of retiring another. The structure at the left represents the situation before any debt retirement occurs. The balloons labeled “A” represent instances of asset A. The balloon labeled “B” represents asset B. The orange circles represent instances of technical debts D1 and D2. The arrows connecting the As to B indicate that asset A depends on Asset B. The structure at the right represents the situation after debt retirement.
As an example of a favorable implication, consider software remodularization. Suppose we have a software asset A that depends on another software asset B. As shown in the left image of the figure, asset A, of which there are many copies, bears two classes of technical debt, D1 and D2. As shown, there is only one copy of asset B. Suppose further that an asset that bears debt D2 also bears debt D1, but an asset that bears D1 might or might not bear debt D2.

To retire D2, engineers modified B by assigning it responsibility for the tasks that formerly bore debt D2. After this change, B bears debt of type D1. Next, they retired debt D2. The right half of the figure shows the result. The system still bears debt D1. But now it’s inside B instead of A. Those modifications relieve all instances of A of both types of debt. The result is that D2 vanishes, and only a single instance of D1 remains. In this way, retiring debt D2 has reduced the MICs and MPrin for D1.

Policymakers can help

Exploiting the salutary opportunities of this property of technical debt provides an example of the risks of adhering too closely to the financial model of debt.

Many different scenarios have the property that retiring one kind of technical debt can reduce the MICs associated with other kinds. Technologists understandably tend to be more concerned with technical debt retirement strategies that emphasize short-term improvement of their own productivity. That’s why it’s so important for policymakers to provide guidance that steers the organization in the direction of enterprise benefits.

References

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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MICs on technical debt can be difficult to measure

Last updated on July 8th, 2021 at 12:48 pm

For financial debts, creditors regularly inform debtors of interest charges, principal remaining, and other loan parameters. Laws usually require reports and explicit statements about interest charges. By contrast, for technical debt, MICs can be difficult to compute with useful precision, even if we know they’re accumulating. Many decision makers are actually unaware that MICs are accumulating. For an organization to appreciate the full financial consequences of carrying technical debt, everyone in the enterprise must appreciate the concept of MICs.

The heart of the problem

A stack of floppy disks
A stack of floppy disks. You don’t see many of these around much anymore. Very little of the software or hardware we use is as obsolete as these floppies. But much of it is obsolete, and it therefore comprises technical debt. It still works, but it’s slow and probably out of support life. On the basis of speed alone, the MICs it incurs can easily justify replacement. And some of it is vulnerable to cyberattack. One significant breach can ruin a brand.
Unlike financial debt, for technical debt there are no legally required reports or disclosures. We can sometimes estimate MICs, but most organizations don’t track the data necessary to estimate MICs with useful precision. Indeed, developing useful estimates is often technically impossible.

The difficulty of measuring MICs arises from three sources. First, people whose productivity is most directly affected by technical debt—usually engineers—often have difficulty determining with precision the extent of the impact of technical debt on their efforts.

Second, many people are unaware of the impact technical debt has on their results. For example, if a product arrives late to market, we could compute the financial costs attributable to technical debt if we knew that technical debt is partially—or wholly—responsible for the delay. Too often, those who could perform such calculations aren’t sufficiently familiar with the concept of MICs. In any case, the data they would need for calculating a useful estimate is rarely available.

This brings us to the third source of difficulty.

The terrifying opportunity

Finally, a more insidious form of the consequences of technical debt is what we might call the terrifying opportunity. This situation arises when the organization rejects (or fails to recognize) a market opportunity because exploiting it would involve modifying an existing asset. The modification is terrifying because the asset harbors a heavy load of technical debt. The debt causes decision makers to assess that the probability of success is so low that the opportunity seems terrifying. They therefore reject the opportunity. Typically, terrifying opportunities would be exploitable if the debt-bearing assets didn’t exist at all. Then we would be starting fresh. But when opportunities require modifying assets that bear technical debt, commitment requires faith that we can address the technical debt successfully.

The sense of risk isn’t a reflection on the capabilities of the technical organization. Rather, it’s a result of the challenges involved in working with assets that bear high levels of technical debt. Given past performance of the technical organization relative to these debt-bearing assets, success can seem unlikely.

Computing the cost of a terrifying opportunity requires estimating the cost of not exploiting the opportunity, a difficult task in the best of circumstances. But whatever that cost is, it’s a form of MICs that we rarely recognize.

Last words

Building expertise in estimating MICs in all their forms is advantageous to any organization that seeks to make its technical debt more manageable. By making MICs visible, we can bring about better recognition of the cost of carrying technical debt, thereby providing an appropriate motivator for retiring technical debt.

