The trap of elegantly stated goals

Last updated on January 10th, 2020 at 07:26 pm

For organizations, an elegantly stated goal is one that’s so clearly stated that anyone can understand it, remember it, and recite it to others. An example for technical debt management might be, “We’ll drive enterprise technical debt to zero over five years.” Or, “No project is finished if it increases the total volume of technical debt.” But when the goal pertains to solving a problem for which all solutions are messy, stating that goal elegantly risks becoming ensnared in what I call the trap of elegantly stated goals.

Rock cairns in a wilderness area
Rock cairns—also known as rock stacks—in a wilderness area. Some rock stacks in parks and wilderness areas serve a practical purpose as trail markers. But in recent decades, rock stacking has acquired the status of a fad. Rock stacks aren’t permanent—they use no glue, rings, or fasteners—but their presence does degrade the experience of the natural surroundings. The practice continues, in part, because many find the elegance of the structures appealing. As with elegantly stated goals, the elegance of rock stacks has a dark side.

Because elegant goal statements are so memorable and so repeatable, elegantly stated goals spread rapidly, especially if they’re even a bit inspirational. But elegantly stated goals become traps when they incorporate overly simplistic views of how to attain those goals.

And that often happens when technical debt is involved. Here are four guidelines that can help organizations avoid the trap of elegantly stated goals for technical debt.

Beware the halo effect

The halo effect [Thorndike 1920] is a cognitive bias [Kahneman 2011] that systematically skews our assessments of the qualities of a person, product, brand, company, or any entity, really. If our sense of one quality of the entity is positive, we’re more likely to assess as positive other qualities of that entity. Thus, the elegance of a goal statement can cause us to regard the goal as more desirable than we would if the goal were stated less elegantly. For example, the statement, “we will achieve zero technical debt in five years,” can increase the chances that we’ll believe that achieving such a goal is attainable. Indeed, some might not even question its desirability, let alone its attainability.

When devising goals for technical debt management, beware the halo effect. Always question desirability, taking costs and benefits into account.

Technical debt matters less than its metaphorical interest charges

The metaphorical interest charges (MICs) on technical debt, rather than the metaphorical principal (MPrin) of the debt itself, are what matter. A goal for total technical debt might be more elegant and more simply stated than would be a goal for technical debts that carry high MICs. But goals for total technical debt can lead to effort spent on debts with low MICs.  And those efforts produce little benefit.

When setting goals for technical debt management, pay attention to the MICs. Distinguish between low-MICs and high-MICs technical debt. Keep in mind that MICs can fluctuate. One kind of technical debt can be a low priority at one point in time, and a high priority at another.

Controlling technical debt is safer than trying to drive it to zero

Blind application of an elegantly stated goal can have strikingly silly unintended consequences. Keep in mind that the policymaker’s definition of technical debt is any technological element that contributes, through its existence or through its absence, to lower productivity, or depressed velocity, or a higher probability of defects.

Consider this example of strikingly silly unintended consequences for the goal of zero technical debt. An engineer creates an innovative and superior solution to a previously solved problem. Existing assets that incorporate the old solution are instantly outmoded by the innovative solution. Those existing assets now carry technical debt. If the enterprise directive mandates zero technical debt, some engineering managers might be tempted to do the unexpected. They might inhibit the kind of creativity that leads to innovative solutions to previously solved problems. The temptation arises because introducing those new solutions creates exogenous technical debt in existing assets. Therein lies the trap of the elegantly stated goal.

Throttling efforts to find innovative solutions to previously solved problems is one example of an unintended consequence of trying to drive technical debt to zero. Controlling technical debt is probably a safer option than trying to drive it to zero. With respect to technical debt, it would be wise to study the possible unintended consequences of elegantly stated goals before propagating those goals.

Get control of the behaviors that lead to technical debt

Technical debt management efforts typically emphasize technical debt retirement or engineering process improvement. While both activities are worthwhile, the root causes of the technical debt problem often lie elsewhere. See, for example, the thread in this blog exploring nontechnical precursors of technical debt.

For example, “across the board” cuts to project budgets can lead to technical debt formation as teams suspend efforts that would have already created technical artifacts. Indeed, those teams might even lack the resources necessary to retract any partially implemented capabilities. See “How budget depletion leads to technical debt” for a more detailed explanation of this particular technical debt formation mechanism.

Such budget control tactics as across-the-board cuts can be counter-effective unless they attend to their technical debt implications. When budget control tactics lead to technical debt formation, they can add to future expenses through the MICs on the debt they generate. Those additional expenses then create future needs for budget cuts, creating a vicious cycle. To gain control of technical debt, we must alter these budget control tactics. We need to provide teams with the resources they need for retracting partial implementations. That would ensure that budget reductions don’t lead to technical debt formation.

Investing in technical debt retirement and engineering process improvement without first addressing the nontechnical causes of technical debt is probably futile. It’s like bailing out a sinking rowboat without first plugging its leaks. The stated goal, “We’ll drive technical debt to zero in five years,” might better be replaced with, “Within two years we’ll get control of the behaviors that lead to technical debt.”

Last words

The template known as SMART goals provides one approach to setting goals with limited exposure to the risk of elegantly stated goals. See “Using SMART goals for technical debt reduction,” for details.

Achieving control of technical debt—rather than attaining any particular level of technical debt—is a useful goal. Either we will control technical debt or technical debt will control us.

References

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

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Cited in:

[Thorndike 1920] E.L. Thorndike. “A constant error in psychological ratings,” Journal of Applied Psychology, 4:1, 25-29, 1920. doi:10.1037/h0071663

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Accounting for technical debt

Last updated on September 16th, 2018 at 03:28 pm

With all the talk of technical debt these days, it’s a bit puzzling why there’s so little talk in the financial community about how to go about accounting for technical debt [Conroy 2012]. Perhaps one reason for this is the social gulf that exists between the financial community and the community most keenly aware of the effects of technical debt — the technologists. But another possibility is the variety of mechanisms compelling technologists to leave technical debt in place and move on to other tasks.

Accounting for technical debt isn’t the same as measuring it
Accounting for technical debt isn’t the same as measuring it. We usually regard our accounting system as a way of measuring and tracking the financial attributes of the enterprise. As such, we think of those financial attributes as representations of money. Technical debt is different. It isn’t real, and it isn’t a representation of money — it’s a representation of resources. Money is just one of those resources. Money is required to retire technical debt, and money is consumed when we carry technical debt, but other kinds of resources are also required. Sometimes we forget that when we account for technical debt.

Here’s an example. One common form of technical debt is the kind first described by Cunningham [Cunningham 1992]. Essentially, when we complete a project, we often find that we’ve advanced our understanding of what was actually needed to accomplish our goals. And we’ve advanced our understanding to such an extent that we recognize that we should have taken a different approach. Fowler described this kind of technical debt as, “Now we know how we should have done it.” [Fowler 2009] At this point, typically, we disband the team and move on to other things, leaving the technical debt outstanding, and often, undocumented and soon to be forgotten.

A (potentially) lower-cost approach involves immediate retirement of the debt and a re-release of the asset — an “echo release” — in which the asset no longer carries the technical debt we just incurred and immediately retired. But because echo releases usually offer no immediate, evident advantage to the people and assets that interact with the asset in question, decision-makers have difficulty allocating resources to echo releases.

