Tag: non-strategic

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Feature bias: unbalanced concern for capability vs. sustainability

Enterprise decision-makers affected by feature bias tend to harbor distorted views of the importance of new capability development compared to technical debt management. This tendency is likely due to the customer’s relative sensitivity to features, and relative lack of awareness of sustainability. Whatever the cause, customers tend to be more attracted to features than they are to indicators of sound technical debt management and other product sustainability practices. This tendency puts decision-makers at risk of feature bias: unbalanced concern for capability vs. sustainability.

Alaska crude oil production 1990-2015
Alaska crude oil production 1990-2015. This chart [Yen 2015] displays Alaska crude oil produced and shipped through the Trans Alaska Pipeline System (TAPS) from 1990 to 2015. Production had dropped by 75% in that period, and the decline is projected to continue. In January 2018, in response to pressure from Alaskan government officials and the energy industry, the U.S. Congress passed legislation that opened the Arctic National Wildlife Refuge to oil exploration, despite the threat to ecological sustainability that exploration poses. If we regard TAPS as a feature of the U.S. energy production system, we can view its excess capacity as a source of feature bias bias, creating pressure on decision-makers to add features to the U.S. energy system instead of acting to enhance the sustainability of Alaskan and global environmental systems [Wight 2017].
Changes in cost accounting could mitigate some of this feature bias by projecting more accurately total MICs based on historical data and sound estimation. I’ll explore possible accounting changes later in this post, and in future posts; meanwhile, let’s explore the causes and consequences of the distorted perspective I call feature bias.

For products or services offered for sale outside the enterprise, the sales and marketing functions of the enterprise represent the voice of the customer [Gaskin 1991]. But customers are generally unaware of product or service attributes that determine maintainability, extensibility, or cybersecurity — all factors that affect the MICs for technical debt. On the other hand, customers are acutely aware of capabilities — or missing or defective capabilities — in products or services. Customer comments and requests, therefore, are unbalanced in favor of capabilities as compared to maintainability, extensibility, cybersecurity, and other attributes related to sustainability. The sales and marketing functions tend to accurately transmit this unbalanced perspective to decision-makers and technologists.

An analogous mechanism prevails with respect to infrastructure and the internal customers of that infrastructure. Internal customers tend to be more concerned with capabilities — and missing capabilities — than they are with sustainability of the processes and systems that deliver those capabilities. Thus, pressure from internal customers on the developers and maintainers of infrastructure elements tends to emphasize capability at the expense of sustainability. The result of this imbalance is pressure to allocate excessive resources to capability enhancement, compared to activities that improve maintainability, extensibility, or cybersecurity, and which therefore would aid in controlling or reducing technical debt and its MICs.

Nor is this the only consequence of feature bias. It provides unrelenting pressure for increasing numbers of features, despite the threats to architectural coherence and overall usability that such “featuritis” or “featurism” present. Featurism leads, ultimately, to feature bloat, and to difficulties for users, who can’t find what they need among the clutter of features that are often too numerous to document. For example, in Microsoft Word, many users are unaware that Shift+F5 moves the insertion point and cursor to the point in the active document that was last edited, even if the document has just been freshly loaded into Word. Useful, but obscure.

Feature bias, it must be noted, is subject to biases itself. The existing array of features appeals to a certain subset of all potential customers. Because it is that subset that’s most likely to request repair of existing features, or to suggest additional features, the pressure for features tends to be biased in favor of the needs of the most vociferous segments of the existing user base. That is, systems experience pressure to evolve to better meet the needs of existing users, in preference to meeting the needs of other stakeholders or potential stakeholders who might be even more important to the enterprise than are the existing users. This bias in feature bias presents another risk that can affect decision-makers.

Organizations can take steps to mitigate the risk of feature bias. An example of such a measure might be the use of focus groups to study how education in sustainability issues affects customers’ perspectives relative to feature bias. Educating decision makers about feature bias can also reduce this risk.

