Degrees of wickedness

Last updated on July 12th, 2021 at 09:23 am

Window blinds with some slats open and some closed, a metaphor for the degrees of wickedness of a wicked problem
Window blinds with some slats open and some closed, a metaphor for the degrees of wickedness of a wicked problem. Think of the slats as the wicked problem criteria of Rittel and Weber. A closed slat is a criterion satisfied; a partially open slat is a criterion satisfied to some extent. A wicked problem has all slats closed; a tame problem has at least one slat at least partially open. When only a few slats are open, the problem isn’t a wicked problem, but finding a solution might be very difficult. The number of open slates corresponds to the degrees of wickedness of most technical debt retirement project design problems. When even one slat is partially open, we can peek through the blinds, and use that information to pry open other slats.

In a recent post I explored conditions that tend to make designing a project to retire technical debt a wicked problem. And in another post I noted some conditions that tend to make designing a project to retire technical debt a super wicked problem. But not all technical debt retirement project design efforts are wicked problems. “Wickedness” can occur in degrees. Designing these projects can be a tame problem, especially if we incurred the technical debt recently. In this post I explore degrees of wickedness in retiring technical debt. I propose a framework for dealing with technical debt retirement project design problems that are less-than-totally wicked.

The degrees of wickedness of a problem

As a quick review, here are the attributes of wicked problems as Rittel and Webber see them [Rittel 1973], rephrased for brevity:

  1. There is no clear problem statement
  2. There’s no way to tell when you’ve “solved” it
  3. Solutions aren’t right/wrong, but good/bad
  4. There’s no ultimate test of a solution
  5. You can’t learn by trial-and-error
  6. There’s no way to describe the set of possible solutions
  7. Every problem is unique
  8. Every problem can be seen as a symptom of another problem
  9. How you explain the problem determines what solutions you investigate
  10. The planner (or designer) is accountable for the consequences of trying a solution

Rittel and Webber held that wicked problems possessed all of these characteristics, but Kreuter, et al., take a different view, which I find compelling [Kreuter 2004]. Their view is that wicked problems and tame problems lie at opposite ends of a spectrum. A problem that satisfies all ten of the criteria would lie at the wicked end of the spectrum; one that satisfies none would lie at the tame end.

The ten criteria aren’t black-and-white

A close examination of Rittel’s and Webber’s ten criteria reveals that they aren’t black-and-white. We can regard each one as occurring in various degrees. For example, consider Criterion 1: “There is no clear problem statement,” which Rittel and Webber express as, “There is no definitive formulation of a wicked problem.” Burge and co-author McCall, who was a student of Rittel, offer this interpretation [Burge 2015]:

Here by the term formulation Rittel means the set of all the information need [sic] to understand and to solve the problem. By definitive, he means exhaustive.

The original language of Rittel and Webber, with the interpretation of Burge and McCall, is black-and-white. But we can imagine problems that satisfy this criterion to varying degrees. That is, one problem formulation might have almost everything needed to understand and solve the problem, while another might have almost none of what’s needed. In some cases, the problem solver might make progress toward a solution by making reasonable assumptions to fill gaps. Or the formulation as given might be incomplete. If so, by working on a solution despite gaps, the missing information might reveal itself, or it might arrive as a result of other research.

A continuum hypothesis

For these reasons, I regard the degree to which a problem satisfies Criterion 1 as residing on a continuum. And I expect that we could find analogous arguments for all ten criteria. This “continuum hypothesis” doesn’t conflict with the definition of a wicked problem. Wickedness still requires that all ten criteria be satisfied absolutely. But how well the problem satisfies the criteria of Rittel and Webber determines its position on the Tame/Wicked spectrum. In other words, as we address the problem of designing a technical debt retirement project, we can consider the degree of wickedness of the problem, not merely whether a problem is wicked.

The degree of a problem’s wickedness provides useful guidance. If a problem clearly satisfies nine of the ten criteria, but not the tenth, according to Rittel and Webber, it would not be a wicked problem. Because solving it might be extraordinarily difficult, we would treat it as wicked with respect to the nine criteria it satisfies. We would use that information to guide our decisions about resource choice and resource allocation. The model of wicked problems provided by Rittel and Webber would be useful, even though the problem itself might not meet their definition.

And so emerges the concept of the dimensionality of wickedness.

The dimensionality of wickedness

We can regard the ten criteria of Rittel and Webber as dimensions in a ten-dimensional space. When we do, our “wickedness spectrum” becomes much richer. Maybe too rich, in the sense that its complexity presents difficulty when we try to think about it. But the concept of dimensionality of wickedness can be useful, if we consider each dimension as having a degree of wickedness. This enables us to choose problem-solving techniques that work well for wicked problems that owe their wickedness to specific dimensions. That is the approach of Kreuter, et al. [Kreuter 2004].

This suggests a framework for designing (or redesigning) technical debt retirement projects:

  • Deal separately (and first) with any parts of the technical debt retirement project design problem that are tame
  • Determine the importance of each one of a set of “nine indicators of wickedness
  • Use that information to determine which of the ten criteria of Rittel and Webber are most relevant to this particular technical debt retirement project design problem
  • Apply established approaches that account for the relevant criteria to formulate a project design

This program is too much for a single post. But I can make a start in my next post with descriptions of the indicators of wickedness. That post includes an examination of the implications of each of these indicators relative to the presence of each of the ten criteria of Rittel and Webber. The next step will be to suggest techniques for technical debt retirement project design problems that meet, to some degree, the criteria of Rittel and Webber.

Buckle up.

References

[Burge 2015] Janet E. Burge and Raymond McCall. “Diagnosing Wicked Problems,” Design Computing and Cognition 14, 2015, 313-326.

Available: here; Retrieved: October 25, 2018

Cited in:

[Kreuter 2004] Marshall W. Kreuter, Christopher De Rosa, Elizabeth H. Howze, and Grant T. Baldwin. “Understanding wicked problems: a key to advancing environmental health promotion.” Health Education and Behavior 31:4, 2004, 441-454.

Available: here; Retrieved: October 26, 2018

Cited in:

[Rittel 1973] Horst W. J. Rittel and Melvin M. Webber. “Dilemmas in a General Theory of Planning”, Policy Sciences 4, 1973, 155-169.