References

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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MICs can sometimes be deferred or advanced without penalty

Last updated on July 7th, 2021 at 03:11 pm

A rehabilitated Green Line car of the Massachusetts Bay Transit Authority
A rehabilitated Green Line car of the Massachusetts Bay Transit Authority. Trolley cars still travel on surface streets in and around Boston, in medians of divided roadways. Many streets still contain buried trolley tracks. They comprise a technical debt. MICs continue to accrue due to a near-continuous need to patch roadways. The need arises because of surface decomposition from the freeze-thaw cycle and small movements of buried tracks under traffic loads. A recent sewer upgrade project in Cambridge required removal of buried tracks to replace an old sewer line. This presented an opportunity to defer street surface maintenance (MICs) to take advantage of the surface rebuilding that was included in the sewer project. I don’t know whether the city actually exploited that opportunity.

Although rescheduling financial interest payments is possible only by special arrangement, or in bankruptcy, we can often defer or advance MICs on technical debt by rescheduling work that might incur them. For some kinds of technical debt, MICs accumulate only if we perform engineering work that involves that debt. This property is especially useful when we plan to retire an asset that bears technical debt. When we remove the asset from service, the technical debt it carries vanishes.

For most conventional financial debts, interest charges accumulate until we retire the debt. Interest charges might be zero for some time periods, but they’re never negative. Failure to meet the contractual payment schedule can result in penalties and additional interest charges.

MICs are different from financial interest charges

For technical debt, we can sometimes defer or advance MICs without penalty. We can arrange to temporarily nullify the MICs on a particular class of technical debt, or particular instances of that class. To do so, we need only reschedule a project or projects. This is possible when MICs accrue only if there is a need to perform work on the assets that carry the debt. In a given fiscal period, if we perform no work on those assets, the MICs can be zero. By scheduling projects accordingly, we can arrange for MICs to be zero.

There is one caveat. As I mentioned in “Debt contagion: how technical debt can create more technical debt,” as long as a particular class of technical debt remains in place, its associated MPrin might increase. Deferring retirement of a class of technical debt can be wise only if we can control its associated MPrin or if changes in its MPrin are acceptable.

References

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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MICs can differ for different instances of the same kind of technical debt

Last updated on July 8th, 2021 at 12:46 pm

For financial debts, the interest charges associated with a unit of debt are (usually) the same for every unit of debt incurred under the same loan agreement. But for technical debt, the MICs associated with a given instance of a class of technical debt might differ from the MICs associated with any other instance of the same class of technical debt. They can differ even if we incurred those instances of technical debt at the same time. And they can differ even if they formed as results of a single decision or sequence of events. Unlike the transactions on a credit card, the interest charges can vary for instances of the same kind of technical debt.

Why MICs can differ from instance to instance

Collapse of the I-35W bridge in Minneapolis, Minnesota
The I-35W Bridge collapse, day 4, Minneapolis, Minnesota, August 5, 2007. Underweight gusset plate design made the bridge vulnerable due to the increased static load from concrete road surfacing additions. And it was especially vulnerable due to the weight of construction equipment and supplies during a repair project that was then underway. But the root cause of the failure was that the bridge was “fracture critical.” It was vulnerable to collapse if any one of a set of critical bridge members failed. The 18,000 fracture critical bridges in the U.S. were built (or are being built) because they’re cheaper than are bridges that have zero fracture critical members [CBS News 2013]. Expedient shortcuts are among the most prolific generators of technical debt. For bridges, the MICs could include inspections, repairs, and temporary closures for inspections and repairs. Variations of design from bridge to bridge clearly could create variations in MICs from bridge to bridge. Photo by Kevin Rofidal, United States Coast Guard,  courtesy Wikimedia Commons.
For most financial debts, a single algorithm determines the interest charges for every unit of a particular class of debt. Following the technical debt metaphor, people tend to assume that the MICs on every instance of a particular class of technical debt are uniform across the entire class.

But in practice, uniformity assumptions with regard to MICs are generally invalid. Given two different instances of the same kind of technical debt, the MICs associated with modifying asset components in and around those two instances can differ significantly. For any given instance of a particular class of technical debt, MICs can depend on whether engineers must interact with that part of the asset. And when they do interact with a given asset component, MICs can also depend upon the transparency and condition of that asset component.