At the enterprise scale, awareness of feature bias would be helpful, but awareness alone is unlikely to counter its detrimental effects, which include underfunding of technical debt management efforts. Eliminating the source of feature bias is extraordinarily difficult, because customers and potential customers aren’t subject to enterprise policy. Feature bias and feature bias bias are therefore givens. To mitigate the effects of feature bias, we must adopt policies that compel decision-makers to consider the need to deal with technical debt. One possible corrective action might be improvement of accounting practices for MICs, based, in part, on historical data. For example, since there’s a high probability that any project might produce new technical debt, it might be prudent to fund the retirement of that debt, in the form of reserves, when we fund the project. And if we know that a project has encountered some newly recognized form of technical debt, it might be prudent to reserve resources to retire that debt as soon as possible. Ideas such as these can rationalize resource allocations with respect to technical debt.

These two examples illustrate what’s necessary if we want to mitigate the effects of feature bias. They also illustrate just how difficult such a task will be.

References

[Gaskin 1991] Steven P. Gaskin, Abbie Griffin, John R. Hauser, Gerald M. Katz, and Robert L. Klein. “Voice of the Customer,” Marketing Science 12:1, 1-27, 1991.

Cited in:

[Wight 2017] Philip Wight. “How the Alaska Pipeline Is Fueling the Push to Drill in the Arctic Refuge,” YaleE360, Yale School of Forestry & Environmental Studies, November 16, 2017.

Available: here; Retrieved: February 8, 2018

Cited in:

[Yen 2015] Terry Yen, Laura Singer. “Oil exploration in the U.S. Arctic continues despite current price environment,” Today in Energy blog, U.S. Energy Information Administration, June 12, 2015.

Available: here; Retrieved: February 8, 2018.

Cited in:

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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

[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:

[Gaskin 1991] Steven P. Gaskin, Abbie Griffin, John R. Hauser, Gerald M. Katz, and Robert L. Klein. “Voice of the Customer,” Marketing Science 12:1, 1-27, 1991.

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:

[Wight 2017] Philip Wight. “How the Alaska Pipeline Is Fueling the Push to Drill in the Arctic Refuge,” YaleE360, Yale School of Forestry & Environmental Studies, November 16, 2017.

Available: here; Retrieved: February 8, 2018

Cited in:

[Yen 2015] Terry Yen, Laura Singer. “Oil exploration in the U.S. Arctic continues despite current price environment,” Today in Energy blog, U.S. Energy Information Administration, June 12, 2015.

Available: here; Retrieved: February 8, 2018.

Cited in:

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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

[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:

[Gaskin 1991] Steven P. Gaskin, Abbie Griffin, John R. Hauser, Gerald M. Katz, and Robert L. Klein. “Voice of the Customer,” Marketing Science 12:1, 1-27, 1991.

Cited in:

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

Available: here; Retrieved: May 9, 2017.

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:

[Wight 2017] Philip Wight. “How the Alaska Pipeline Is Fueling the Push to Drill in the Arctic Refuge,” YaleE360, Yale School of Forestry & Environmental Studies, November 16, 2017.

Available: here; Retrieved: February 8, 2018

Cited in:

[Yen 2015] Terry Yen, Laura Singer. “Oil exploration in the U.S. Arctic continues despite current price environment,” Today in Energy blog, U.S. Energy Information Administration, June 12, 2015.

Available: here; Retrieved: February 8, 2018.

Cited in:

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How performance management systems can contribute to technical debt

Last updated on August 24th, 2018 at 02:17 pm

Few performance management systems provide guidance with respect to behaviors relating to technical debt, perhaps because technical debt is not widely understood, or perhaps because technical debt isn’t seen as a concern for the performance of anyone but engineers and their managers. Still, organizations that expect to gain control of technical debt must ensure that performance standards are clear about expectations with respect to behaviors that could affect technical debt. In organizations in which technical debt currently plays a minor role, if any, in the performance management system, policymakers can advocate for effective changes, if they understand what the appropriate role for performance management is in controlling technical debt. This post should be helpful.