Available: here; Retrieved: October 16, 2018

Cited in:

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Retiring technical debt can be a super wicked problem

Last updated on July 10th, 2021 at 10:51 am

In my last post I provided a list of attributes of wicked problems [Rittel 1973]. I included the reasons why I feel that designing technical debt retirement projects can be wicked problems. As a review, here are the attributes of wicked problems as Rittel and Webber see them, rephrased for brevity:

  1. Wicked problems have no definitive formulation
  2. Wicked problems have no stopping rule
  3. Solutions to wicked problems aren’t true-or-false; they’re good-or-bad
  4. There is no immediate ultimate test of a solution to a wicked problem
  5. Every solution to a wicked problem is a “one-shot operation”; because there is no opportunity to learn by
    trial-and-error, every attempt counts significantly
  6. Wicked problems do not have an enumerable (or an exhaustively describable) set of potential solutions; nor is there a
    well-described set of permissible operations that we can incorporate into the plan
  7. Every wicked problem is essentially unique
  8. We can regard every wicked problem as a symptom of another problem
  9. The existence of a discrepancy representing a wicked problem can be explained in numerous ways. The choice of explanation
    determines the nature of the problem’s resolution
  10. The planner (or designer) has no right to be wrong

Four properties of super wicked bproblems

We can regard a subset of wicked problems as super wicked [Levin 2012]. Levin, et al. list the following four properties of super wicked problems. With each one, I’ve added reasons why planning a technical debt retirement project can qualify as a super wicked problem.

Time is running out

Super wicked problems have inherent timescales. For example, many believe that climate change will become irreversible within 30 years if current practices continue.

Technical debt retirement can have an inherent time scale. For example, Microsoft ended mainstream support for Windows 7 in January 2015. At that time, computers running Windows 7 incurred a technical debt. Yet by September 2018, 46.7% of computers running Windows were still running Windows 7. That was a 0.6% increase from the previous month [Keizer 2018]. At this writing, standard support will end in January 2020. That confers a timescale on this kind of technical debt.

When time runs out for solving wicked problems, the consequences can be severe. With respect to Windows 7, the consequences are more serious than forcing conversion to Windows 10. Some applications running on those machines might be compatible with Windows 10, but some might require udates. And all users of converted machines must learn how to use Windows 10 and any updated or replaced applications. So there’s also a training issue, a learning curve, and period of elevated user error rates.

Letting a time-boxed technical debt remain in place can be financially dangerous. As the retirement window closes, the cost of debt retirement concentrates on a declining number of fiscal quarters. If retirement costs are high enough, the impact of debt retirement on net income can be severe and negative. For enterprises whose securities are publicly traded, this effect can be costly for shareholders. At this writing there are only about five fiscal quarters remaining for Windows 10 conversions. For other technical debts, the number of fiscal quarters available for diluting the costs of retirement might be more—or less.

Those who cause the problem also advocate a solution
Two pilots line up their F/A-22 Raptor behind a tanker
Two pilots line up their F/A-22 Raptor behind a tanker. When Hurricane Michael made landfall on October 10, 2018, it passed over Tyndall Air Force Base. Tyndall has responsibility for air dominance training for F-22s. As Hurricane Michael approached, 33 of the 55 F-22s at Tyndall were repositioned to Wright-Patterson Air Force Base in Ohio [Phillips 2018a]. The remaining aircraft at Tyndall were undergoing maintenance and weren’t operational [Gabriel 2018]. The storm damaged some of them, but they’re believed to be repairable.

Because of climate change [Cook 2016], increases in storm intensity and frequency are likely. Air bases in coastal regions are at risk [Phillips 2018b]. They now constitute a technical debt. Relocating them could be a wicked problem, and possibly a super wicked problem. But if federal policies continue to fail to address climate change, they could prevent relocation. If that happens, the policies themselves represent a technical debt. U.S. Air Force photo by TSgt Ben Bloker, courtesy Wikipedia

The phrase “seek to provide a solution” might be somewhat tactful. I expect that some super wicked problems have the property that those who cause the problem exert some degree of control over what kinds of solutions are acceptable, or even discussible. In many cases, this represents a conflict of interest that can prevent the organization from deploying the more effective options.

That conflict of interest is certainly present in the context of many technical debt retirement projects. Technical debt formation and persistence are due, in part, to a failure to commit resources to retiring it, or, at least, to inhibiting its formation. That failure is the responsibility of those in leadership roles in the enterprise. Typically, these are the same people who must decide to commit resources to retire technical debt in the future.

The central authority needed to address the problem is weak or nonexistent

Again, I find this description unnecessarily limiting. I would prefer a phrasing such as, “The central authority, for whatever reason, chooses to exert, or is unable to exert, its authority in furtherance of solution, or even investigation.” In other words, the central authority need not be weak for it to be a source of difficulty in addressing the super wicked problem. It need only choose not to act. This can happen when those who cause the problem are the people who constitute the central authority, or they capture the central authority, or they capture the function to which the central authority has delegated responsibility for solution.

With respect to technical debt retirement, consider this scenario. At AMUFC, A Made-Up Fictitious Corporation, the sales and marketing functions have repeatedly struggled with the engineering function for shares of budget resources. Engineering has argued repeatedly, and unsuccessfully, that it needs additional resources to address the technical debt that has accumulated in several products. But the CEO is a former VP Sales, and a close friend of the CFO. Together, they have always decided to defer technical debt retirement in favor of new products and enhancements favored by the VP Marketing, by customers, and by investors.

Scenarios like this are common. Enterprise leadership is strong, but not inclined to address the technical debt retirement issue.

Partly as a result, policy responses discount the future irrationally

Irrational discounting of future costs and benefits occurs when policies are deployed that give too much emphasis to producing short-term benefits and/or to avoiding short-term costs or inconveniences. Benefits are pulled in from the future towards the present; costs and inconveniences are pushed out toward the future and deferred. One form of this discounting scheme—one of many—is hyperbolic discounting.

This tendency is one way of distracting attention from the actual problem. It is the principal tactic that enables the persistence of technical debt, and the means by which enterprises repeatedly defer attention to the problem of retiring technical debt.

Both the problem of managing technical debt and the problem of designing technical debt retirement projects, exhibit all of these properties to some degree. It’s likely, in my view, that these problems are super wicked problems.

Intervention strategies for super wicked problems

Levin, et al., recommend four distinct strategies for resolving super wicked problems [Levin 2012]. They are all approaches to devising policies that are difficult to alter, thus committing the organization to a particular path forward.