This problem is actually due, in part, to the effects of a shortcoming in management accounting systems. Most enterprise management accounting systems track effectively the immediate costs associated with technical debt retirement projects. They do a much less effective job of representing the effects of failing to execute echo releases, or failing to execute debt retirement projects in general. The probable cause of this deficiency is the distributed nature of the MICs — the metaphorical interest charges associated with carrying a particular technical debt. The MICs appear in multiple forms: lower productivity, increased time-to-market, loss of market share, elevated voluntary turnover in the ranks of technologists, and more (see “MICs on technical debt can be difficult to measure”). These phenomena are poorly represented in enterprise accounting systems.

Decision-makers then adopt the same bias that afflicts the accounting system. In their deliberations regarding resource allocation, they emphasize only the cost of debt retirement, often omitting from consideration altogether any mention of the cost of not retiring the debt, which can be ongoing.

If we do make long-term or intermediate-term projections of costs related to carrying technical debt or costs related to debt retirement releases, we do so in the context of a cost/benefit computation as part of the proposal to retire the debt. Methods vary from proposal to proposal. Many organizations lack a standard method for making these projections. And because there’s no standard method for estimating costs, comparing the benefits of different debt retirement proposals is difficult. This ambiguity and variability further encourages decision-makers to base their decisions solely on current costs, omitting consideration of projected future benefits.

Dealing with accounting for technical debt

Relative to technical debt, the accounting practice perhaps most notable for its absence is accounting for outstanding technical debts as liabilities. We do recognize outstanding financial debt as such, but few balance sheets — even those for internal use only — mention outstanding technical debt. Ignorance of the liabilities imposed by outstanding technical debt can cause decision-makers to believe that the enterprise has capacity and resources that it doesn’t actually have. Many of the problems associated with high levels of technical debt would be alleviated more readily if we began to track our technical debts as liabilities — even if we did so for internal purposes only.

But other shortcomings in accounting practices can create additional problems almost as severe.

Addressing the technical-debt-related shortcomings of accounting systems requires adopting enterprise-wide patterns for proposals, which gives decision-makers meaningful comparisons between different technical debt retirement options and between technical debt retirement options and development or maintenance options. One area merits focused and immediate attention: estimating MPrin and estimating MICs.

Standards for estimating MPrin are essential for estimating the cost of retiring technical debt. Likewise, standards for estimating MICs, at least in the short term, are essential for estimating the cost of not retiring technical debt. Because both MPrin and MICs can include contributions from almost any enterprise component, merely determining where to look for contributions to MPrin or MICs can be a complex task. So developing a checklist of potential contributions can help proposal writers develop a more complete and consistent picture of the MICs or MPrin associated with a technical debt. Below are three suggestions of broad areas worthy of close examination.

Revenue stream disruption

Technical debt can disrupt revenue streams either in the course of being retired, or when defects in production systems need attention. When those systems are taken out of production for repairs or testing, revenue capture might undergo short disruptions. Burdens of technical debt can extend those disruptions, or increase their frequency.

For example, a technical debt consisting of the absence of an automated test can lengthen a disruption while the system undergoes manual tests. A technical debt consisting of a misalignment between a testing environment and the production environment can allow defects in a repair or enhancement to slip through, creating new disruptions as those new defects get attended to. Even a short disruption of a high-volume revenue stream can be expensive.

Some associations between classes of technical debt and certain revenue streams can be discovered and defined in advance of any debt retirement effort. This knowledge is helpful in estimating the contributions to MICs or MPrin from revenue stream disruption.

Extended time-to-market

Although technologists are keenly aware of productivity effects of technical debt, these effects can be small compared to the costs of extended time-to-market. In the presence of outstanding technical debt, time-to-market expands not only as a result of productivity reduction, but also from resource shortages and resource contention. Extended time-to-market can lead to delays in realizing revenue potential, and persistent and  irreparable reductions in market share. To facilitate comparisons between different technical debt retirement proposals, estimates of these effects should follow standard patterns.

Data flow disruption

All data flow disruptions are not created equal. Some data flow processes can detect their own disruptions and backfill when necessary. For these flows, the main consequence that might contribute to MICs or MPrin is delay. And the most expensive of these are delays in receipt of orders, delays in processing orders, and delays in responding to anomalous conditions. Data flows that cannot detect disruptions are usually less critical, but they nevertheless have costs too. All of these consequences can be modeled and estimated, and we can develop standard packages for doing so that we can apply repeatedly to MICs or MPrin estimates for different kinds of technical debt.

Last words

Estimates of MICs or MPrin are helpful in estimating the costs of retiring technical debt. They’re also helpful in estimating the costs of not retiring technical debt. In either case, they’re only estimates, and as such, they have error bars and confidence limits. The accounting systems we now use have no error bars. That, too, is a shortcoming that must be addressed.

References

[Conroy 2012] Patrick Conroy. “Technical Debt: Where Are the Shareholders' Interests?,” IEEE Software, 29, 2012, p. 88.

Available: here; Retrieved: August 15, 2018.

Cited in:

[Cunningham 1992] Ward Cunningham. “The WyCash Portfolio Management System.” Addendum to the Proceedings of OOPSLA 1992. ACM, 1992.

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

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

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Cited in:

[Thorndike 1920] E.L. Thorndike. “A constant error in psychological ratings,” Journal of Applied Psychology, 4:1, 25-29, 1920. doi:10.1037/h0071663

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The Principal Principle: Focus on MICs

Last updated on December 11th, 2018 at 06:56 am

When some organizations first realize that their performance is being limited by technical debt, they begin by chartering a “technical debt inventory.” Their goals are to determine just how much technical debt they’re carrying, where it is, how much retiring it all will cost, and how fast they can retire it. That’s understandable. It’s not too different from how one would approach an out-of-control financial debt situation. Understandable, but in most cases, ineffective. With technical debt we need a different approach, because technical debt is different from financial debt. With technical debt, we must be guided by what I call the Principal Principle, which is:

The Metaphorical Principal (MPrin) of a technical debt, which is the cost of retiring it, isn’t what matters most. What usually matters most is the Metaphorical Interest Charges—the MICs.

The door to a bank vault
The door to a bank vault. One way to know that technical debt differs from financial debt is that banks aren’t involved in any way. Treating technical debt as if it had anything in common with financial debt—beyond our own sense of obligation—is a shortcut to real trouble. Remember the Principal Principle.

With technical debt, MICs can vary dramatically. For assets that aren’t being maintained or enhanced, the MICs can be Zero for extended periods. For retiring assets, their technical debt can vanish when the asset is retired. For other assets, MICs can be dramatically higher—beyond the total cost of replacing the asset.

Most people regard MICs as being restricted to productivity problems among engineers. I take a different approach. I include in MICs anything that depresses net income—lost or delayed revenue, increased expenses, anything. For instance, if technical debt causes a two-month delay in reaching a market, its effect on revenues can be substantial for years to come. I regard all of that total effect as contributing to MICs.

So the Principal Principle is that a focus on Principal can be your undoing. Focus on MICs. Drive them to Zero and keep them there.