A dog receiving a reward
A dog receiving a reward. Many performance management systems implement a model that assumes that the correct configuration of incentives and disincentives will produce the desired levels of performance. This theory is questionable.

A fundamental premise of many performance management systems is that incentives can encourage desirable behavior and disincentives can discourage undesirable behavior. Unfortunately, serious questions have arisen about the effectiveness of these behavioral control mechanisms in general [Kohn 1999]. The problem is that employees find ways to harvest incentives without exhibiting the desired behavior. Likewise, they find ways to circumvent disincentives while continuing to exhibit undesired behavior.

Moreover, specifically for technical debt management, behavioral control is especially problematic, because some of the behaviors that must be controlled are inherently immeasurable. For example, the design of an incentive structure to encourage legacy technical debt retirement is debatable, given the technical difficulties involved in even defining legacy technical debt, let alone measuring its size.

Managing performance vis-à-vis technical debt, therefore, presents a problem of the kind Austin calls partially supervised [Austin 1996]. Supervising engineers whose work touches on assets that bear technical debt can only be partial, because measuring technical debt is only partially practical given the state of the art. Austin shows how partial supervision frequently leads to dysfunctional performance management, but the problem is especially vexing for managing technical debt. For example, in some cases, engineers’ work can incur new technical debt that remains unrecognized for months or years after the work is completed. To fully supervise such work would require inventing retroactive incentives and disincentives, which not only do not exist, but which are of questionable legality in most jurisdictions.

Although incentives and disincentives cannot serve to manage performance relative to technical debt, a very effective model is available. Enterprise leaders could communicate their intentions relative to technical debt, and empower the people of the organization to take steps to reduce debt. In the United States military, and others as well, a doctrine that implements this approach is called commander’s intent [Mattis 2008].

Gen. Mattis offers five principles that guide what the military calls “effect-based operations.” For technical debt management, the effect we seek is rational control of the technical debt portfolio. Here are his five principles, transformed to the field of technical debt.

  1. Technology development, maintenance, and cyberdefense in the future will require a balance of conventional and unconventional approaches.
  2. Technology evolves rapidly, and we must be willing to adapt our methods.
  3. Technologies are dynamic with an infinite number of variables; therefore, it is not scientifically possible to accurately predict the level of technical debt that will result from any given effort. To suggest otherwise runs contrary to historical experience and the nature of modern technological assets.
  4. We are in error when we think that what works (or does not work) in efforts involving one technology in one enterprise will be universally applicable to all technologies in all enterprises.
  5. Finally, to paraphrase General Sherman, “Every attempt to make technical debt management easy and safe will result in humiliation and disaster.”

Most organizations rely on supervisors to communicate the analog of commander’s intent to their subordinates. Currently, it’s fair to say that few supervisors outside the technology-oriented elements of the enterprise communicate much about technical debt to their subordinates.

That situation might explain why most performance management systems encourage behaviors that unwittingly expand the body of technical debt, especially for non-technologist performers. There are situations in which the widely applauded actions of the outstanding performer are such as to incur technical debt strategically and responsibly. Technical debt so incurred is what McConnell calls Type II [McConnell 2008] and what Fowler calls Deliberate and Prudent [Fowler 2009]. But most performance management systems, especially for non-technologists, say nothing about technical debt, and thus risk encouraging behaviors that indirectly exacerbate the problems associated with technical debt.