Lock-in

Lock-in is usually regarded as dysfunctional adherence to a strategy or course of action despite the existence of superior alternatives [Brenner 2011]. It occurs when a policy confers some kind of immediate benefit on a subset of the population. If that benefit is significant, if the population subset would be harmed by alterations of the policy that remove the benefit, and if the subset has enough political power to defend the benefit, the policy will be “locked in” and thus difficult to change. Levin, et al., suggest that this phenomenon can serve a beneficial purpose by protecting a constructive policy, thus preventing its abandonment.

Most technical debt retirement efforts focus solely on retiring the debt. All (or most) of the benefit appears in the form of increased engineering productivity, decreased sources of frustration for engineers, or increased engineering agility. Benefits for non-engineering stakeholders tend to be indirect. To establish policies that exploit lock-in we must craft them so that they provide ongoing, direct benefit to the most politically powerful stakeholders. For example, addressing first the forms of technical debt that are most likely to lead to product innovations that non-engineering stakeholders would value highly could cause those stakeholders to favor further technical debt retirement efforts.

Positive feedback

Exploiting lock-in makes policies durable when people or organizations already supporting the policy derive some kind of increased benefit, leading to others not yet supporting or covered by the policy to decide to support it. This mechanism is sometimes known as a “network effect.” When network effects are present, the value of a product or service increases as the size of the population using it increases [Shapiro 1998].

To exploit network effects when devising technical debt retirement efforts, focus on retiring the kinds of technical debts that confer benefits on stakeholders of platform assets. A platform asset is an asset that supports multiple other assets. Examples: an application development tool suite, a product line architecture, or an enterprise data network. Platform assets that support collaboration communities are more likely to generate network effects.

Increasing Returns

Policies and interventions that enable increasing returns to the population are more likely to be durable than those that offer steady returns. Because people adapt to steady levels of stimuli, policies that produce a change in the context only during the period immediately following initial adoption of those policies are less likely to maintain popular support than are policies that continue to provide increasing returns as long as they’re in place.

But among policies that provide increasing returns, Levin, et al., identify two types. Type I policies, which are less durable, confer their benefits on an existing population of supporters. They don’t cause others to become supporters. Type II policies also confer benefits on supporters, but they do cause others to become supporters. They are thus far more durable than are Type I, because they foster growth in the supporting population.

Framing technical debt retirement projects as individual projects with the objective of retiring a specified kind of technical debt is likely to lead to the enterprise population viewing the effort as a Type I policy at best. But framing each project as a phase of a longer-term effort could position the larger effort as a Type II policy, if the larger effort affects increasing portions of the enterprise population.

Self-reinforcing

Self-reinforcing policies create a dynamic that makes them more durable. Reinforcement can come about for two reasons. It can be a result of increases in the benefits the policy generates, or it can result from increases in the cost of rescinding the policy. In some cases, reinforcement can result from a combination of both effects. As with the strategy of Increasing Returns, there are two types of self-reinforcing policies. Type I self-reinforcing policies focus on maintaining support for the policy within the subset of the population consisting of its original supporters. In analogy with Type II Increasing Returns policies, Type II Self-reinforcing policies affect both the original supporting population and portions of the population not yet affected directly by the policy.

To exploit self-reinforcement, technical debt retirement programs must emphasize retiring debts that have curtailed organizational agility in recognizable ways, or which have prevented introduction of capabilities that the population values. Communicating these objectives is an important part of the program, because self-reinforcing popular support is possible only if the population understands the strategy and how it benefits the enterprise.

Last words

Because of the essential uniqueness of any wicked problem (Proposition 7 of Rittel and Webber), it is futile to attempt to apply as a template any retirement program that worked for some other organization, or for some other portion of a given organization at an earlier time with a different form of technical debt. But these four strategies, implemented carefully and communicated widely and effectively within the organization, can build organizational commitment to a long-term technical debt retirement program, even though retiring technical debt may be a super wicked problem.

References

[Brenner 2011] Richard Brenner. “Indicators of Lock-In: I,” Point Lookout 11:12, March 23, 2011.

Available: here; Retrieved: October 23, 2018.

Cited in:

[Burge 2015] Janet E. Burge and Raymond McCall. “Diagnosing Wicked Problems,” Design Computing and Cognition 14, 2015, 313-326.

Available: here; Retrieved: October 25, 2018

Cited in:

[Cook 2016] John Cook, Naomi Oreskes, Peter T. Doran, William R.L. Anderegg, Bart Verheggen, Ed W. Maibach, J. Stuart Carlton, Stephan Lewandowsky, Andrew G. Skuce, Sarah A. Green, Dana Nuccitelli, Peter Jacobs, Mark Richardson, Bärbel Winkler, Rob Painting, and Ken Rice. “Consensus on consensus: a synthesis of consensus estimates on human-caused global warming,” Environmental Research Letters 11, 2016, 048002.

Available: here; Retrieved: October 23, 2018

Cited in:

[Gabriel 2018] Melissa Gabriel. “Hurricane Michael: Fate of costly stealth fighter jets at Tyndall Air Force Base still unknown,” USA Today: Pensacola News Journal, October 17, 2018.

Available: here; Retrieved: October 23, 2018

Cited in:

[Keizer 2018] Gregg Keizer. “Windows by the numbers: Windows 10 backtracks, Windows 7 remains resilient,” Computerworld, October 2, 2018.

Available: here; Retrieved: October 18, 2018

Cited in:

[Kreuter 2004] Marshall W. Kreuter, Christopher De Rosa, Elizabeth H. Howze, and Grant T. Baldwin. “Understanding wicked problems: a key to advancing environmental health promotion.” Health Education and Behavior 31:4, 2004, 441-454.

Available: here; Retrieved: October 26, 2018

Cited in:

[Levin 2012] Kelly Levin, Benjamin Cashore, Steven Bernstein, and Graeme Auld. “Overcoming the tragedy of super wicked problems: constraining our future selves to ameliorate global climate change,” Policy Science 45, 2012, 123–152.

Available: here; Retrieved: October 17, 2018

Cited in:

[Phillips 2018a] Dave Phillips. “Tyndall Air Force Base a ‘Complete Loss’ Amid Questions About Stealth Fighters,” The New York Times, October 11, 2108.

Available: here; Retrieved: October 23, 2018

Cited in:

[Phillips 2018b] Dave Phillips. “Exposed by Michael: Climate Threat to Warplanes at Coastal Bases,” The New York Times, October 17, 2108.

Available: here; Retrieved: October 23, 2018

Cited in:

[Rittel 1973] Horst W. J. Rittel and Melvin M. Webber. “Dilemmas in a General Theory of Planning”, Policy Sciences 4, 1973, 155-169.

