Self-sustaining technical knowledge deficits during contract negotiations

Enterprises that grow by acquisition find themselves acquiring the technological assets of the organizations they acquire. And most enterprises acquire technological assets by other means as well. In either case, the contract negotiation teams need technical knowledge to evaluate and project the effects of these acquisitions on total enterprise technical debt. But as total enterprise technical debt grows, the capacity of enterprise technologists to support new contract negotiations declines, which leads to a self-sustaining cycle of technical knowledge deficits. Policymakers and strategic planners are likely the most effective possible advocates for breaking the cycle by hiring more technologists.

Avoid technical knowledge deficits in important contract negotiations
Contract negotiations can be complex

Negotiating contracts with vendors that provide outsourcing services or subcontracting work, or with organizations to be acquired, requires a sophisticated appreciation of the technical debt status of the assets acquired or to be acquired. The technical debt in question includes more than just the debt borne by the asset as it stands in its pre-acquisition context. It also includes the debt that the asset will carry after it’s inserted into the asset portfolio of the acquiring enterprise.

These two debts — pre-acquisition and post-acquisition — can differ, because the interfaces, standards, and approaches of the acquiring organization likely differ from those prevailing within the vendor organization or the acquired organization. Knowledge of the interfaces, standards, and approaches of both parties to the transaction is therefore required to make a valid assessment of the total post-acquisition levels of technical debt.

The enterprise negotiation team therefore requires the services of technologists who are familiar with the maintenance, extension, and cybersecurity work that will be performed on the acquired assets post-acquisition. When the technical debt situation in the enterprise reaches a level so serious that it requires the full attention of all available technologists, they cannot be spared for negotiating contracts. If this happens, then contract negotiation teams could experience a deficit of knowledge concerning the consequences of acquiring assets laden with technical debt. That leads to increasing levels of non-strategic technical debt, which then has the potential to exacerbate the technical knowledge deficit for the negotiating teams.

This situation is an example of what’s commonly called a vicious cycle. After technical debt has reached a critical level, there are really only two tactics that can break the cycle — get more engineers, or suspend some work.

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Where the misunderstandings about MICs come from

The differences between technical debt and financial debt are numerous and significant, and often overlooked, in part, because of the metaphor itself. Attempting to manage technical debt as one 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 reduce the costs of both carrying and retiring technical debt. More important are the opportunities lost or unrecognized because of reticence about addressing the technical debt to the extent necessary if we were to exploit those opportunities.

The right tool for the wrong job
Managing technical debt by using approaches that work well for financial debt is analogous to using the right tool for the wrong job.

The debt metaphor itself is probably at the root of the misalignment between the conventional concept of fixed or slowly varying interest rates and the reality of loss of enterprise agility or lost revenue due to technical debt. 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.

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 undertaken on the assets that carry the debt. This fact is a source of flexibility useful for planning technical debt management programs, which can exploit it to set priorities for debt retirement and debt prevention efforts. That flexibility implies, for instance, that planning technical debt retirement programs to satisfy the urge to retire all instances of a given class of technical debt might not be sensible.

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

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MICs can change when other debts are retired

The metaphorical interest charges (MICs) and metaphorical principal (MPrin) of a particular class of technical debt can change as a result of retiring other seemingly unrelated classes of technical debt. In most cases, engineering expertise is required to determine technical debt retirement strategies that can exploit this property of some kinds of technical debt.

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.