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Technical debt use disorder

The American Psychiatric Association has identified a disorder they call Substance Use Disorder (SUD), which includes alcoholism, drug addiction, and other patterns related to substance use [APA 2013]. The research they’ve done can serve well as a model for understanding organizational behavior related to technical debt. In this post I’ll show how to use that model to describe a disorder of organizations that we could call Technical Debt Use Disorder (TDUD). It’s a pattern in which the organization can’t seem to retire much of its technical debt, or can’t stop incurring increasing burdens of technical debt, even though everyone in the organization realizes—or almost everyone realizes—that technical debt is harming the organization.

A ball and chain, with shackle
A ball and chain, with shackle.  Attaching this device to the legs of prisoners or slaves limits their ability to run, just as technical debt limits the ability of organizations to exploit new opportunities, or even to maintain their current market positions.

A brief description of the American Psychiatric Association’s publication, DSM-5®, might help explain the connection between SUD and TDUD. DSM-5 is the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM). It’s used by health care professionals in the United States and much of the rest of the world as a guide to diagnosing mental disorders, and as a framework for further research. First published in 1952, the current revision, DSM-5, was released in 2013.

So what does DSM-5 have to do with technical debt?

What distinguishes responsible use of technical debt from irresponsible use is a topic that has generated many papers, conference presentations, and hallway debates over the years. Although there is consensus about the distinction in many cases, the debate continues. Sometimes, though, research in one field suggests paths forward in seemingly unrelated fields. So much thought and study has been invested in DSM-5 that it’s worth a look to see if the technical debt community can harvest something useful from the research in psychiatry.

I looked at DSM because I noticed that organizations that carry significant volumes of technical debt seem to have difficulty retiring it. In some cases, they also have difficulty halting accumulation of technical debt, or even slowing the rate of accumulation. This struck me as similar to the substance use problems some people encounter. I began to wonder whether there might be parallels between the substance use disorders that afflict people—alcoholism, drug addiction, and so on—and the technical debt problems that afflict organizations.

In the table below is one set of parallels I’ve found. The left column of the table is the list of diagnostic criteria for Substance Use Disorder provided in the DSM. The right column is my rewording of those criteria in an attempt to make them apply to how organizations deal with technical debt. I had thought initially that the rewording exercise might be difficult—that it might be a stretch. And here and there, it was a bit of a stretch. But overall, the SUD framework is a very good fit.

Diagnosing technical debt use disorder

Have a look at the table, and then check out the comments below it about how health care professions use the criteria.

DSM-5 Criteria for Substance Use Disorder (SUD)Criteria for Enterprise Technical Debt Use Disorder (TDUD)
1. Taking the substance in larger amounts or for longer than you’re meant to.
1. Incurring technical debt in larger amounts than you intended and carrying it for longer than you intended.
2. Wanting to cut down or stop using the substance but not managing to.2. Wanting to retire your technical debt or reduce the rate of incurring it but not managing to.
3. Spending a lot of time getting, using, or recovering from use of the substance.3. Spending a lot of time dealing with the consequences of the technical debt you’ve already incurred.
4. Cravings and urges to use the substance.4. Insistent demands on precious resources, causing the enterprise to incur “just a little more” technical debt.
5. Not managing to do what you should at work, home, or school because of substance use.5. Not managing to attend to the needs of existing products, services, or technological infra­structure because of the demands resulting from metaphorical interest charges on technical debt.
6. Continuing to use, even when it causes problems in relationships.6. Continuing to carry technical debt, or continuing to incur yet more technical debt, even though it causes toxic conflict among employees, and problems in customer relationships and strategic partnerships.
7. Giving up important social, occupational, or recreational activities because of substance use.7. Giving up developing important new products or services, or upgrading critical infrastructure, or pursuing new initiatives because of resource deficits traceable to technical debt service.
8. Using substances again and again, even when it puts you in danger.8. Incurring technical debt again and again, even when it puts the enterprise in fiscal danger or danger of losing market position.
9. Continuing to use, even when you know you have a physical or psychological problem that could have been caused or made worse by the substance.9. Continuing to incur technical debt, even when you know you have a fiscal or market leadership problem that could have been caused or made worse by technical debt.
10. Needing more of the substance to get the effect you want (tolerance).10. Needing to incur more technical debt to get the fiscal effect you need—a product delivered or a contract completed.
11. Development of withdrawal symptoms, which can be relieved by taking more of the substance.11. Upon attempting to retire existing technical debt, or halting incurring yet more technical debt, fiscal or market position problems develop in short order, which can be relieved only by incurring yet more debt.

In health care, two or three symptoms indicate a mild substance use disorder; four or five symptoms indicate a moderate substance use disorder, and six or more symptoms indicate a severe substance use disorder. Have a look at the right-hand column. How would you score your organization? Can we categorize the severity of an organization’s problem with technical debt using a scale similar to the one health care professionals use for SUD?

Conclusion

Technical debt isn’t inherently evil. Its existence among technological assets isn’t proof of engineering malpractice. For example, we can decide—responsibly—to deliver a system that carries technical debt, provided that we’ve carefully weighed the consequences of incurring that debt against the consequences of delayed delivery, and provided that we have a workable plan for retiring that debt, or for carrying the burden of its MICs.

But organizations can nevertheless become trapped in a cycle of technical debt, unable to make much progress in reducing it. In some cases, business as usual won’t work. Drastic action is required.

References

[APA 2013] American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association Publishing, 2013.

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Cited in:

[Conroy 2012] Patrick Conroy. “Technical Debt: Where Are the Shareholders' Interests?,” IEEE Software, 29, 2012, p. 88.

Available: here; Retrieved: August 15, 2018.

Cited in:

[Cunningham 1992] Ward Cunningham. “The WyCash Portfolio Management System.” Addendum to the Proceedings of OOPSLA 1992. ACM, 1992.

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

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

Order from Amazon

Cited in:

[Thorndike 1920] E.L. Thorndike. “A constant error in psychological ratings,” Journal of Applied Psychology, 4:1, 25-29, 1920. doi:10.1037/h0071663

Cited in:

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Using SMART goals for technical debt reduction

Last updated on May 9th, 2019 at 02:17 pm

Attempting to reduce the enterprise burden of technical debt by setting so-called “SMART goals” in the obvious way can often produce disappointing results. SMART, due to George T. Doran [Doran 1981], is a widely used approach for expressing management goals. “SMART” is an acronym for “Specific, Measurable, Attainable, Realistic, and Time-boxed,” though the last three words (the “ART”) are chosen in various alternative ways. Doran himself used “assignable, realistic, and time-related.”

Prof. George T. Doran (1939-2011), creator of the S.M.A.R.T acronym for setting management objectives
Prof. George T. Doran (1939-2011), creator of the S.M.A.R.T acronym for setting management objectives. Watch a 2010 interview of Prof. Doran at YouTube.
SMART is so embedded in management culture that many assume without investigation that expressing technical debt reduction goals directly using the SMART pattern will produce the desired results. Also embedded in management culture is the aphorism, “You get what you measure.” [Ariely 2010]  [Bouwers 2010] Combining these two ideas in a straightforward way, one might express the technical debt reduction goal as, “Reduce the burden of technical debt by 20% per year for each of the next five years.”