Available: here; Retrieved: October 16, 2018

Cited in:

[Shapiro 1998] Carl Shapiro and Hal R. Varian. Information rules: a strategic guide to the network economy. Harvard Business Press, 1998.

Cited in:

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Retiring technical debt can be a wicked problem

Last updated on July 16th, 2021 at 07:38 pm

Prototypes of President Trump’s “border wall.”

Prototypes of President Trump’s “border wall.” Building the wall is an example of a wicked problem. Building prototypes in short segments of the wall is a tame problem. But these are just prototypes of short segments of the wall. They aren’t prototypes of the project.

Prototypes of the wall itself don’t demonstrate the process for taking private property, or how to build construction access roads, or the effects on wildlife, or how the government of Mexico will respond, or how to repair the wall when drug gangs destroy sections of it in isolated regions, or even the effectiveness of the wall. Prototyping works well for tame problems. It helps us project how the finished project will perform, and how difficult completing the project will be. But for wicked problems, prototyping is of limited value. As Rittel observes, prototyping can make the problem worse.

Photo by Mani Albrecht, U.S. Customs and Border Protection Office of Public Affairs, Visual Communications Division.

The theory of wicked problems originated with Horst Rittel in the mid-1960s. He was addressing “that class of problems which are ill-formulated, where the information is confusing, where there are many decision makers and clients with conflicting values, and where the ramifications in the whole system are confusing.” [Churchman 1967] The term wicked isn’t a moral judgment. It suggests the mischievous streak in these problems. Many of them have the property that proposed solutions can lead to conditions even more problematic than the original situation. Is it just me, or are you also thinking, “Ah, technical debt”? In this post, I suggest that retiring technical debt can be a wicked problem. I’ll show how wickedness explains many of the difficulties we associate with retiring forms of technical debt that involve many stakeholders, assets, revenue streams, policies, or strategies.

Introduction

Horst Rittel was a design theorist at the University of California at Berkeley. His interest in wicked problems came about because designers must deal with the interactions between architecture and politics. In today’s technology-dependent enterprises, analogous problems arise when we retire technical debt. When we do, we affect multiple sets of quasi-independent stakeholders.

Applicability to the technical debt problem

In the years since Rittel originated the wicked problem concept, others have extended it. These extensions have led some to regard the concept as inflated and less than useful. But extension or less-than-useful concepts rarely occurs, I take it as an indicator of worth. The focus of this post, then, is applying Rittel’s version of wicked problems to the problem of designing a complex technical debt retirement project.

The wicked problem concept has propagated mostly in the realm of public policy and social planning. Certainly wicked problems abound there. Poverty, crime control, and climate change are examples. But I know of no attempt to explore the wickedness of retiring technical debt in large enterprises, but have a look below and see what you think.

Rittel defines a problem as the discrepancy between the current state of affairs and the “state as it ought to be.” For the purposes of technical debt retirement planning, the state as it ought to be might at times be a bit ambitious. So I take the objective of a technical debt retirement project to be an attempt to resolve the discrepancy between the current state of affairs and some other state that’s more desirable. For the present purpose, then, the problem is designing a technical debt retirement project that converts the current state of an asset to a more desirable state that might still contain technical debt in some form. But in that new state, the asset is in a better configuration.

A note on super-wicked problems

Actually, there is a subset of wicked problems—super-wicked problems—that I think might include some technical debt retirement problems. I address them in the post “Retiring technical debt can be a super wicked problem.”

For now, though, let’s examine the properties of wicked problems. Let’s see how well they match up with the problem of designing technical debt retirement projects.

Attributes of wicked problems

Rittel’s summary of the attributes of wicked problems [Rittel 1973] convinced me that major technical debt retirement projects present wicked problems. Here are those attributes. In what follows, I use Rittel’s term tame problem to refer to a problem that isn’t wicked. (See also [Kreuter 2004])

1. [No Definitive Formulation] Wicked problems have no definitive formulation

For any given tame problem, it’s possible to state it in such a way that it provides the problem-solver all information necessary to solve it. That’s what definitive formulation means. For wicked problems, on the other hand, our understanding of the problem depends on the solution we’re considering. Each candidate solution might potentially require its own understanding of the problem.

When designing a technical debt retirement project, we must fully grasp the impact of the effort on all activities in the enterprise. Each proposed project plan has its own schedule and risk profile. Each proposed project plan affects enterprise activities in its own way. In principle, each candidate approach to the effort affects a different portfolio of enterprise assets in its own unique order. Because examining all possible candidate project plans is impractical, choosing a project plan by seeking an optimal set of effects is also impractical. By the time you’re ready to execute a given project plan, the data supporting your decision might be obsolete.

2. [No Stopping Rule] Wicked problems have no stopping rule

For any given tame problem, solutions have “stopping rules.” Stopping rules of solutions are signatures that indicate clearly that they are indeed solutions. For example, in a chess problem to be solved in N moves, N and checkmate provide a stopping rule. We know how to count to N and the position of checkmate is well defined.

Wicked problems have no stopping rule.

When planning a major technical debt retirement project, we must determine the attributes of the project. The attributes include a task breakdown, a sequence for performing the tasks, a resource array including both human and non-human resources, a risk plan including risk mitigations and risk responses, a revenue stream interruption schedule, and so on. For each such plan, we can estimate the direct and indirect costs to the enterprise. We can project the effects of the plan on market share for every affected product or service. Every plan has these attributes. When we compute them for a given candidate plan, the result doesn’t reveal that we’ve found “the solution.” We will have found only an estimate for that given solution. What we learn by doing this doesn’t reveal whether or not a “better” solution exists.

There is no indicator contained in any given candidate solution that tells us we can “stop” solving the problem. Most often, we just stop when we run out of time for finding solutions. In some cases, we stop when we find just one solution.

3. [Solutions Are Good/Bad] Solutions to wicked problems aren’t true-or-false, but good-or-bad

The criteria for finding solutions to tame problems are unambiguous. For example, if a candidate function satisfies a differential equation, it’s a solution to the equation. The volume of concrete required to pave a section of roadway is a single number, determined by computing the area of roadway and multiplying by the thickness of the roadbed, and subtracting the volume of any reinforcing steel.

The solutions to wicked problems have no such clarity. When evaluating a candidate project plan for retiring a technical debt, we can estimate its cost, the time required, interruptions in revenue streams, and the timing of resource requirements. But determining how “good” that is might be difficult. Much depends on what other demands there might be for those resources or funds. Much also depends on the political power of the people making those demands. No single number measures that.