Two examples illustrating varying MICs

For example, an instance of technical debt might reside in a setting that relatively few local experts understand. The people who are capable of doing that work might be in high demand, or heavily committed, or expensive. Subsequent scheduling difficulty can lead to delays or service interruptions associated with completing the required work. That can result in lost revenue, which also contributes to MICs. Meanwhile, instances of the same kind of technical debt residing in other parts of the asset might be addressable by less expert staff. They might be in lesser demand, and less well compensated. Service interruptions might be shorter, and lost revenue less. The MICs associated with these two cases can therefore differ significantly.

As a second example, consider documentation deficits. Suppose an engineer needs documentation to determine how to proceed, and that documentation doesn’t exist. The engineer must then resort to alternatives that might be more time-consuming. He or she might read code or specifications, or interview colleagues. But for two instances of the same kind of technical debt, the need to refer to documentation can differ. The engineer might need documentation for one instance in one part of the asset, but not for another.

Last words

Another form of documentation deficit can be especially costly. Suppose engineers need documentation, and it does exist, but it’s out of date or incorrect. Those engineers might make costly, potentially irreversible errors when they undertake maintenance or extension activity. When testing uncovers the defects the engineers unwittingly introduced due to the defective documentation, the damage is less. But if testing doesn’t catch the defects, they might somehow find their way into production. If they do, the revenue or liability impact can be substantial. And the impact can vary from instance to instance of the technical debt in question. These effects are all forms of MICs.

So MICs can vary almost on an instance-by-instance basis. Or they might be constant across instances. It’s difficult to say. But the easy assumption—that MICs are the same for all instances of a given class of technical debt—the easy assumption is probably incorrect.

References

[CBS News 2013] CBS News and the Associated Press. “Thousands of U.S. bridges vulnerable to collapse,” May 25, 2013.

Available: here; Retrieved: November 29, 2017

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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MICs on technical debt can be unpredictable

Last updated on July 8th, 2021 at 12:44 pm

Few senior management teams would seriously consider making decisions about financial instruments without carefully estimating their effects on revenue and expenses. Most enterprises support decision makers with an impressive array of tools, historical data, and skilled financial professionals. Yet few organizations invest at similar levels to support estimators of the MICs involved in undertaking engineering efforts. A similar dearth of resources affects those who estimate the effects on revenue due to carrying technical debt.

A composite satellite view of Antarctica
A composite satellite view of Antarctica. Composite by Dave Pape using NASA’s Blue Marble data set. Exploring unknown territory, as Roald Amundsen did in 1911-12, is far more difficult and riskier than exploring mapped territory. For this reason, managing technical debt is more successful when we have even minimal capability for estimating the MICs of carrying technical debt. Courtesy Wikimedia Commons.
A resource shortage of this kind can have starkly negative effects. The inherent difficulties of projecting the effects of both carrying and retiring technical debt create uncertainties in project budgets and schedules.

MICs can fluctuate dramatically depending on a range of factors. These factors include:

  • The kind of work underway on the asset that carries the debt
  • How the debt affects customers and what they’re doing at any given time
  • The difficulty of researching engineering problems arising from the debt
  • The loss of revenue due to debt-related delays in reaching the market
  • A loss of sales due to semi-catastrophic failures in customer demonstrations

In short, MICs are often unpredictable [Allman 2012].

The state of the art

Most of the research into the effects of carrying or retiring technical debt has focused on engineering activity, and specifically, software engineering activity [MacCormack 2016] [Kamei 2016]. By comparison, research has been less intensive for effects on other activities—marketing, sales, regulatory compliance, to name a few. And in many cases, the effects of technical debt on these other activities are the most significant.

Consider first the effect of technical debt on enterprise expenses. The kind of maintenance and enhancement work performed on a set of assets bearing technical debt can determine the depressive effect on productivity. And declines in productivity directly affect MICs. In many cases, projecting future MICs associated with any given class of technical debt can be difficult. The difficulty arises because we might not know with sufficient certainty what projects will be active in the intermediate term or long term future, and what kind of work those projects will undertake. Even when we do know these things, the level of involvement with instances of particular classes of technical debt can be difficult to project enough certainty to be useful.

Turning to revenue, for most organizations, the picture is also bleak. Because we can’t retire some classes of technical debt incrementally, retirement projects can have significant impact on operations and revenue. Research in this area is even more limited than in the area of effects on productivity.

Last words

Projecting MICs with useful accuracy would be a valuable capability. Making MICs more predictable would require systematically gathering data and building expertise for projecting MICs for your enterprise. That problem is more tractable than the more general problem of projecting MICs absent specific knowledge of enterprise characteristics.

