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

Last updated on June 17th, 2021 at 07:49 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:

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MICs on technical debt can be unpredictable

Last updated on June 17th, 2021 at 02:00 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

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:

Related posts

MICs can fluctuate dramatically

Last updated on June 16th, 2021 at 04:28 pm

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

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:

Related posts

The concept of MICs

Last updated on June 16th, 2021 at 03:13 pm

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.

What exactly are “metaphorical interest charges?”

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.

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

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:

Related posts

How financial interest charges differ from interest charges on technical debt

Last updated on June 16th, 2021 at 12:43 pm

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.

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.

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

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:

Related posts

MPrin for missing or incomplete capability

Last updated on June 15th, 2021 at 11:31 am

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

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:

Related posts

MPrin when standards or regulations change

Last updated on June 16th, 2021 at 02:36 pm

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

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:

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

Available: here; Retrieved: November 22, 2017

Cited in:

Related posts

MPrin in platform component upgrades

Last updated on June 16th, 2021 at 08:45 am

The MPrin of technical debt that forms as a consequence of a platform component upgrade depends on how we incur the debt. If we incur the debt by installing the upgrade, and then perform only some of the work made necessary by the upgrade, then the MPrin is the total cost of performing the deferred work. If we incur the debt by deferring the upgrade, then the conventional definition of the MPrin has two components. The first is the cost of the upgrade, and the second is the cost of any work made necessary by the upgrade, but not performed.

Hold on—it’s not so simple

An aisle in the stacks of a library
An aisle in the stacks of a library. Some libraries are upgrading their book tagging systems from barcodes to RFID tags. This is essentially a platform upgrade. When they do convert, every item in their collections becomes an instance of technical debt until it’s tagged with an RFID. A tagging technician can process about 1,000 items per day [Boss 2011]. It’s a big job.

In this latter instance, MPrin can increase over time. Increases can occur if the following three-step sequence happens for either maintenance or enhancements. In step 1, we perform work in the environment of the obsolete platform component, but after deferring the upgrade. Step 2 is performance of the upgrade. In step 3, we must repeat the work we performed in step 1 because the step 1 version isn’t compatible with the upgrade. This situation can be even worse if we discover the need for step 3 as a result of operational failure after the upgrade. In that case, maintainers must investigate the failure first. And the failure might cause database contamination, which would also need remedying. These additional costs are actually part of the debt retirement effort for the debt incurred by deferring the upgrade, but we usually account for them—mistakenly—as routine operational expense.

Last words

Advance knowledge of what can go wrong is always a nice-to-have. Most of us try to acquire this knowledge before or as we plan our projects. And most of us can do better. Before you consider a plan complete, ask yourself if anyone else might have already tried something similar. If you can guess who that might be, contact him or her to find out how it went. No point repeating someone else’s mistakes.

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

Cited in:

[Boss 2011] Richard W. Boss, “RFID Technology for Libraries,” American Library Association, 2011.

Some libraries are upgrading their book tagging systems from barcodes to RFID tags—what is essentially a platform upgrade. When they do convert, every item in their collections becomes an instance of technical debt until it’s tagged with an RFID. A tagging technician can process about 1,000 items per day. It’s a big job. Available: here; Retrieved: November 21, 2017

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:

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

Available: here; Retrieved: November 22, 2017

Cited in:

Related posts

MPrin in a development project

Last updated on June 15th, 2021 at 07:29 pm

We usually regard the MPrin of new technical debt associated with a development project as the difference between the cost of implementing it sustainably and the cost of simply making it work. The effort saved by choosing the latter over the former is the initial MPrin of the technical debt.

The "basket bridge" of the Los Angeles Metro system
The “basket bridge” of the Los Angeles Metro system. Constructed by the Metro Gold Line Foothill Extension Construction Authority, and opened in 2012, it carries the Los Angeles to Pasadena Metro Gold Line light rail across the eastbound lanes of the I-210 Freeway. The rail line provides transport service to a ridership that had been driving or using bus service. Although the bus and rail aren’t exact duplicates of each other, there is enough overlap that bus ridership dropped significantly after the rail line opened. That drop created a technical debt in the bus system. Retiring that debt requires reducing, rescheduling and re-routing bus service [Broverman 2017].