4. [No Test of Solutions] There is no immediate ultimate test of a solution to a wicked problem

To test a candidate solution to a tame problem, the problem-solving team determines whether the solution meets the requirements set in the tame problem statement. The consequences of implementing the solution are all evident to the problem-solving team. The team has everything it needs to judge the success of the solution.

Not so with wicked problems. Any candidate solution to a wicked problem generates waves of consequences. As these waves propagate, some of the problem’s stakeholders might find the solution unsatisfactory. They’ll report their objections, possibly through politically powerful people or organizations. Because the consequences can be so diverse, the team can’t anticipate all of them. In some cases, the team might have difficulty understanding how the troubles that plague some stakeholders were actually related to the implemented solution. Some undesirable consequences can be far more harmful than any intended benefits are helpful. In other cases, the undesirable consequences might remain undiscovered until long after the solution is in use and operational.

When designing a technical debt retirement project, it’s necessary to determine everything that must be changed, what resources must be assembled to do the work, and what processes might be interrupted, when and for how long. Only rarely, if ever, can we determine all of that with certainty in advance. For that reason, determining that the design of the project is “correct” isn’t possible, except perhaps in the probabilistic sense. We never really know in advance that we’ve found a solution. Most of the time, after execution begins, we must make adjustments along the way, in real time.

5. [No Trial-and-error] Every solution to a wicked problem is a “one-shot operation”; because there is no opportunity to learn by trial-and-error, every attempt counts significantly

When solving tame problems, we can try candidate solutions without incurring significant penalties. That is, trying a solution might require some effort, and therefore incur a cost. But it doesn’t otherwise affect the ability to find other solutions. Wicked problems are different. Every attempt to “try” a solution leaves traces that can potentially make further solution attempts more difficult, costly, or risky than they would have been if we hadn’t tried that solution. These traces of past solution attempts might also impose constraints on future solutions. Those constraints can effectively transform the wicked problem into a different wicked problem. This property makes trial-and-error approaches undesirable and possibly infeasible. Indices of such undesirability are the half-lives of the traces of attempts to address the problem. A long half-life might mean that the problem solver has only one shot at addressing the problem.

When designing a technical debt retirement project, we sometimes try to “pilot” a potential approach to determine difficulty, costs, feasibility, political issues, or risk profiles. Even when we can revert the asset to its former state after a pilot is completed or suspended, the consequences for stakeholders and for stakeholder operations might not be reversible. When we next try another “pilot,” or perhaps a fully committed retirement project, these stakeholders might be significantly less willing to cooperate. Every attempted solution can thus leave political or financial traces like these, making future attempts riskier and more challenging.

6. [Solutions Are Not Describable] Wicked problems don’t have an enumerable (or an exhaustively describable) set of potential solutions, nor is there a well-described set of permissible operations that we can incorporate into the plan

In devising solutions to tame problems, one common approach entails first gathering the full set of possibilities. Next, we screen them according to a set of favorability criteria. Reducing the field of possibilities is a useful strategy for finding optimal or acceptable solutions to tame problems.

Wicked problems defy such strategies. Gathering the full set of possible solutions to a given wicked problem can be a wicked problem in itself. We cannot parameterize the set of possible solutions to a wicked problem. We cannot define a finite set of attributes that fully covers the solution space. For these reasons, we can never be certain that the set of candidate solutions is complete.

Candidate designs for technical debt retirement projects present this same quality. We have a dizzying array of choices. In what order should we retire different kinds of technical debts? In what order should we address the debts different assets bear? Can we “refinance” portions of the debt to intermediate forms [Zablah 2015]? What kinds of refactoring should we perform and when? Because options like these are neither denumerable nor parameterizable, we cannot know whether a given set of candidate project designs is complete.

7. [Essential Uniqueness] Every wicked problem is essentially unique

Among tame problems, we can define classes or categories of problems that share a solution method. That is, using the method associated with a given class, we can solve all problems in that class. For example, we can solve all second order linear differential equations with the same method.

Even though we can define classes of wicked problems whose members are in some sense similar, that similarity doesn’t enable us to find a unified solution strategy that works for every member of the class.

So it is with designing technical debt retirement projects. Certainly, the collection of all technical debt retirement projects is a class. But the problem of designing a given retirement project is essentially unique. What “works” for one project in one enterprise in one fiscal year probably won’t work for another project in another enterprise in another fiscal year. It might not even work for another project in that same enterprise in that same fiscal year. Elements of the solution for one project might be useful for another project. But even then, we might need to adapt them to the conditions of that next project.

This essential uniqueness property of technical debt retirement projects collides with a common pattern decision makers use when chartering major efforts. That pattern is reliance on consultants, employees, or contractors who “have demonstrated success and experience with this kind of work.” Because each technical debt retirement project is essentially unique, relying on a history of demonstrated success is a much less viable strategy than it would be with tame problems. Decision makers would do well to keep this in mind when they seek approaches, leaders, and staff for major technical debt retirement efforts: no major technical debt retirement project is like any other.

8. [Problems as Symptoms] We can regard every wicked problem as a symptom of another problem

With tame problems or wicked, we typically begin the search for solutions by inquiring as to the cause of the current condition. When we find the cause or causes, and remove them, we usually find a new problem underlying them. Thus, for wicked problems, what we regarded initially as the problem is thereby converted into a symptom of a newly recognized underlying problem. By repeating this process, we escalate the “level” of the problem we’re addressing. Higher-level problems do tend to be more difficult to resolve, but addressing symptoms, though easier, isn’t a path to ultimate resolution.

Rittel also observes that incremental approaches to resolving wicked problems can be self-defeating. The difficulty arises from the traces left behind by incrementalism, as described in the discussion of the unworkability of trial-and-error strategies. Rittel provides the example of the increase in difficulty of changing processes after we automate them.

To regard the wicked problem of designing a technical debt retirement project as a symptom of a higher-level wicked problem, we must be willing to regard as problems the very things that make the technical debt retirement project design effort a wicked problem. That is, the processes that lead to formation of technical debt, or that enhance its persistence, are themselves wicked problems. For example, one might inquire about how to change the enterprise culture so as to reduce the incidence of technical debt contagion. To undertake major technical debt retirement efforts without first determining what can be done to limit technical debt formation or persistence due to contagion or due to other processes, might be unwise.