There is ample support for a claim that this “direct” approach to applying the SMART technique will be ineffective. The fundamental issue is that so much of employee behavior affects technical debt indirectly that it overwhelms the effects of employee behaviors that affect technical debt directly. The result is that although the direct approach does cause some employees to adopt desirable behaviors, their impact is not significant enough compared to the effects of the behaviors of employees who see little connection between their own activities and the burden of technical debt, or who are subject to competing constraints on their behaviors that then cause them to act in ways that increase technical debt.

That’s why it’s necessary for management to develop a series of SMART goals that affect behaviors that have indirect effects on technical debt. In the first part of this post, “Setting a direct SMART goal for technical debt reduction is problematic,” I explore the problems inherent in the direct approach. In the second part, “How to set SMART goals for technical debt,” I provide examples of SMART goals that touch on behaviors that have indirect effects on technical debt.

Setting a direct SMART goal for technical debt reduction is problematic

Let’s begin by exploring some of the problems with the direct approach. In this section, I assume that management has set a SMART goal for the enterprise in the form, “Reduce the burden of technical debt by 20% per year for each of the next five years.” But there’s nothing special about the numbers. My comments below apply to the form of the goal, rather than the specific numbers.

The direct approach assumes measurability

To attain a goal of a 20% reduction in technical debt in a given year, we must be able to measure the level of technical debt at the beginning of the year and the level at the end of the year, presumably with confidence in the 90% range or better. Such a measurement with the precision required might not be possible. Moreover, in most cases the probability that such a measurement is possible is low. For these reasons, setting periodic goals for total technical debt is not a useful management tool.

Consider a simple example. One form of technical debt—and it’s a common form—is missing or incompletely implemented capability. In some instances, the metaphorical principal (MPrin) of a given instance of this debt in the current year can change spontaneously to a dramatically larger value in the following year (or even the following week), due to changes in the underlying asset unrelated to the technical debt, or due to debt contagion, or due to any number of other reasons. When this happens, the technical debt retirement effort for that year can appear to have suffered a serious setback, even though the technical debt retirement teams might have been performing perfectly well.

The direct approach assumes a static principal

With most financial debts, the principal amount is specified at the time of loan origination. Moreover, we can compute the principal at any time given the mathematical formulas specified in the loan agreement.

By contrast, in many cases, the metaphorical principal amount of a technical debt might be neither fixed nor readily computable. We can estimate the MPrin of a given kind of technical debt at a given time, and we can even make forward projections of those estimates. But they are merely estimates, and their error bars can be enormous. See “Policy implications of the properties of MPrin” and “Useful projections of MPrin might not be attainable.”

The direct approach focuses on MPrin, not MICs

Objectives expressed in terms of the volume of technical debt—the total MPrin—are at risk of missing the point. Total MPrin is not what matters most. What matters is MICs—the total cost of carrying the debt. Even more important is the timing of arrival of the MICs.

And like MPrin, MICs can vary in wild and unpredictable ways. For example, the MICs for a piece of technical debt borne by an asset that isn’t undergoing maintenance or enhancement can be zero; in a later time period, when that asset is undergoing enhancement, the MICs can be very high indeed. See  “MICs on technical debt can be unpredictable” for a detailed discussion.

Priority setting for technical debt retirement is most effective when it takes into account the timing of MICs. For example, if we know that we must enhance a particular asset by FY21 Q3, and if we know that it bears technical debt that adds to the cost of the enhancement, retiring that debt in FY20 would be advisable. On the other hand, if that form of technical debt has no effect on MICs for the foreseeable future, retiring that technical debt might not be worth the effort.

The direct approach fails to distinguish legacy technical debt from incremental technical debt

Unless policies are already in place governing the formation of new technical debt—what I call incremental technical debt—technical debt retirement programs might encounter severe difficulty meeting their goals. The technical debt retirement program might simply be unable to keep up with the formation of new technical debt resulting from new development or from ongoing maintenance and enhancement of existing assets.

The direct approach fails to anticipate the formation of enterprise-exogenous technical debt

Technical debt can sometimes form as a result of innovations, changes in standards, or changes in regulations that occur entirely external to the enterprise. I call such technical debt enterprise-exogenous. When this happens, the technical debt retirement effort can appear to have suffered a serious setback, even though the technical debt retirement teams might have been performing perfectly well. Before initiating a technical debt reduction program, it’s wise to first deploy a program that’s capable of retiring technical debt at a pace that at least equals the pace of formation of enterprise-exogenous technical debt.

Incurring technical debt is sometimes the responsible thing to do

At times, incurring technical debt is prudent. In some situations, accepting the debt you’ve incurred—even for the long term—might be called for. Because strict goals about total technical debt can lead to reluctance to incur debt that has a legitimate  business purpose, whatever goals are set for total technical debt must be nuanced enough to deal with these situations. Goals for total technical debt that adhere strictly to the SMART goal pattern sometimes lack the necessary level of nuance.

How to set SMART goals for technical debt

SMART goals can work for technical debt management, but we must express them in ways that are more closely related to behavioral choices. Here are some examples of SMART goals that can be effective elements of the technical debt management program. Some of these examples are admittedly incomplete. For example,  I offer no proof of assignability, attainability, or realism, because they can vary from organization to organization, or because the goal in question must be distributed across multiple organizational elements in ways peculiar to the organization.

At least 30% of incremental technical debt will be secured technical debt at the end of Year 1; 60% by the end of Year 2

Incremental technical debt is technical debt that’s incurred in the course of work currently underway or just recently completed. Because it’s so well understood, its MPrin can be estimated with higher precision than is usually possible with legacy technical debt. That precision is needed for defining the collateral and resources used to secure the debt.

A secured technical debt, like a secured financial debt, is one for which the enterprise reserves the resources needed to retire the debt. However, unlike a financial debt, the resources required to retire a technical debt might not be purely financial. Beyond financial resources, they might include particular staff, equipment, test beds, and downtime. The commitment might extend beyond the current fiscal period. Secured technical debt is a powerful means of driving down total technical debt burden, but it might require modification of internal budget management processes and fiscal reporting. Policymakers can help in designing and deploying the necessary changes.

Within one year, at least 50% of all incremental technical debt will be retired within one year of its origination; 70% within 18 months

This goal also exploits the fact that incremental technical debt can be estimated with relatively high precision. As a goal, it builds on the goal above by requiring that the resources pledged to retire incremental debts actually be expended as intended.

Within one year, all engineers and their direct supervisors will be educated in basic technical debt concepts

The educational materials will be developed in the next five months and piloted with 10% of the technical staff within seven months. The material will include an online proficiency test that 90% of engineers will have successfully passed within a year.

Within one year, 90% of project plans will include projections of the MPrin of the incremental technical debt they expect to generate for each delivery cycle

This information is useful for making forward projections of resources needed to secure incremental technical debt. Tracking the accuracy of these projections helps project planners improve their estimates.