An enterprise-specific MICs projection capability could elevate the quality of decisions regarding resource allocation for projects of all kinds, including technical debt retirement projects. Policymakers can play an important advocacy role in establishing such a capability.

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:

[CBS News 2013] CBS News and the Associated Press. “Thousands of U.S. bridges vulnerable to collapse,” May 25, 2013.

Available: here; Retrieved: November 29, 2017

Cited in:

[Kamei 2016] Yasutaka Kamei, Everton Maldonado, Emad Shihab, and Naoyasu Ubayashi. “Using Analytics to Quantify the Interest of Self-Admitted Technical Debt,” 1st International Workshop on Technical Debt Analytics (TDA 2016), 68-71.

Available: here; Retrieved: November 28, 2017

Cited in:

[MacCormack 2016] Alan MacCormack and Daniel J. Sturtevant. “Technical debt and system architecture: The impact of coupling on defect-related activity,” The Journal of Systems and Software 120, 170–182, 2016.

Available: here; Retrieved: November 19, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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MICs can fluctuate dramatically

Last updated on July 8th, 2021 at 11:54 am

A common assumption vis-à-vis technical debt is that we can model its productivity-depressing and velocity-reducing effects. We model them as the “interest” on the technical debt (MICs). And we assume that MICs are relatively constant over time. In practice, MICs can fluctuate dramatically. Those fluctuations provide planners valuable insight and flexibility, if they choose to use it. Unfortunately, most plans I have seen make the assumption that MICs are relatively stable.

An example of MICs behavior

30-year average fixed mortgage rates in the United States, 2012-2017
30-year average fixed mortgage rates in the United States, 2012-2017, in %. Over this five-year period, rates did fluctuate. But they did so in a narrow range of from 3.3% to just over 4.5%. When we speak of “interest,” we evoke an impression of relative stability. This happens even when we’re speaking of technical debt. MICs for technical debt can vary from 0 to well above MPrin in any given time period. That’s one thing that makes the term “interest” so misleading in the context of technical debt. Data provided by U.S. Federal Reserve Bank of St. Louis [Federal Reserve 2017].
As an example of this assumption is available in a paper by Buschmann [Buschmann 2011b]. He states that the longer we wait to retire technical debt in design and code, the larger the amount of interest. This presumes constant or non-negative MICs. That assumption that might be valid for some situations, but it isn’t universally applicable.

Consider a project that entails maintenance or extension of parts of the system that don’t manifest a specific class of technical debt. And suppose that the assets in question don’t depend on elements that do manifest that debt. Such a project is less likely to incur the MICs associated with that debt. So with respect to any particular class of technical debt, there might be time periods in which no projects incur MICs. During those periods, the interest accrued can be zero. In other time periods, the interest accrued on account of that same class of technical debt could be very high indeed.

These effects are quite apart from the tendency of MPrin to grow with time, as we noted in an earlier post (see “Debt contagion: how technical debt can create more technical debt”).

Last words

A capacity for projecting MICs associated with a particular class of technical debt can be useful to planners as they work out schedules for maintenance projects, development projects, and technical debt retirement projects. Technical debt retirement projects are also subject to MICs, including from classes of technical debt other than the debt they’re retiring.

Analogous to the functioning of governance boards, a technical debt resources board could provide resources for evaluating assessments of likely MICs for maintenance projects, development projects, and technical debt retirement projects. Decision makers could use these assessments when they set priorities for these various efforts. I’ll say more about technical debt resources boards in future posts.

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:

[Buschmann 2011b] Frank Buschmann. “To Pay or Not to Pay Technical Debt,” IEEE Software, November/December 2011, 29-31.

Available: here; Retrieved: March 16, 2017.

Cited in:

[CBS News 2013] CBS News and the Associated Press. “Thousands of U.S. bridges vulnerable to collapse,” May 25, 2013.

Available: here; Retrieved: November 29, 2017

Cited in:

[Federal Reserve 2017] Federal Reserve Bank of St. Louis. “30-Year Fixed Rate Mortgage Average in the United States (MORTGAGE30US).” Weekly time series.

Available: here; Retrieved: November 25, 2017.

Cited in:

[Kamei 2016] Yasutaka Kamei, Everton Maldonado, Emad Shihab, and Naoyasu Ubayashi. “Using Analytics to Quantify the Interest of Self-Admitted Technical Debt,” 1st International Workshop on Technical Debt Analytics (TDA 2016), 68-71.