9. [No Controlled Experiments] The existence of a discrepancy representing a wicked problem can be explained in numerous ways. The choice of explanation determines the nature of the problem’s resolution

When addressing tame problems, problem-solving teams can often perform controlled experiments. The general framework of these experiments is as follows. The team forms a hypothesis H as to the cause of the problem, conjecturing a solution. Then assuming H is correct, and given a set of conditions C, they deduce the consequences E that must follow. If any elements of E don’t occur, then H is incorrect. The process repeats until an H’ is found that provides all elements of E. H’ then provides the basis of a solution. Essentially, this is the scientific method.

With wicked problems, the method fails in numerous ways. Foremost among these failure modes is the inability to control C. That is, interventions that might be required to set C to be a desired C0 tend to be impossible. Moreover, even if we can establish C0, the experiments that determine whether E is observed tend to leave the traces discussed in Proposition 5 [No Trial-and-error]. Finally, the determining the presence or absence of the elements of E is usually subjective.

When planning enterprise-scale technical debt retirement projects, as with many projects of similar scale, we believe that we can benefit from running a pilot of our proposed plan, to determine its fitness. These trials are sometimes called “proof of concept” exercises. However, because we cannot control the conditions in which we execute the pilot, we cannot be confident that our interpretation of the results of the pilot will apply to the actual project. Moreover, a small-scale pilot cannot generate some of the effects we most want to observe because they occur only at full scale. These effects include staff shortages, resource contention, and revenue interruption incidents.

10. [100% Accountability] The planner (or designer) has no right to be wrong

In solving tame problems, solvers can experiment with proposed solutions. They make conjectures about what might work, and gather the results of trials to determine how to improve their conjectured solutions. There is no social or legal penalty for failed conjectures.

In solving wicked problems, experiments don’t exist. Any trial solution is a real solution, with real effects on stakeholders and later, real effects on the problem solvers themselves. Problem solvers are accountable for the undesirable consequences of each solution, whether it’s a trial or not.

In planning a technical debt retirement project, any attempt to gather data about how the approach would affect the enterprise could potentially have real, lasting, deleterious effects. The project bears the costs associated with these consequences, if not officially and financially, then politically. The politics of failure can lead to serious consequences for the problem solvers. Any approach that the team deploys, on any scale no matter how small, can potentially create financial problems for the enterprise, and political problems for anyone associated with the technical debt retirement project.

Last words

The fit between wicked problems and technical debt retirement project design looks pretty good to me. But the research on a subset of wicked problems—super wicked problems—is also intriguing. I’ll look at that in my next post. After that, we’ll be ready to examine which approaches to retiring technical debt take these matters into account.

References

[Brenner 2011] Richard Brenner. “Indicators of Lock-In: I,” Point Lookout 11:12, March 23, 2011.

Available: here; Retrieved: October 23, 2018.

Cited in:

[Burge 2015] Janet E. Burge and Raymond McCall. “Diagnosing Wicked Problems,” Design Computing and Cognition 14, 2015, 313-326.

Available: here; Retrieved: October 25, 2018

Cited in:

[Churchman 1967] C. West Churchman. “Wicked problems,” Management Science 14:4, 1967, B-141–B-142

Available: here; Retrieved: October 16, 2018

Cited in:

[Cook 2016] John Cook, Naomi Oreskes, Peter T. Doran, William R.L. Anderegg, Bart Verheggen, Ed W. Maibach, J. Stuart Carlton, Stephan Lewandowsky, Andrew G. Skuce, Sarah A. Green, Dana Nuccitelli, Peter Jacobs, Mark Richardson, Bärbel Winkler, Rob Painting, and Ken Rice. “Consensus on consensus: a synthesis of consensus estimates on human-caused global warming,” Environmental Research Letters 11, 2016, 048002.

Available: here; Retrieved: October 23, 2018

Cited in:

[Gabriel 2018] Melissa Gabriel. “Hurricane Michael: Fate of costly stealth fighter jets at Tyndall Air Force Base still unknown,” USA Today: Pensacola News Journal, October 17, 2018.

Available: here; Retrieved: October 23, 2018

Cited in:

[Keizer 2018] Gregg Keizer. “Windows by the numbers: Windows 10 backtracks, Windows 7 remains resilient,” Computerworld, October 2, 2018.

Available: here; Retrieved: October 18, 2018

Cited in:

[Kreuter 2004] Marshall W. Kreuter, Christopher De Rosa, Elizabeth H. Howze, and Grant T. Baldwin. “Understanding wicked problems: a key to advancing environmental health promotion.” Health Education and Behavior 31:4, 2004, 441-454.

Available: here; Retrieved: October 26, 2018

Cited in:

[Levin 2012] Kelly Levin, Benjamin Cashore, Steven Bernstein, and Graeme Auld. “Overcoming the tragedy of super wicked problems: constraining our future selves to ameliorate global climate change,” Policy Science 45, 2012, 123–152.

Available: here; Retrieved: October 17, 2018

Cited in:

[Phillips 2018a] Dave Phillips. “Tyndall Air Force Base a ‘Complete Loss’ Amid Questions About Stealth Fighters,” The New York Times, October 11, 2108.

Available: here; Retrieved: October 23, 2018

Cited in:

[Phillips 2018b] Dave Phillips. “Exposed by Michael: Climate Threat to Warplanes at Coastal Bases,” The New York Times, October 17, 2108.

Available: here; Retrieved: October 23, 2018

Cited in:

[Rittel 1973] Horst W. J. Rittel and Melvin M. Webber. “Dilemmas in a General Theory of Planning”, Policy Sciences 4, 1973, 155-169.

Available: here; Retrieved: October 16, 2018

Cited in:

[Shapiro 1998] Carl Shapiro and Hal R. Varian. Information rules: a strategic guide to the network economy. Harvard Business Press, 1998.

Cited in:

[Zablah 2015] Raul Zablah and Christian Murphy. “Restructuring and Refinancing Technical Debt.” Proceedings of the IEEE 7th International Workshop on Managing Technical Debt (MTD). IEEE, 2015.

Available: here; Retrieved: February 13, 2016

Cited in:

Other posts in this thread

Synergy between the reification error and confirmation bias

Last updated on July 10th, 2021 at 08:53 am

In deciding whether to undertake technical debt retirement projects, organizations risk making inappropriate decisions because of a synergy between the reification error and confirmation bias. Together, these two errors of thought create conditions that make committing appropriate levels of resources difficult. And when organizations do commit resources, they tend to underestimate costs. That underestimate can elevate the chance of failure in technical debt retirement projects.