For example, consider an enhancement project for an existing asset. After we achieve an operational capability, we might notice that we’ve duplicated some of the asset’s pre-existing functionality. The responsible debt-free approach has three stages. First, we eliminate the new and unnecessary duplicated capability. Next, we modify the asset to use the previously existing capability. Finally, we re-test the asset. The approach that generates new debt involves leaving the duplication in place.

Other generators of technical debt

In a closely related example, we might recognize that the duplicated functionality in the newly developed portion of the asset is superior to the pre-existing form elsewhere in the asset. We’d like to remove the pre-existing form and replace instances of that form with instances of the newly developed functionality. But that work is clearly outside the scope of the new development, and it must await budgetary authority before it can be undertaken. Consequently, it becomes technical debt for the larger asset.

As time passes, and the enterprise undertakes other development projects, the implementations of previous projects can accumulate additional technical debt. The more obvious mechanisms by which this occurs include defect discovery, customer requests for enhancements, the need to enhance cyberdefenses in response to new threats, or changes in law or regulation. Less obvious, but no less significant, are changes in markets, customer needs, and underlying technologies. All can contribute to technical debt formation

A final example

An example of a less obvious process might be insights gained in marketing one product (call it P1). Suppose those insights reveal an opportunity to introduce other related products—P2, P3, and P4—to form a suite. The latter products could employ some assets developed for P1, if the latter products had been constructed slightly differently. The changes required in P1 therefore constitute technical debt, because we would have been able to develop P2, P3, and P4 much more rapidly if we had recognized the opportunity earlier. The P1 changes then become technical debt. And if we pursue P2, P3, or P4 without first retiring that debt, the debt probably expands, because the subsequent products manifest it.

New product (or service) developments often generate these situations.

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

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[Boss 2011] Richard W. Boss, “RFID Technology for Libraries,” American Library Association, 2011.

Some libraries are upgrading their book tagging systems from barcodes to RFID tags—what is essentially a platform upgrade. When they do convert, every item in their collections becomes an instance of technical debt until it’s tagged with an RFID. A tagging technician can process about 1,000 items per day. It’s a big job. Available: here; Retrieved: November 21, 2017

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[Broverman 2017] Neal Broverman. “The Success of the Gold and Expo Lines Has Taken a Toll on Bus Ridership,” Los Angeles Magazine, March 30, 2017.

Available: here; Retrieved: November 21, 2017

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[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.

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[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

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[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.

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[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.

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

Available: here; Retrieved: November 22, 2017

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Related posts

Examples of MPrin in four scenarios

Last updated on June 15th, 2021 at 01:57 pm

Some examples might help to clarify the differences between the principal of financial debts and the MPrin of a technical debt. The examples to come in the next four posts illustrate the unique properties of MPrins of technical debts.

Technical debt can arise as a result of:
  • Changes internally within the enterprise
  • External environmental changes that directly affect existing assets
  • Changes in the competitive environment
  • Insights and changes in perception that lead to changes in objectives
  • Existing technical debt
  • Deferring decisions about almost anything

By contrast, we incur financial debt only as a result of decisions to incur financial debt.

The examples below illustrate some of these phenomena. For each one, the full post contains a more complete explanation.

Development projects

This example illustrates how technical debt can develop as a result of unanticipated insight regarding a marketing opportunity for a new product line. It shows how technical debt can arise independent of any decision made within the enterprise, and without any changes to assets of any kind. More: “MPrin in a development project

Platform component upgrades

We’ve already provided an example of technical debt arising from a platform upgrade. In this example, we show how deferring a platform upgrade creates new complications not present in the previous example, by illustrating how total MPrin can increase after the debt first forms. More: “MPrin in platform component upgrades

Standards or regulatory changes

Changes in standards or regulations, whether internal, industry-wide, or governmental, can create technical debt. In some cases, the enterprise might not even be aware of the new debt. More: “MPrin when standards or regulations change

Missing or incompletely implemented capability

When a capability is incompletely implemented, it’s clear that the part left undone constitutes technical debt. What is less clear is what happens when the capability implementation is halted or rescinded. Trying to avoid new technical debt can actually be the cause of new technical debt, albeit of a different kind. More: “MPrin for missing or incomplete capability

Whether or not any similar scenarios have happened in your organization, these discussions are helpful for gaining insight into what kinds of technical debt policies can assist your organization in managing its technical debt. Let me know if you have experience with situations in which problems can be traced, even if only in part, to treating technical debt as if it were financial debt.