Within one year, initiate a practice of identifying the top five forms of legacy technical debt, ranked by the volume of the contagion

Debt contagion is the propagation of a given form of technical debt by creating new system elements or assets in forms compatible with elements already identified as technical debt. By examining the body of incremental technical debt created enterprise-wide in a given time period (say, by fiscal quarter), we can determine the portion of that incremental debt that results from contagion, for each type of contagious legacy technical debt. This data is needed to identify the most contagious forms of legacy technical debt. They are prime candidates for debt retirement.

Within one year, initiate an industrial intelligence practice that is responsible for projecting the formation of enterprise-exogenous technical debt

This group must have a sophisticated grasp of the technologies in use within the enterprise that already bear enterprise-exogenous technical debt, or which could be subject to the formation of enterprise-exogenous technical debt. Its responsibilities cover enterprise products and services, as well as enterprise infrastructure. It issues advisories as needed, and an annual forecast. The group is also responsible for recommending and monitoring participation in industrial standards organizations. The group reports to the CIO or CTO.

References

[APA 2013] American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association Publishing, 2013.

Order from Amazon

Cited in:

[Ariely 2010] Dan Ariely. “You are what you measure,” Harvard Business Review 88:6, p. 38, 2010.

Available: here; Retrieved: June 4, 2018

Cited in:

[Bouwers 2010] Eric Bouwers, Joost Visser, and Arie van Deursen. “Getting What You Measure: Four common pitfalls in using software metrics for project management,” ACM Queue 10: 50-56, 2012.

Available: here; Retrieved: June 4, 2018

Cited in:

[Conroy 2012] Patrick Conroy. “Technical Debt: Where Are the Shareholders' Interests?,” IEEE Software, 29, 2012, p. 88.

Available: here; Retrieved: August 15, 2018.

Cited in:

[Cunningham 1992] Ward Cunningham. “The WyCash Portfolio Management System.” Addendum to the Proceedings of OOPSLA 1992. ACM, 1992.

Cited in:

[Doran 1981] George T. Doran. “There’s a S.M.A.R.T. Way to Write Management’s Goals and Objectives”, Management Review, 70:11, pp. 35-36, 1981.

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

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

Order from Amazon

Cited in:

[Thorndike 1920] E.L. Thorndike. “A constant error in psychological ratings,” Journal of Applied Psychology, 4:1, 25-29, 1920. doi:10.1037/h0071663

Cited in:

Other posts in this thread

Malfeasance can be a source of technical debt

Last updated on April 29th, 2018 at 06:36 am

Although creating and deploying policies to manage technical debt is a necessary step, it isn’t sufficient for achieving control in every case. Even if training and communication programs are effective, the possibility of intentional circumvention of technical debt management policy remains. Malfeasance can lead to incurring new technical debt by circumventing any policy. And malfeasance can be an obstacle to retiring—or even identifying—existing technical debt. Moreover, indirect effects of forms of malfeasance seemingly unrelated to technical debt can nevertheless incur technical debt or extend the lifetime of existing technical debt.

Examples of malfeasance as a source of technical debt

Elizabeth Holmes Backstage at TechCrunch Disrupt San Francisco 2014
Elizabeth Holmes Backstage at TechCrunch Disrupt San Francisco 2014. She is the founder, chairman, and CEO of Theranos, a startup that grew to a total valuation of $9 billion in 2015, and has since dramatically declined in value, now on the edge of its second bankruptcy. Theranos, through Holmes, claimed to have developed a technology that enabled blood testing with small amounts of blood—0.1% to 1% of the amount of blood required by conventional blood testing technologies. These claims proved false. After a series of collisions with U.S. government agencies, the U.S. Securities and Exchange Commission sued Holmes and Theranos. In March 2018, a settlement was reached in which Holmes accepted severe financial penalties, loss of voting control of Theranos, and a ban from serving as an officer or director of any public company for ten years. Photo (cc) Max Morse for TechCrunch.

Consider an example from software engineering. To save time, an engineer might intentionally choose to use a deprecated approach. When the malfeasance is discovered, one question naturally arises: in what other places and on what other projects has this individual (or other individuals) been making such choices? In a conventional approach to controlling this form of technical debt, we might be concerned only with the engineer’s current assignment. But a more comprehensive investigation might uncover a trail of technical debt artifacts in the engineer’s previous assignments.

Allman relates a hardware-oriented example [Allman 2012]. He describes an incident involving the University of California at Berkeley’s CalMail system, which failed catastrophically in November 2011, when one disk in a RAID (Redundant Array of Inexpensive Disks) failed due to deferred maintenance. Allman regards this incident as traceable to the technical debt consisting of the deferred RAID maintenance. While this particular case isn’t an example of malfeasance, it’s reasonable to suppose that decisions to defer technical maintenance on complex systems frequently are arguably negligent.

History provides us with many clear examples of malfeasance leading to technical debt indirectly. Consider the Brooklyn Bridge. Many of the suspension cables of the bridge contain substandard steel wire, which was provided to the bridge constructors by an unscrupulous manufacturer. When the bridge engineer discovered the malfeasance, he recognized that the faulty wire that had already been installed could not be removed, or even inspected. So he compensated for the faulty wire by adding additional strands to the affected cables. For more, see “Nontechnical precursors of non-strategic technical debt.”

What kinds of malfeasance deserve special attention and why

Malfeasance that leads to incurring technical debt or which extends the life of existing technical debt has the potential to expose the enterprise to uncontrolled increases in operating expenses and unknown obstacles to revenue generation. The upward pressures on operating expenses derive from the MICs associated with technical debt. Although MICs can include obstacles to revenue generation, considering these obstacles separately helps to clarify of the effects of malfeasance.

Malfeasance deserves special attention because the financial harm to the enterprise can dramatically exceed the financial benefit the malfeasance confers on its perpetrators. This property of technical-debt-related malfeasance is what makes its correction, detection, and prevention so important.

For example, when hiring engineers, some candidates claim to have capabilities and experience that they actually don’t have. Once they’re on board, they expose the enterprise to the risk of technical debt creation through substandard work that can escape notice for indefinite periods. The malfeasance here consists of the candidate’s misrepresentation of his or her capabilities. Although the candidate, once hired, does receive some benefit arising from the malfeasance, the harm to the enterprise can exceed that benefit by orders of magnitude.

As a second example, consider the behavior of organizational psychopaths [Babiak 2007] [Morse 2004]. Organizational psychopathy can be a dominant contributing factor to technical debt formation when the primary beneficiary of a proposed strategy is the decision-maker or the advocate who takes credit for the short term effects of the decision, and when he or she intends knowingly to move on to a new position or to employment elsewhere before the true long term cost of the technical debt becomes evident. This behavior is malfeasance of the highest order. And although it’s rare, its impact can be severe. For more, see “Organizational psychopathy: career advancement by surfing the debt tsunami.”

What’s required to control malfeasance

When a particular kind of malfeasance can incur technical debt or extend the life of existing technical debt, it merits special attention. Examples like those above suggest three attributes that technical debt management programs must have if they are to deal effectively with malfeasance.

Corrective measures

Corrective measures can be undertaken in a straightforward manner when inadvertent policy violations occur. For example, unexpected difficulties in setting priorities for technical debt retirement efforts might be the result of individual performance metrics that conflict with the technical debt control program. Such conflicts can be inadvertent and can be resolved collaboratively.