The reification error and confirmation bias

As explained elsewhere in this blog, the reification error is an error of reasoning in which we treat an abstraction as if it were a real, concrete, physical thing. Because technical debt is an abstraction, we risk committing the reification error when we deal with it. (See “Metrics for technical debt management: the basics”)

Confirmation bias is a cognitive bias that causes us to favor and seek only information that confirms our preconceptions, or to avoid information that disconfirms them. (See “Confirmation bias and technical debt”)

How the reification error affects management

The reification error might be responsible, in part, for a widely used management practice that often appears in the exploratory stages of undertaking projects. Let’s start with an illustration from the physical world.

In the physical world, when we want cherries, we go to a market and check the price per pound or kilo. Then we decide how much we want. If the price is high, we might decide to buy fewer cherries. If the price is low, we might buy more cherries. We have in mind a total cost target, and we adjust the weight of the cherries to meet the target. In the physical world, we can often adjust what we purchase to match our willingness to pay.

Retiring technical debt doesn’t work like that, in part, because technical debt is an abstraction. But we try anyway; here’s how it goes. Management decides to retire a particular class of technical debt. They ask an engineer for an estimate of the cost. Sometimes Management reveals the target they have in mind if they have one; sometimes not. The estimate comes back as Total ± Uncertainty. Management decides that’s too high, or the Uncertainty is too great. They then ask the engineer to find a way to do it for less, or to reduce the Uncertainty.

Management—the “customer” in this scenario—makes this request, in part, based on the belief that adjusting the work is possible. Management hopes that the engineer can adjust the work to meet a (possibly unstated) target, in analogy to buying cherries. That thinking is an example of the reification error. In this dynamic, we rarely take into account the fact that retiring technical debt isn’t exactly like buying cherries.

How confirmation bias affects engineering estimates

Return now to the interaction between Management and the engineer/estimator. The engineer now suspects that Management does have a target in mind. Some engineers might ask what the target is. Some don’t. In any case, the engineer makes a lower estimate, which might still be too high. This process repeats until either Management decides against retiring the debt, or accepts the lowest Total ± Uncertainty.

In adjusting their estimates, engineers have a conflict of interest. That conflict of interest can compromise their objectivity through the action of confirmation bias. For technical debt retirement efforts, engineers are usually highly motivated to gain Management approval of the project. The motivation arises, in part, from the frustrating loss of engineering productivity. And since engineers typically sense that Management approval of the project is contingent on finding an estimate that’s low enough, the engineers have a preconception. That is, engineers have an incentive to convince themselves that Management’s adjustments to budget and schedule are reasonable. Because of the confirmation bias, engineers tend to seek justifications for the adjustments. And they tend to avoid seeking justifications for believing that their adjustments might not be feasible. That’s the confirmation bias in action.

How synergy between the reification error and confirmation bias comes about

Because of the reification error, Management tends to believe that retiring technical debt is a more adjustable activity than it actually is. Because of confirmation bias, engineers tend to believe that Management’s proposed cost and schedule are feasible. Too often, the synergy between the two errors of thinking provides a foundation for disaster.

Why this synergy creates conditions for disaster in technical debt retirement projects

Management usually equates estimates with commitments. Engineers don’t. Management usually forgets or ignores the upside Uncertainty. Typically, when Management accepts an estimate, the engineering team finds that it has made a commitment to deliver the work for the cost Total, with zero upside Uncertainty. Rarely does Management make this explicit. An analogous problem occurs with schedule.

By ignoring the Uncertainty, Management (the buyer) transfers the uncertainty risk to the project team. That strategy might work to some extent with conventional development or maintenance projects, where we can adjust scope and risk before the work begins. But for technical debt retirement projects, this practice creates problems for two reasons.

Adjusting the scope of debt retirement projects is difficult

First, with technical debt retirement we’re less able to adjust scope. To retire a class of technical debt, we must retire it in toto. If we retire only some portion of a class of technical debt, we would leave the asset in a mixed state that can actually increase MICs. So it’s usually best to retire the entirety of any class of technical debt, so as to leave the asset in a uniform state.

Debt retirement efforts are notoriously unpredictable

Second, the work involved in retiring a particular class of technical debt is more difficult to predict than is the work involved in more conventional projects. (See “Useful projections of MPrin might not be attainable”) Often, we must work with older assets, or older portions of younger assets. The people who built them aren’t always available, and documentation can be sparse or unreliable. Moreover, it’s notoriously difficult to predict with accuracy when or for how long affected assets will be out of production. Revenue stream interruptions, which can comprise a significant portion of total costs, can be difficult to schedule or predict. Thus, technical debt retirement projects tend to be riskier than other kinds of projects. They have wider uncertainty bands. Ignoring the Uncertainty, or trying to transfer responsibility for it to the project team, is foolhardy.

A strategy for reducing the effects of this synergy

To intervene in the dynamic between the consequences of the reification error and the consequences of confirmation bias, we must find a way to limit how their consequences can interact. That will curtail the ability of one phenomenon to reinforce the other. This task is well suited for application of Donella Meadows’ concept of leverage points [Meadows 1999]. See “Leverage points for technical debt management.”

In that post, I summarized Meadows’ concepts of using leverage points to alter the behavior of complex systems. One can intervene at one or more of 12 categories of leverage points. These are elements in the system that govern the behavior of the people and institutions that comprise the system. In that post, I sketched the use of Leverage Point #9, Delays, to alter the levels of technical debt in an enterprise.

In what follows I sketch the use of interventions at Leverage Point #8, “The strength of negative feedback loops, relative to the impacts they are trying to correct against.”

Our strategy is this:

A feedback loop that now provides budgetary control in most organizations

One feedback loop at issue in this case, illustrated above, influences managers who might otherwise overrun their budgets. It does so by triggering some sort of organizational intervention when a manager overruns his or her budget. And the feedback loop leads to increases in the size and stature of the portfolios of managers who handle their budgets responsibly.  Presumably, that’s one reason why managers compel estimators to find approaches that cost less. The feedback loop to which managers are exposed causes them to establish another feedback loop involving the engineer/estimator, and later the engineering team. That second loop causes engineers to hold down their estimates, and later to limit actual expenditures.

A diagram of effects analysis

A feedback loop that now provides budgetary control in most organizations
A feedback loop that now provides budgetary control in most organizations.