Distinguishing responsible and irresponsible behaviors is possible only if understanding of the nature of technical debt is widespread in the organization, even beyond the technologists. Here’s an example:

It was ambitious, what advocates called a “stretch goal,” but the VP of Marketing approved the plan to get the new app released by the end of the next fiscal quarter. After a month of meetings, and much jawboning, the CTO agreed to find a way to make it happen, despite serious objections from the VP of New Product Development. Engineers and testers were able to meet the date, but they had to incur significant technical debt, and when they asked for resources to retire that debt after the release, the VP of Marketing opposed the request, because she needed additional resources for the promotional campaign due to our late entry into the market.

Stories like this illustrate scenarios in which technical debt considerations are consistently assigned a lower priority than goals related to market timing, market development, and revenue generation. Standards for setting priorities closely parallel the standards defined in the performance management system. Indeed, the goal of performance management should be to support enterprise goals. In the scenario above, the organization might meet the immediate goal of a successful release, but it does so by incurring technical debt, thereby imperiling the next release. In this scenario, it’s evidently necessary to change the performance management system to achieve a better balance between immediate goals and the near-term future goals.

Since anyone in the enterprise can take actions or make decisions that lead to incurring new technical debt, or cause existing technical debt to remain in place, organizations need performance standards that guide employees with respect to technical debt. To provide guidance for distinguishing responsible behavior from irresponsible behavior, performance management systems must acknowledge the potential of any employee to affect technical debt, constructively or otherwise. Performance management systems must be reviewed with respect to alignment with technical debt policy, and adjusted to encompass a mechanism analogous to Mattis’s vision of commander’s intent.

References

[Austin 1996] Robert D. Austin. Measuring and Managing Performance in Organizations. New York: Dorset House, 1996. ISBN:0-932633-36-6

Contains an extensive discussion of the consequences of partial supervision of performance. Since technical debt can only be partially supervised, the concept is relevant to understanding the effects of performance management systems on technical debt. 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:

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

Available here; Retrieved January 10, 2016.

Cited in:

[Gaskin 1991] Steven P. Gaskin, Abbie Griffin, John R. Hauser, Gerald M. Katz, and Robert L. Klein. “Voice of the Customer,” Marketing Science 12:1, 1-27, 1991.

Cited in:

[Kohn 1999] Alfie Kohn. Punished by rewards: The trouble with gold stars, incentive plans, A's, praise, and other bribes. Boston: Houghton Mifflin Harcourt, 1999. ISBN:0-395-71090-1

Order from Amazon

Cited in:

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

Available: here; Retrieved: May 9, 2017.

Cited in:

[Mattis 2008] James N. Mattis. “USJFCOM Commander’s Guidance for Effects-based Operations,” Joint Force Quarterly 51, Autumn 2008 105-108.

Available: here; Retrieved November 9, 2017.

Cited in:

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

Available: here; Retrieved November 10, 2017.

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:

[Wight 2017] Philip Wight. “How the Alaska Pipeline Is Fueling the Push to Drill in the Arctic Refuge,” YaleE360, Yale School of Forestry & Environmental Studies, November 16, 2017.

Available: here; Retrieved: February 8, 2018

Cited in:

[Yen 2015] Terry Yen, Laura Singer. “Oil exploration in the U.S. Arctic continues despite current price environment,” Today in Energy blog, U.S. Energy Information Administration, June 12, 2015.

Available: here; Retrieved: February 8, 2018.

Cited in:

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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.

References

[Austin 1996] Robert D. Austin. Measuring and Managing Performance in Organizations. New York: Dorset House, 1996. ISBN:0-932633-36-6

Contains an extensive discussion of the consequences of partial supervision of performance. Since technical debt can only be partially supervised, the concept is relevant to understanding the effects of performance management systems on technical debt. 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:

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

Available here; Retrieved January 10, 2016.

Cited in:

[Gaskin 1991] Steven P. Gaskin, Abbie Griffin, John R. Hauser, Gerald M. Katz, and Robert L. Klein. “Voice of the Customer,” Marketing Science 12:1, 1-27, 1991.