But with regard to malfeasance, difficulties arise when policy violations are discovered or reported. When the violations are intentional, corrective action usually entails investigation of the means by which the infraction was achieved, and the means by which it was concealed. When these activities involve many individuals attached to multiple business units, some means of allocating the cost of corrective action might be needed. Allocating the cost of corrections can also be difficult when one party has reaped extraordinary benefits by taking steps that led to incurring significant technical debt. In some cases, corrective measures might include punitive actions directed at individuals.

Detection measures

When intentional violations are covert, or those who committed the violations claim that they’re unintentional, investigation is necessary to determine whether or not a pattern of violations exists. Technical debt forensic activities require resources, including rigorous audits and robust record-keeping regarding the decisions that led to the formation or persistence of technical debt. Automated detection techniques might be necessary to control the cost of detection efforts, and to ensure reliable detection.

Preventative measures

Successful prevention of policy violations requires education, communication, and effective enforcement. The basis of effective policy violation prevention programs includes widespread understanding of the technical debt concept and the technical debt management policies, and the certainty of discovery of intentional infractions. These factors require commitment and continuing investment.

Policy frameworks are at risk of depressed effectiveness if they pay too little attention to malfeasance and other forms of misconduct. Such misbehavior deserves special attention because it’s often accompanied both by attempts to conceal any resulting technical debt, and attempts to mislead investigators and managers about its existence. These situations do arise, though rarely, and when they do, they must be addressed in policy terms.

References

[APA 2013] American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association Publishing, 2013.

Order from Amazon

Cited in:

[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:

[Ariely 2010] Dan Ariely. “You are what you measure,” Harvard Business Review 88:6, p. 38, 2010.

Available: here; Retrieved: June 4, 2018

Cited in:

[Babiak 2007] Paul Babiak and Robert D. Hare. Snakes in Suits: When Psychopaths Go to Work. New York: HarperCollins, 2007. ISBN:978-0-06-114789-0

Order from Amazon

Cited in:

[Bouwers 2010] Eric Bouwers, Joost Visser, and Arie van Deursen. “Getting What You Measure: Four common pitfalls in using software metrics for project management,” ACM Queue 10: 50-56, 2012.

Available: here; Retrieved: June 4, 2018

Cited in:

[Conroy 2012] Patrick Conroy. “Technical Debt: Where Are the Shareholders' Interests?,” IEEE Software, 29, 2012, p. 88.

Available: here; Retrieved: August 15, 2018.

Cited in:

[Cunningham 1992] Ward Cunningham. “The WyCash Portfolio Management System.” Addendum to the Proceedings of OOPSLA 1992. ACM, 1992.

Cited in:

[Doran 1981] George T. Doran. “There’s a S.M.A.R.T. Way to Write Management’s Goals and Objectives”, Management Review, 70:11, pp. 35-36, 1981.

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

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

Order from Amazon

Cited in:

[Morse 2004] Gardiner Morse. “Executive psychopaths,” Harvard Business Review, 82:10, 20-22, 2004.

Available: here; Retrieved: April 25, 2018

Cited in:

[Thorndike 1920] E.L. Thorndike. “A constant error in psychological ratings,” Journal of Applied Psychology, 4:1, 25-29, 1920. doi:10.1037/h0071663

Cited in:

Other posts in this thread

How budget depletion leads to technical debt

Some projects undergo budget depletion exercises when their budgets are reduced, or when there’s evidence that the funds remaining will be insufficient to complete the work originally planned. Formats vary, but the typical goal of these exercises is downscoping — removing, relaxing, deferring, or suspending some requirements. Since funds are limited, downscoping is often executed in a manner that leads to technical debt.

The Old River Control Complex on the Mississippi River
The Old River Control Complex on the Mississippi River. Built and operated by the US Army Corps of Engineers (USACE) the Old River Control Complex is used for controlling the flow from the Mississippi into a distributary known as the Atchafalaya River. Were it not for this facility, the Mississippi would long ago have rerouted itself into the Atchafalaya, which has a much steeper gradient to the ocean. Since that change would have deprived New Orleans and all the industrial facilities along the lower Mississippi of access to the water and navigational channels they now enjoy, USACE maintains a complex of flow control facilities to prevent Nature taking its course, and to prevent flooding along the lower Mississippi.
The industrial facilities of the lower Mississippi constitute a technical debt, in the sense that their existence is no longer compatible with the “update” Nature is trying to deploy, in the form of rerouting the flow of water from the Mississippi to the Atchafalaya. Because our national budget doesn’t allow for repositioning the city of New Orleans and all the industrial facilities from the lower Mississippi to somewhere along the Atchafalaya, we’ve elected to redirect the flow of water from the course Nature prefers to a course more compatible with the existing industrial base. Operating and maintaining the Old River Control Complex, together with a multitude of levees, dredging projects, and gates throughout lower Louisiana, are the MICs we pay for the technical debt that is the outdated position of the city of New Orleans and its associated industrial base.
For more about Atchafalaya, see the famous New Yorker article by John McPhee [MacFee 1987]. Photo courtesy USACE
Here’s an illustrative scenario. At the time downscoping begins, the work product might contain incomplete implementations of items that are to be removed from the list of objectives. A most insidious type of debt, and most difficult to detect, consists of accommodations contained in surviving artifacts that are no longer needed because the items they were intended to support have been cancelled. This class of technical debt is difficult to detect because the affected system components appear to be merely overly complicated. Recognizing it as a residual of a cancelled capability requires knowledge of its history. Unless these artifacts are documented at the time of the downscoping, that knowledge may be lost.

Other items of technical debt that arise from budget depletion include tests that no longer need to be executed, or documentation that’s no longer consistent with the rest of the work product, or user interface artifacts no longer needed. When budgets become sufficiently tight, funds aren’t available for documenting these items of technical debt as debt, and the enterprise can lose track of them when team members move on or are reassigned.

In some instances, budget depletion takes effect even before the work begins. This happens, for example, when project champions unwittingly underestimate costs in order to obtain approval for the work they have in mind. The unreasonableness of the budget becomes clear soon after the budget is approved, and the effects described above take hold soon thereafter.

Budget depletion can also have some of the same effects as schedule pressure. When the team devises the downscoping plan, it must make choices about what to include in the revised project objectives. In some cases, the desire to include some work can bias estimates of the effort required to execute it. If the team underestimates the work involved, the result is increased pressure to perform that work. With increased pressure comes technical debt. See “With all deliberate urgency” for more.

A policy that could limit technical debt formation in response to budget depletion would require identifying the technical debt such action creates, and later retiring that debt. Because these actions do require resources, they consume some of the savings that were supposed to accrue from downscoping. In some cases, they could consume that amount in its entirety, or more. Most decision-makers probably over-estimate the effectiveness of the downscoping strategy. Often, it simply reduces current expenses by trading them for increased technical debt, which raises future expenses and decreases opportunities in future periods.

References

[APA 2013] American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association Publishing, 2013.

Order from Amazon

Cited in:

[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:

[Ariely 2010] Dan Ariely. “You are what you measure,” Harvard Business Review 88:6, p. 38, 2010.