Decision-makers who understand the world of financial instruments at a very sophisticated level might tend to overvalue arguments favoring technical debt management in ways analogous to the ways we manage financial debts. Financial sophisticates might find appealing any argument for a technical debt management program that parallels financial approaches. Such programs are unlikely to work, for two reasons. First, as we’ve already noted, the uncertainties associated with estimating MPrin and MICs 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, as noted above, the familiar concept of interest rate is inapplicable to technical debt, because the MICs depend on the degree of interaction between ongoing activities and the debt itself, 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 class of technical debt 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 a different kind of technical debt. 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 debt D1 and D2, respectively. 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 have decided to modify B by having it assume responsibility for the tasks that formerly bore debt type D2. They do this even though, as a consequence of this change, B will now bear debt of type D1. Next, debt type D2 is retired. The right half of the figure shows the resulting implementation. The system still bears debt D1, but now it’s located in B instead of A. All instances of type A assets change, and those modifications relieve them of both types of debt. This is a sensible approach, because there are several assets of type A and only one of type B. The end 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 of debt. Because technologists understandably tend to be more concerned with technical debt retirement strategies that emphasize short-term improvement of their own productivity, policymakers can provide guidance that steers the organization in the direction of enterprise benefits.

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MICs on technical debt can be difficult to measure

For a financial debt, creditors regularly inform debtors of periodic interest charges, principal remaining, and other parameters of the loan. In many cases, laws require regular reports and explicit statements about interest charges when prospective creditors interact with prospective debtors. By contrast, for technical debt, MICs can be difficult to compute with useful precision, even if we know that they’re accumulating. Many decision-makers are actually unaware that MICs are accumulating at all. For an organization to appreciate the full financial consequences of carrying technical debt, everyone in the enterprise must appreciate the concept of MICs.

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 no longer supported by its manufacturer. 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, the financial costs attributable to technical debt can be computed if we realize 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, and in any case, the data they would need for calculating a useful estimate is rarely available.

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 or product offering that harbors a heavy load of technical debt. The debt causes decision-makers to assess that the probability of success is so depressed by technical debt that the opportunity seems terrifying, and they therefore reject the opportunity. Typically, terrifying opportunities would be exploitable if the debt-bearing assets didn’t exist at all, because then we would be starting fresh. But given that terrifying opportunities require modifying existing assets that bear heavy loads of technical debt, commitment requires faith that the technical debt can be addressed successfully.

The sense of risk isn’t a reflection on the capabilities of the technical organization. Rather, it is 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.

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.

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MICs can sometimes be deferred or advanced without penalty

Although rescheduling interest payments on financial debts is possible only by prearrangement, by special arrangement, or in bankruptcy, MICs on technical debt can often be deferred or advanced by simply rescheduling any work that might incur them. This is possible because, for some kinds of technical debt, MICs accumulate only if we perform engineering work that’s affected by that debt. This property is especially useful when we plan to retire an asset that bears technical debt, because when it’s removed from service, the technical debt it carries vanishes.

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 Boston, but the only active lines are in medians of divided roadways. Many streets in and around Boston still contain buried trolley tracks. They comprise a technical debt, and MICs continue to accrue in the form of broken pavement and a near-continuous need to patch roadways, due to surface decomposition from the freeze-thaw cycle and the constant small movements of the buried tracks due to traffic loads. A recent sewer upgrade project in Cambridge required removal of buried tracks to remove and replace the 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, though I don’t know whether that opportunity was actually exploited.

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

But at times, for technical debt, MICs can be deferred or advanced without penalty and without additional “interest charges.” In other words, the organization can arrange to temporarily nullify the MICs on a particular class of technical debt, or for particular instances of that class, by simply rescheduling a project or projects. This is possible when the nature of the debt is such that MICs accrue only if there is a need to perform work on assets that are affected by the debt in question. In a given fiscal period, if no work is performed on those assets, the MICs can be zero. By scheduling projects accordingly, organizations can arrange for MICs to be zero.

There is one caveat. As discussed in “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 is wise only if its associated MPrin is controlled or if projected changes in its MPrin are acceptable.

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

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, even if those instances of technical debt were incurred at the same time as a result of a single decision or sequence of events.