Cited in:

[Kohn 1999] Alfie Kohn. Punished by rewards: The trouble with gold stars, incentive plans, A's, praise, and other bribes. Boston: Houghton Mifflin Harcourt, 1999. ISBN:0-395-71090-1

Order from Amazon

Cited in:

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

Available: here; Retrieved: May 9, 2017.

Cited in:

[Mattis 2008] James N. Mattis. “USJFCOM Commander’s Guidance for Effects-based Operations,” Joint Force Quarterly 51, Autumn 2008 105-108.

Available: here; Retrieved November 9, 2017.

Cited in:

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

Available: here; Retrieved November 10, 2017.

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:

[Wight 2017] Philip Wight. “How the Alaska Pipeline Is Fueling the Push to Drill in the Arctic Refuge,” YaleE360, Yale School of Forestry & Environmental Studies, November 16, 2017.

Available: here; Retrieved: February 8, 2018

Cited in:

[Yen 2015] Terry Yen, Laura Singer. “Oil exploration in the U.S. Arctic continues despite current price environment,” Today in Energy blog, U.S. Energy Information Administration, June 12, 2015.

Available: here; Retrieved: February 8, 2018.

Cited in:

Other posts in this thread

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The Dunning-Kruger effect can lead to technical debt

Last updated on May 31st, 2018 at 07:43 am

The Dunning-Kruger effect [Kruger 1999] can lead to formation or persistence of technical debt in two ways. First, it can cause technologists or their managers to overestimate their ability to maintain the resource focus needed for retiring technical debt in a timely fashion. Second, it can cause senior managers to be reluctant to accede to resource requests of technologists and their managers in support of technical debt management programs.

Cropped detail from Charles Robert Darwin, a painting by John Collier
Cropped detail from Charles Robert Darwin, a painting by John Collier (1850-1934), given to the National Portrait Gallery, London, in 1896. Darwin writes, in The Descent of Man (1871): “… ignorance more frequently begets confidence than does knowledge …” which is the essence of the Dunning-Kruger effect. Image courtesy WikiQuote.

Kruger and Dunning conducted experiments that yielded results consistent with the following four principles (paraphrasing):

  1. Incompetent individuals, compared to their more competent peers, tend to dramatically overestimate their own ability and performance
  2. Incompetent individuals, compared to their more competent peers, tend to be less able to gain insight into their own true levels of performance
  3. Incompetent individuals can gain insight about their shortcomings, but, paradoxically, this comes about by gaining competence
  4. Incompetent individuals, compared to their more competent peers, are less able to recognize competence when they see it

The first three principles lead to distorted assessments of one’s own capabilities. The fourth principle leads to distorted assessments of the capabilities of others.

As an example of distorted self-assessment, consider a team or its managers who must undertake retirement of some types of technical debt in the course of enhancing or repairing an asset. Such a task plan seems at first to offer efficiencies, because the engineers can readily make both kinds of changes at one go. Metaphorically, if we must go to the store for milk, we can also pick up bread while we are there, rather than making two trips.

However, modifying an existing complex technological asset is unlike shopping for bread and milk. The two kinds of modifications — debt retirement and asset enhancement or repair — might seem at first to be separable, and often they are. But if they are not separable, and the two tasks are undertaken together, testing and debugging can become extremely complicated, because of interactions between defects in the two kinds of modifications. Under some circumstances, an experienced team and its managers might be more likely to anticipate these difficulties. An inexperienced team and its managers might be more likely to underestimate the difficulties, as a consequence of the Dunning-Kruger effect. Budget and schedule overruns are possible consequences of underestimating the complexity of the problem.