Available: here; Retrieved: June 4, 2018

Cited in:

[Babiak 2007] Paul Babiak and Robert D. Hare. Snakes in Suits: When Psychopaths Go to Work. New York: HarperCollins, 2007. ISBN:978-0-06-114789-0

Order from Amazon

Cited in:

[Bouwers 2010] Eric Bouwers, Joost Visser, and Arie van Deursen. “Getting What You Measure: Four common pitfalls in using software metrics for project management,” ACM Queue 10: 50-56, 2012.

Available: here; Retrieved: June 4, 2018

Cited in:

[Conroy 2012] Patrick Conroy. “Technical Debt: Where Are the Shareholders' Interests?,” IEEE Software, 29, 2012, p. 88.

Available: here; Retrieved: August 15, 2018.

Cited in:

[Cunningham 1992] Ward Cunningham. “The WyCash Portfolio Management System.” Addendum to the Proceedings of OOPSLA 1992. ACM, 1992.

Cited in:

[Doran 1981] George T. Doran. “There’s a S.M.A.R.T. Way to Write Management’s Goals and Objectives”, Management Review, 70:11, pp. 35-36, 1981.

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

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

Order from Amazon

Cited in:

[MacFee 1987] John MacFee. “Atchafalaya,” The New Yorker, February 23, 1987.

Available: here; Retrieved: February 5, 2018.

Cited in:

[Morse 2004] Gardiner Morse. “Executive psychopaths,” Harvard Business Review, 82:10, 20-22, 2004.

Available: here; Retrieved: April 25, 2018

Cited in:

[Thorndike 1920] E.L. Thorndike. “A constant error in psychological ratings,” Journal of Applied Psychology, 4:1, 25-29, 1920. doi:10.1037/h0071663

Cited in:

Other posts in this thread

Separating responsibility for maintenance and acquisition

Last updated on July 24th, 2018 at 08:49 pm

Separating responsibility for maintenance and acquisition of technical assets can lead to uncontrolled growth of technical debt. When the performance of the business acquisition function or the performance of the development organization is measured without regard for the technical debt that arises as a consequence of their actions, technical debt is likely to expand unchecked. To limit such expansion, policymakers must devise performance measures that hold these organizations accountable for the technical debt arising from their actions.

Road damage in Warwick, Rhode Island, resulting from historic storms in March 2010
Road damage in Warwick, Rhode Island, resulting from historic storms in March 2010 [NOAA 2013]. The storms were so severe that at least one river flood gauge “flat-lined” — the floodwaters overtopped the gauge’s measurable range. Moreover, the National Weather Service (NWS) lacked a database of measurable ranges for flood gauges. Quoting the NWS report: “A lesson learned here was that maximum recordable river levels should be known by NWS staff, not only so staff aren’t surprised when this type of issue arises, but also to notify USGS personnel so that they can install a temporary gage and remove or elevate threatened equipment.” Technical debt, if ever I’ve seen it.
For systems consisting solely of software, separation of responsibility for system maintenance and system development or acquisition enables the acquiring organization to act with little regard for the consequences of its decisions vis-à-vis maintenance matters [Boehm 2016]. This is an unfortunate state of affairs that increases the rate of accumulation of new technical debt, and increases the lifetime of legacy technical debt, because the MICs associated with the technical debt aren’t borne by the acquiring organization.

For example, a focus on performance of the organization that’s responsible for acquisition biases them in favor of attending to the direct and immediate costs of the acquisition, with little or no regard for ongoing maintenance issues. The maintenance organization is then left to deal with whatever the acquired system contains (or lacks).

An analogous mechanism operates for organizations that develop, market, and maintain products or services with software elements in their respective infrastructures. In that case, separation of the development function from the maintenance function enables the development function to act independently of the consequences of its decisions for maintenance matters.

But the separation-of-responsibilities mechanism that leads to uncontrolled technical debt isn’t restricted to software. Any technological asset that has ongoing maintenance needs (and most of them do) can potentially present this problem.

For example, in the United States, and many other countries, two streams of resources support publicly-owned infrastructure [Blair 2017]. The funding stream covers construction, operations and maintenance, and repairs. Its usual sources are taxes, tolls, licenses, other user fees, sale of ad space, and so on. The financing stream covers up-front construction costs, to bridge the period from conception through construction, until the funding stream begins delivering resources. The financing stream usually comes from bond sales.

Although both streams are controlled by legislatures, or by agencies they establish, the effects of the two streams differ fundamentally. The financing stream is dominant in the early stages of the asset’s lifecycle — during construction. The funding stream is dominant after that — when maintenance and operations are most important. Legislators and agencies are generally reluctant to supply funding because of the impact on taxpayers and users. Legislators and agencies find financing much more palatable. For this reason, among others, U.S. infrastructure maintenance is generally under-resourced, and technical debt gradually accumulates.

So it is with technological assets in organizations. For accounting purposes, capital expenses are treated differently from operational expenses, and the result is that operational expenses can have a more significant impact on current financial results than capital expenses do. This leads organizations to underfund operations and maintenance, which contributes to the accumulation of technical debt.

Control of new technical debt accumulation and enhancement of technical debt retirement rates is possible only if the acquisition or development organizations can somehow be held accountable for the MICs that result from their actions. Securitization of the debt incurred, as I’ll address in a forthcoming post, is one possible means of imposing this accountability. But reserves are also required, because some of the debt incurred might not be known at the time the asset is acquired or created.

Separation of responsibility for system maintenance and system acquisition or system development is actually a form of stovepiping. See “Stovepiping can lead to technical debt” for more on stovepiping.

References

[APA 2013] American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association Publishing, 2013.

Order from Amazon

Cited in:

[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:

[Ariely 2010] Dan Ariely. “You are what you measure,” Harvard Business Review 88:6, p. 38, 2010.

Available: here; Retrieved: June 4, 2018

Cited in:

[Babiak 2007] Paul Babiak and Robert D. Hare. Snakes in Suits: When Psychopaths Go to Work. New York: HarperCollins, 2007. ISBN:978-0-06-114789-0

Order from Amazon

Cited in:

[Blair 2017] Hunter Blair. “No free bridge: Why public–private partnerships or other ‘innovative’ financing of infrastructure will not save taxpayers money,” Economic Policy Institute blog, March 21, 2017.

Available: here; Retrieved: January 29, 2018

Cited in:

[Boehm 2016] Barry Boehm, Celia Chen, Kamonphop Srisopha, Reem Alfayez, and Lin Shiy. “Avoiding Non-Technical Sources of Software Maintenance Technical Debt,” USC Course notes, Fall 2016.

Available: here; Retrieved: July 25, 2017

Cited in:

[Bouwers 2010] Eric Bouwers, Joost Visser, and Arie van Deursen. “Getting What You Measure: Four common pitfalls in using software metrics for project management,” ACM Queue 10: 50-56, 2012.

Available: here; Retrieved: June 4, 2018

Cited in:

[Conroy 2012] Patrick Conroy. “Technical Debt: Where Are the Shareholders' Interests?,” IEEE Software, 29, 2012, p. 88.

Available: here; Retrieved: August 15, 2018.