Collapse of the I-35W bridge in Minneapolis, Minnesota
The I-35W Bridge collapse, day 4, Minneapolis, Minnesota, August 5, 2007. The proximate cause of the collapse was underweight gusset plate design, which made the bridge vulnerable to the increased static load due to concrete road surfacing additions over the years, and 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 design of the bridge was “fracture critical,” meaning that it was vulnerable to collapse if any one of a set of critical bridge members failed. There are 18,000 fracture critical bridges in the U.S. today, and more are under construction. They were built (and are being built) because they’re cheaper to build than are bridges that have zero fracture critical members [CBS News 2013]. Engineering practices like this—expedient shortcuts—are among the most prolific generators of technical debt. The MICs in the case of bridges could include inspections, repairs, and temporary closures for inspections and repairs. Variations in bridge design and usage clearly could create variations in MICs from bridge to bridge. Photo by Kevin Rofidal, United States Coast Guard,  courtesy Wikimedia Commons.

Here’s why.

For most financial debts, a single algorithm determines the interest charges for every unit of a particular class of financial 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 asset base.

But in practice, uniformity assumptions with regard to MICs are generally unwarranted. Given two different manifestations 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 or not 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.

For example, an instance of technical debt might reside in a portion of the system 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, who 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. If an engineer needs access to documentation to determine how to proceed with a task, and that documentation doesn’t exist, the engineer must resort to alternatives that might be more time-consuming, such as reading code or specifications, or interviewing colleagues. But for two given instances of the same kind of technical debt, the need to refer to documentation can differ. Documentation might be needed for one instance in one part of the asset, but not for another.

Another form of documentation deficit can be especially costly. If documentation is needed, and it does exist, but it’s outdated or incorrect, engineers who rely on that documentation might make costly, potentially irreversible errors when they undertake maintenance or extension activity. A less-damaging case is one in which testing uncovers the defects they unwittingly introduced due to the defective documentation. But if the defects aren’t caught in testing, and if those defects somehow find their way into production, the revenue or liability impact can be substantial, and it 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

Few senior management teams would seriously consider making decisions about the use of financial instruments without first developing careful estimates of their effects on revenue and expenses. In most enterprises, there is an impressive array of tools, historical data, and skilled financial professionals to support those who devise or specify financial instruments for use in financing the enterprise. Yet few organizations invest at similar levels to support those who make estimates of the MICs involved in undertaking engineering efforts. A similar deficit of resources affects those who make estimates of 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 Amundsen did in 1911-12, is far more difficult and far riskier than exploring mapped territory. For this same reason, managing technical debt is likely to be more successful when we have even minimal capability for estimating the MICs associated with carrying or retiring technical debt. Courtesy Wikimedia Commons.

This resource shortage has starkly negative effects, because of the inherent difficulties associated with projecting the effects of both carrying and retiring technical debt.

Although there can be a cost associated with carrying technical debt—I call them MICs—the cost can fluctuate dramatically depending on a range of factors, such as the kind of work underway on the asset that carries the debt; how customers are affected and what they’re doing at any given time; the difficulty of researching engineering problems arising from the debt; loss of revenue due to debt-related delays in reaching the market; loss of sales due to semi-catastrophic failures in customer demonstrations; and much more. In short, the MICs are often unpredictable [Allman 2012].

Moreover, 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]. Effects on other activities—marketing, sales, regulatory compliance, to name a few—are, by comparison, largely unstudied. And in many cases, the effects 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 extent to which productivity is depressed, in turn affecting the MICs. In many cases, projecting future MICs associated with any given class of technical debt can be difficult because we might not know with sufficient certainty what projects will be undertaken 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 with a degree of certainty consistent with most other estimates.

Turning to revenue, for most organizations, the picture is also bleak. Because some classes of technical debt cannot be retired incrementally, attempts to retire them can have significant impact on operations and revenue. Research in this area is even more limited than in the area of effects on productivity.

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] Allman, Eric. “Managing Technical Debt: Shortcuts that save money and time today can cost you down the road,” ACM Queue, vol 10 issue 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] MacCormack, Alan, and Daniel J. Sturtevant. “Technical debt and system architecture: The impact of coupling on defect-related activity,” The Journal of Systems and Software 120 (2016) 170–182.

Available: here Retrieved: November 19, 2017.