Available: here; Retrieved: November 28, 2017

Cited in:

[MacCormack 2016] Alan MacCormack and Daniel J. Sturtevant. “Technical debt and system architecture: The impact of coupling on defect-related activity,” The Journal of Systems and Software 120, 170–182, 2016.

Available: here; Retrieved: November 19, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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Cited in:

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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:

[Buschmann 2011b] Frank Buschmann. “To Pay or Not to Pay Technical Debt,” IEEE Software, November/December 2011, 29-31.

Available: here; Retrieved: March 16, 2017.

Cited in:

[CBS News 2013] CBS News and the Associated Press. “Thousands of U.S. bridges vulnerable to collapse,” May 25, 2013.

Available: here; Retrieved: November 29, 2017

Cited in:

[Federal Reserve 2017] Federal Reserve Bank of St. Louis. “30-Year Fixed Rate Mortgage Average in the United States (MORTGAGE30US).” Weekly time series.

Available: here; Retrieved: November 25, 2017.

Cited in:

[Kamei 2016] Yasutaka Kamei, Everton Maldonado, Emad Shihab, and Naoyasu Ubayashi. “Using Analytics to Quantify the Interest of Self-Admitted Technical Debt,” 1st International Workshop on Technical Debt Analytics (TDA 2016), 68-71.

Available: here; Retrieved: November 28, 2017

Cited in:

[MacCormack 2016] Alan MacCormack and Daniel J. Sturtevant. “Technical debt and system architecture: The impact of coupling on defect-related activity,” The Journal of Systems and Software 120, 170–182, 2016.

Available: here; Retrieved: November 19, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

Order from Amazon

Cited in:

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How financial interest charges differ from interest charges on technical debt

Last updated on July 7th, 2021 at 02:55 pm

Credit cards also have interest charges
Credit cards. Revolving unsecured charge accounts are perhaps the most familiar form of financial debt. They do have one thing in common with technical debt: with either one, getting into debt over your head is easy.

Second only to the term debt, the term interest is perhaps the most common financial term in the technical debt literature. In the financial realm, interest charges are the cost of using money. Usually, we express interest charges as a percentage rate per unit time. By contrast, metaphorical interest charges (MICs) on technical debt work differently. Failure to fully appreciate that difference can create problems for organizations as they try to manage their technical debt.

The notion of interest is deep in our culture. We understand it well. But the way we understand it corresponds to fixed or slowly varying interest rates. This understanding biases our perception of technical debt.

The root of the problem

Because we’re so familiar with financial interest, we perceive the elements of technical debt as imposing a cost that’s a relatively stable fraction, per fiscal period, of the initial MPrin. This belief doesn’t correspond to the reality of technology-based systems, which are the targets of the technical debt metaphor.

MICs on technical debt differ from the interest on financial debt in two ways.

  • MICs depend strongly on whether and how the people of the enterprise interact with the assets bearing the technical debt.
  • The MICs on technical debt include the value of opportunities lost (opportunity costs). These losses are due to depressed productivity and reduced organizational agility.

Neither of these factors has a financial analog. In finance, interest charges depend solely on a mathematical formula involving the interest rate and principal.

Last words

In the next few posts, I’ll explore the properties of metaphorical interest charges. This investigation helps clarify how they differ from financial interest charges. It also clarifies how that difference contributes to difficulties in managing technical debt.

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:

[Buschmann 2011b] Frank Buschmann. “To Pay or Not to Pay Technical Debt,” IEEE Software, November/December 2011, 29-31.

Available: here; Retrieved: March 16, 2017.

Cited in:

[CBS News 2013] CBS News and the Associated Press. “Thousands of U.S. bridges vulnerable to collapse,” May 25, 2013.

Available: here; Retrieved: November 29, 2017

Cited in:

[Federal Reserve 2017] Federal Reserve Bank of St. Louis. “30-Year Fixed Rate Mortgage Average in the United States (MORTGAGE30US).” Weekly time series.

Available: here; Retrieved: November 25, 2017.

Cited in:

[Kamei 2016] Yasutaka Kamei, Everton Maldonado, Emad Shihab, and Naoyasu Ubayashi. “Using Analytics to Quantify the Interest of Self-Admitted Technical Debt,” 1st International Workshop on Technical Debt Analytics (TDA 2016), 68-71.

Available: here; Retrieved: November 28, 2017

Cited in:

[MacCormack 2016] Alan MacCormack and Daniel J. Sturtevant. “Technical debt and system architecture: The impact of coupling on defect-related activity,” The Journal of Systems and Software 120, 170–182, 2016.

Available: here; Retrieved: November 19, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

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Cited in:

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