Cited in:

[Cunningham 1992] Ward Cunningham. “The WyCash Portfolio Management System.” Addendum to the Proceedings of OOPSLA 1992. ACM, 1992.

Cited in:

[Doran 1981] George T. Doran. “There’s a S.M.A.R.T. Way to Write Management’s Goals and Objectives”, Management Review, 70:11, pp. 35-36, 1981.

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

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

Order from Amazon

Cited in:

[MacFee 1987] John MacFee. “Atchafalaya,” The New Yorker, February 23, 1987.

Available: here; Retrieved: February 5, 2018.

Cited in:

[Morse 2004] Gardiner Morse. “Executive psychopaths,” Harvard Business Review, 82:10, 20-22, 2004.

Available: here; Retrieved: April 25, 2018

Cited in:

[NOAA 2013] NOAA/National Weather Service. “The March, 2010 Floods in Southern New England,” WFO Taunton Storm Series Report #2013-01, January 2013.

Available: here; Retrieved: January 30, 2018

Cited in:

[Thorndike 1920] E.L. Thorndike. “A constant error in psychological ratings,” Journal of Applied Psychology, 4:1, 25-29, 1920. doi:10.1037/h0071663

Cited in:

Other posts in this thread

Zero tolerance and work-to-rule deliveries create an adversarial culture

Last updated on February 1st, 2018 at 07:29 am

Defining technical debt at the level of specificity needed for project objectives is difficult. Confronted with this difficulty, some internal customers of technologists adopt a zero-tolerance approach to technical debt, without specifically defining technical debt. Post-delivery — sometimes much, much, post — when technical debt is discovered or recognized, technologists are held responsible, even in cases when no one could have predicted that a specific artifact would eventually come to be regarded as technical debt. This sets up an adversarial dynamic between technologists and their internal customers.

Delayed or cancelled flights
Trouble at the airport. When airline pilots engage in work-to-rule actions, the immediate result can be large numbers of delayed or cancelled flights. The longer-term result might be beneficial to pilots, the airline, and the public, but only if labor peace can be restored, and the damage to the flying public can be overcome. So it is with work-to-rule deliveries as a way of dealing with zero-tolerance technical debt policies. The organization must overcome the adversarial culture that results from indiscriminate attempts to control technical debt. Technologists do gain some measure of protection by working to rule, but the longer-term benefit of the organization’s learning to manage technical debt arrives only if the adversarial culture can be overcome. Image (cc) Hotelstvedi courtesy Wikimedia.

And that’s when the trouble begins.

Within this adversarial dynamic, technologists try to protect themselves against future recriminations by “working to rule.” They perform only work that is specified by the internal customer. If they find something additional that must be done, they perform that work only if they successfully obtain the customer’s approval. Some customers continue to adhere to a zero-tolerance policy with respect to technical debt, but such a non-specific requirement cannot be met. Because technologists are “working to rule,” they use the ambiguity of the zero-tolerance requirement to assert that they performed all work that was sufficiently specified. This level of performance is analogous to the work-to-rule actions of some employees involved in labor disputes with their employers, and who are literally in compliance with the requirements of the employer, but only literally [LIBCom 2006].

Requiring deliverables to be totally free of technical debt contributes to formation of an adversarial culture, wherein the adversaries are the technologists and their internal customers. Shedding that adversarial culture, once it sets in, can be difficult. Compelling employees, vendors, or contractors to deliver work that’s free of all technical debt is therefore unlikely to succeed. Whether work is performed in-house by employees, or is outsourced, or is performed in-house by contractors, deliverables that meet the minimum possible interpretation of the objectives of the effort are almost certainly burdened with unacceptable levels of technical debt. What can we do to prevent this?

To avoid creating an adversarial culture, we can specify in project objectives some kinds of technical debt that must be removed in toto. To ensure steady progress in technical debt retirement, develop a statement of objectives that includes complete retirement of at least one well-defined class of technical debt, emphasizing debt classes that have the highest anticipated MICs in the near term. Other well-defined classes of technical debt can be addressed on a best-effort basis.

We must accept that any other forms of technical debt that remain at the end of a given project, or any constructions that later come to be recognized as technical debt, are just the “cost of doing business.” We’ll get to them, but unfortunately, not this time.

References

[APA 2013] American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association Publishing, 2013.

Order from Amazon

Cited in:

[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:

[Ariely 2010] Dan Ariely. “You are what you measure,” Harvard Business Review 88:6, p. 38, 2010.

Available: here; Retrieved: June 4, 2018

Cited in:

[Babiak 2007] Paul Babiak and Robert D. Hare. Snakes in Suits: When Psychopaths Go to Work. New York: HarperCollins, 2007. ISBN:978-0-06-114789-0

Order from Amazon

Cited in:

[Blair 2017] Hunter Blair. “No free bridge: Why public–private partnerships or other ‘innovative’ financing of infrastructure will not save taxpayers money,” Economic Policy Institute blog, March 21, 2017.

Available: here; Retrieved: January 29, 2018

Cited in:

[Boehm 2016] Barry Boehm, Celia Chen, Kamonphop Srisopha, Reem Alfayez, and Lin Shiy. “Avoiding Non-Technical Sources of Software Maintenance Technical Debt,” USC Course notes, Fall 2016.

Available: here; Retrieved: July 25, 2017

Cited in:

[Bouwers 2010] Eric Bouwers, Joost Visser, and Arie van Deursen. “Getting What You Measure: Four common pitfalls in using software metrics for project management,” ACM Queue 10: 50-56, 2012.

Available: here; Retrieved: June 4, 2018

Cited in:

[Conroy 2012] Patrick Conroy. “Technical Debt: Where Are the Shareholders' Interests?,” IEEE Software, 29, 2012, p. 88.

Available: here; Retrieved: August 15, 2018.

Cited in:

[Cunningham 1992] Ward Cunningham. “The WyCash Portfolio Management System.” Addendum to the Proceedings of OOPSLA 1992. ACM, 1992.

Cited in:

[Doran 1981] George T. Doran. “There’s a S.M.A.R.T. Way to Write Management’s Goals and Objectives”, Management Review, 70:11, pp. 35-36, 1981.

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

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

Order from Amazon

Cited in:

[LIBCom 2006] “Work-to-rule: a guide.” libcom.org.

Available: here; Retrieved: May 9, 2017.

Cited in:

[MacFee 1987] John MacFee. “Atchafalaya,” The New Yorker, February 23, 1987.

Available: here; Retrieved: February 5, 2018.

Cited in:

[Morse 2004] Gardiner Morse. “Executive psychopaths,” Harvard Business Review, 82:10, 20-22, 2004.

Available: here; Retrieved: April 25, 2018

Cited in:

[NOAA 2013] NOAA/National Weather Service. “The March, 2010 Floods in Southern New England,” WFO Taunton Storm Series Report #2013-01, January 2013.

Available: here; Retrieved: January 30, 2018

Cited in:

[Thorndike 1920] E.L. Thorndike. “A constant error in psychological ratings,” Journal of Applied Psychology, 4:1, 25-29, 1920. doi:10.1037/h0071663

Cited in:

Other posts in this thread

Self-sustaining technical knowledge deficits during contract negotiations

Last updated on February 1st, 2018 at 07:30 am

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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