As an example of the fourth principle above, the Dunning-Kruger effect can cause some decision-makers to discount the warnings and resource requests of engineers and their managers. Decision-makers who are unsophisticated in matters related to technical debt must nevertheless assess the validity of the requests for resources. In making these assessments, these decision-makers may be disadvantaged for a number of reasons, including the following:

  • Decision-makers might hold any of a number of mistaken beliefs about technical debt. For example, many believe that the main causes of technical debt are poor decisions by engineering managers. And others believe that technical debt is the result of slovenly work habits of engineers. Those who hold such beliefs might be reluctant to allocate yet more resources to engineers to address the problem of technical debt.
  • If the advocates of resources for technical debt management are not fully informed about the strategic direction of the enterprise, their requests might be inconsistent with enterprise strategy. As a result of a cognitive bias [Kahneman 2011] known as the halo effect [Thorndike 1920], decision-makers might tend to discount valid portions of the technologists’ proposals, because some portions of those proposals don’t take enterprise strategy into account properly.
  • Decision-makers might be affected by unrealistic optimism [Weinstein 1996], also known as optimism bias. It’s a cognitive bias that can cause them to discount the sometimes-vivid warnings of technologists about the unfavorable consequences of failing to provide technical debt management resources.

Investigations of the degree of correlation between burdens of technical debt and the incidence of rejected or severely curtailed proposals for resources to support technical debt management programs could determine the significance of the Dunning-Kruger effect relative to the problem of technical debt. Also rewarding would be a survey of the nearly 200 known cognitive biases, to determine which of them might be most likely to affect decision-making relative to technical debt, and how best to mitigate the risks they present.

References

[Austin 1996] Robert D. Austin. Measuring and Managing Performance in Organizations. New York: Dorset House, 1996. ISBN:0-932633-36-6

Contains an extensive discussion of the consequences of partial supervision of performance. Since technical debt can only be partially supervised, the concept is relevant to understanding the effects of performance management systems on technical debt. 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:

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

Available here; Retrieved January 10, 2016.

Cited in:

[Gaskin 1991] Steven P. Gaskin, Abbie Griffin, John R. Hauser, Gerald M. Katz, and Robert L. Klein. “Voice of the Customer,” Marketing Science 12:1, 1-27, 1991.

Cited in:

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

Order from Amazon

Cited in:

[Kohn 1999] Alfie Kohn. Punished by rewards: The trouble with gold stars, incentive plans, A's, praise, and other bribes. Boston: Houghton Mifflin Harcourt, 1999. ISBN:0-395-71090-1

Order from Amazon

Cited in:

[Kruger 1999] Justin Kruger and David Dunning. “Unskilled and Unaware of It: How Difficulties in Recognizing One's Own Incompetence Lead to Inflated Self-Assessments,” Journal of Personality and Social Psychology, 77:6, 1121-1134, 1999.

Cited in:

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

Available: here; Retrieved: May 9, 2017.

Cited in:

[Mattis 2008] James N. Mattis. “USJFCOM Commander’s Guidance for Effects-based Operations,” Joint Force Quarterly 51, Autumn 2008 105-108.

Available: here; Retrieved November 9, 2017.

Cited in:

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

Available: here; Retrieved November 10, 2017.

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

The first report of the halo effect. Thorndike found unexpected correlations between the ratings of various attributes of soldiers given by their commanding officers. Although the halo effect was thus defined only for rating personal attributes, it has since been observed in assessing the attributes of other entities, such as brands. Available: here; Retrieved: December 29, 2017

Cited in:

[Weinstein 1996] Neil D. Weinstein and William M. Klein. “Unrealistic Optimism: Present and Future,” Journal of Social and Clinical Psychology 15:1, 1-8, 1996. doi:10.1521/jscp.1996.15.1.1

Cited in:

[Wight 2017] Philip Wight. “How the Alaska Pipeline Is Fueling the Push to Drill in the Arctic Refuge,” YaleE360, Yale School of Forestry & Environmental Studies, November 16, 2017.

Available: here; Retrieved: February 8, 2018

Cited in:

[Yen 2015] Terry Yen, Laura Singer. “Oil exploration in the U.S. Arctic continues despite current price environment,” Today in Energy blog, U.S. Energy Information Administration, June 12, 2015.