Cited in:

Related posts

MICs can fluctuate dramatically

A common assumption vis-à-vis technical debt is that its productivity-depressing and velocity-reducing effects, usually regarded as interest on the technical debt, can be modeled as relatively constant over time. In practice, the magnitude of these effects can vary dramatically with time, and that variation provides planners valuable insight and flexibility.

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, although the rate did fluctuate, it did so in a narrow range of 3.3% to just over 4.5%. When we speak of “interest,” we tend to evoke an impression of relative stability, even when we’re speaking of technical debt, where MICs 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, Buschmann states that the longer we wait to retire technical debt in design and code, the larger the amount of interest [Buschmann 2011]. This presumes constant, or at least non-negative, metaphorical interest charges, an assumption that might be valid for some situations, but which is not universally applicable. Those projects that entail maintenance or extension of parts of the system that don’t manifest a specific class of technical debt, and which don’t depend on elements that do manifest it, are much less likely to incur the MICs associated with that debt. So with respect to any particular class of technical debt, during time periods in which no projects incur MICs, the interest accrued in those periods 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 “How technical debt can create more technical debt”).

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

Available: here Retrieved: March 16, 2017

Cited in:

[Buschmann 2011] Buschmann, Frank. “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] MacCormack, Alan, and Daniel J. Sturtevant. “Technical debt and system architecture: The impact of coupling on defect-related activity,” The Journal of Systems and Software 120 (2016) 170–182.

Available: here Retrieved: November 19, 2017.

Cited in:

Related posts

The concept of MICs

Using the term interest to refer to the metaphorical interest charges that are associated with 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 are  accumulated 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 borne by the enterprise as a consequence of 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 six 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] Allman, Eric. “Managing Technical Debt: Shortcuts that save money and time today can cost you down the road,” ACM Queue, vol 10 issue 3, March 23, 2012.

Available: here Retrieved: March 16, 2017

Cited in:

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

Available: here Retrieved: March 16, 2017

Cited in:

[Buschmann 2011] Buschmann, Frank. “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] MacCormack, Alan, and Daniel J. Sturtevant. “Technical debt and system architecture: The impact of coupling on defect-related activity,” The Journal of Systems and Software 120 (2016) 170–182.

Available: here Retrieved: November 19, 2017.

Cited in:

Related posts

How financial interest charges differ from interest charges on technical debt

Second only to the term debt, the term interest is perhaps the most common financial term in the literature of technical debt. In the financial realm, interest charges are the cost of using money, usually expressed as a percentage rate per unit time.

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, it’s easy to get into debt over your head.

The notion of interest is deep in our culture. People understand it well, but the way they understand it corresponds to interest rates that are fixed, or at worst relatively slowly varying. This understanding creates a bias in the way we understand technical debt, in the sense that we perceive the elements of technical debt as imposing a cost that is 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. Formulating sound technical debt policy depends on understanding the nature of the difference between interest on financial debt and the metaphorical interest charges associated with technical debt.

There are two fundamental reasons why metaphorical interest charges on technical debt differ from the interest on financial debt.
  • Metaphorical interest charges depend strongly on whether and how the people of the enterprise interact with the assets bearing the technical debt.
  • The metaphorical interest charges on technical debt include the value of opportunities lost to the enterprise (opportunity cost) due to depressed productivity and reduced organizational agility.

Neither of these factors has a direct analog in the financial context. In finance, the interest charges depend solely on a mathematical formula based on the interest rate and the size of the principal.

In the next few posts we’ll explore the properties of metaphorical interest charges. This investigation will help clarify how they differ from financial interest charges, and how that difference contributes to difficulties in managing technical debt.

References

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

Available: here Retrieved: March 16, 2017

Cited in:

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

Available: here Retrieved: March 16, 2017

Cited in:

[Buschmann 2011] Buschmann, Frank. “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] MacCormack, Alan, and Daniel J. Sturtevant. “Technical debt and system architecture: The impact of coupling on defect-related activity,” The Journal of Systems and Software 120 (2016) 170–182.

Available: here Retrieved: November 19, 2017.

Cited in:

Related posts