Available: here; Retrieved: February 8, 2018.

Cited in:

Other posts in this thread

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Technological communication risk

Last updated on February 1st, 2018 at 07:32 am

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

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

Technological communication risk is the risk that knowledgeable people within the enterprise don’t communicate important knowledge to the people who need it, or the people who need it aren’t receptive to it. Policymakers can address this problem by working to define the roles of all involved to specify the need for this communication, and the need to be receptive to it.

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

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

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

Situations like these can lead to the formation of new non-strategic technical debt in circumstances such as the following:
  • Management directs the technologists to produce capabilities using approaches known to the technologists to be technological dead ends.
  • Management directs the technologists to implement capabilities that don’t exploit known approaches that could open new and vital lines of business.
  • Management directs the technologists to focus resources on initiatives that in the view of the technologists lack sufficient technological imperative.

Policymakers can mitigate technological communication risk by establishing internal standards that encourage knowledgeable technologists to share what they know with internal customers, project sponsors, or senior management. Similarly, those standards can encourage internal customers, project sponsors, product owners, product managers, and senior management to take heed when knowledgeable technologists do speak up.

References

[Austin 1996] Robert D. Austin. Measuring and Managing Performance in Organizations. New York: Dorset House, 1996. ISBN:0-932633-36-6

Contains an extensive discussion of the consequences of partial supervision of performance. Since technical debt can only be partially supervised, the concept is relevant to understanding the effects of performance management systems on technical debt. 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:

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

Available here; Retrieved January 10, 2016.

Cited in:

[Gaskin 1991] Steven P. Gaskin, Abbie Griffin, John R. Hauser, Gerald M. Katz, and Robert L. Klein. “Voice of the Customer,” Marketing Science 12:1, 1-27, 1991.

Cited in:

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

Order from Amazon

Cited in:

[Kohn 1999] Alfie Kohn. Punished by rewards: The trouble with gold stars, incentive plans, A's, praise, and other bribes. Boston: Houghton Mifflin Harcourt, 1999. ISBN:0-395-71090-1

Order from Amazon

Cited in:

[Kruger 1999] Justin Kruger and David Dunning. “Unskilled and Unaware of It: How Difficulties in Recognizing One's Own Incompetence Lead to Inflated Self-Assessments,” Journal of Personality and Social Psychology, 77:6, 1121-1134, 1999.

Cited in:

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

Available: here; Retrieved: May 9, 2017.

Cited in:

[Mattis 2008] James N. Mattis. “USJFCOM Commander’s Guidance for Effects-based Operations,” Joint Force Quarterly 51, Autumn 2008 105-108.

Available: here; Retrieved November 9, 2017.

Cited in:

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

Available: here; Retrieved November 10, 2017.

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

The first report of the halo effect. Thorndike found unexpected correlations between the ratings of various attributes of soldiers given by their commanding officers. Although the halo effect was thus defined only for rating personal attributes, it has since been observed in assessing the attributes of other entities, such as brands. Available: here; Retrieved: December 29, 2017

Cited in:

[Weinstein 1996] Neil D. Weinstein and William M. Klein. “Unrealistic Optimism: Present and Future,” Journal of Social and Clinical Psychology 15:1, 1-8, 1996. doi:10.1521/jscp.1996.15.1.1

Cited in:

[Wight 2017] Philip Wight. “How the Alaska Pipeline Is Fueling the Push to Drill in the Arctic Refuge,” YaleE360, Yale School of Forestry & Environmental Studies, November 16, 2017.

Available: here; Retrieved: February 8, 2018

Cited in:

[Yen 2015] Terry Yen, Laura Singer. “Oil exploration in the U.S. Arctic continues despite current price environment,” Today in Energy blog, U.S. Energy Information Administration, June 12, 2015.

Available: here; Retrieved: February 8, 2018.

Cited in:

Other posts in this thread

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