We can use a diagram of effects [Weinberg 1992] to illustrate the feedback mechanism commonly used to control the performance of managers who are responsible for portfolios of project budgets. In the diagram (above), the oval blobs represent quantities indicated by their respective captions. Each of these quantities is assumed to be measurable, though their precise values and the way we measure them are unimportant for our rather qualitative argument.

What the arrows mean

Notice that arrows connect the blobs. The arrows represent the effect of changes in the value represented by one blob on the value represented by another. The blob at the base of the arrow is the effector quantity. The blob at the point of the arrow is the affected quantity. Thus, the arrow running from the blob labeled “Actual Spend” to the blob labeled “Overspend” expresses the idea that a positive (or negative) change in the amount of actual spending on projects causes a positive (or negative) change in Overspend. When a change in the effector quantity causes a like-signed change in the affected quantity, we say that their relationship is covariant.

Because increases in Budget Authority tend to decrease Overspend, all other things being equal, the relationship between Budget Authority and Overspend is contravariant. We represent a contravariant relationship between the effector quantity and the affected quantity as an arrow with a filled circle on it.

Finally, notice that the arrow from Overspend (effector) to Promotion Probability (affected) has a filled Delta on it. This represents the idea that as Overspend increases, it negatively affects the probability that the manager will be promoted at some point in the future. The Delta indicates a delayed effect; that the Delta is filled indicates a contravariant relationship. (An unfilled Delta would indicate a delayed covariant effect.)

Loops in the diagram of effects

This diagram, which contains a loop connecting Budget Authority, Overspend, and Promotion Probability, has the potential to “run away.” That is, as we go around the loop, we find self-re-enforcement, because the loop has an even number of contravariant relationships. It works as follows:

As Overspend increases, after a delay, the Probability of Promotion decreases. This causes reductions in Budget Authority because, presumably, the organization has reduced faith in the manager’s performance. Reductions in Budget Authority make Overspend more likely, and round and round we go.

Similarly:

As Overspend decreases, after a delay, the Probability of Promotion increases. This causes increases in Budget Authority because, presumably, the organization has increased faith in the manager’s performance. Increases in Budget Authority make Overspend less likely, and round and round we go.

Fortunately, other effects usually intervene when these self-re-enforcing phenomena get too large, but that’s beyond the scope of this argument. For now, all we need observe is that managers who manage their budgets effectively tend to rise in the organization; those who don’t, don’t.

The result is that managers limit spending to avoid overspending their budget authority. And that’s one reason why they push engineers to produce lower estimates for technical debt retirement projects.

How this feedback loop overlooks important drivers of technical debt formation

To break the connection between the managers’ reification error and the engineers’ confirmation bias, our intervention must cause the managers and the engineers to make calculations differently. We can accomplish this by requiring that they consider more than the mere cost of retiring the class of technical debt under consideration. They must estimate the consequences of not retiring that technical debt, and they must also estimate costs beyond the cost of retiring the debt. In what follows, I’ll use the shorthand TDBCR to mean the class of Technical Debt Being Considered for Retirement.

Specifically, estimates for technical debt retirement projects cover only the cost of performing the work required to retire the TDBCR. Management then decides whether, when, and to what extent to commit resources to execute the project. The primary considerations budgetary.

Since the debt retirement project can potentially provide benefits beyond the manager’s own portfolio, failing to undertake the project can have negative consequences. Mnagers who decline to undertake debt retirement projects are responsible for the consequences. But accountability for these decisions is rare. That’s the heart of the problem. So let’s look at some examples of relevant considerations.

Adjustments that would support these feedback loops to gain control of technical debt

In allocating resources for a technical debt retirement project, there are considerations beyond the cost of retiring the debt. A responsible decision is possible only if other kinds of estimates are also available. Here are some examples of the estimates we need:

  • The effects of retiring TDBCR on the cost of executing any other development or maintenance effortsy
  • The effects of retiring TDBCR on revenue and market share for all existing assets that directly produce revenue and which could be affected by retiring TDBCR
  • The revenue that would become available (and timing thereof) from any new products or services that become possible because of retiring TDBCR
  • The effects of retiring TDBCR on the cost of executing other technical debt retirement efforts

And these items might not be related to anything for which the decision maker is responsible. But the feedback loop we now use to influence the decision maker excludes considerations that are affected by the decision maker’s decisions. Until we install feedback loops that cause the decision maker to consider these indirect consequences, or until we make decisions at levels that include these other consequences, the effects of the decision maker’s decisions are uncontrolled, and might not lead to decisions optimal for the enterprise.

References

[Brenner 2011] Richard Brenner. “Indicators of Lock-In: I,” Point Lookout 11:12, March 23, 2011.

Available: here; Retrieved: October 23, 2018.

Cited in:

[Burge 2015] Janet E. Burge and Raymond McCall. “Diagnosing Wicked Problems,” Design Computing and Cognition 14, 2015, 313-326.

Available: here; Retrieved: October 25, 2018

Cited in:

[Churchman 1967] C. West Churchman. “Wicked problems,” Management Science 14:4, 1967, B-141–B-142

Available: here; Retrieved: October 16, 2018

Cited in:

[Cook 2016] John Cook, Naomi Oreskes, Peter T. Doran, William R.L. Anderegg, Bart Verheggen, Ed W. Maibach, J. Stuart Carlton, Stephan Lewandowsky, Andrew G. Skuce, Sarah A. Green, Dana Nuccitelli, Peter Jacobs, Mark Richardson, Bärbel Winkler, Rob Painting, and Ken Rice. “Consensus on consensus: a synthesis of consensus estimates on human-caused global warming,” Environmental Research Letters 11, 2016, 048002.

Available: here; Retrieved: October 23, 2018

Cited in:

[Gabriel 2018] Melissa Gabriel. “Hurricane Michael: Fate of costly stealth fighter jets at Tyndall Air Force Base still unknown,” USA Today: Pensacola News Journal, October 17, 2018.

Available: here; Retrieved: October 23, 2018

Cited in:

[Keizer 2018] Gregg Keizer. “Windows by the numbers: Windows 10 backtracks, Windows 7 remains resilient,” Computerworld, October 2, 2018.

Available: here; Retrieved: October 18, 2018

Cited in:

[Kreuter 2004] Marshall W. Kreuter, Christopher De Rosa, Elizabeth H. Howze, and Grant T. Baldwin. “Understanding wicked problems: a key to advancing environmental health promotion.” Health Education and Behavior 31:4, 2004, 441-454.

Available: here; Retrieved: October 26, 2018

Cited in:

[Levin 2012] Kelly Levin, Benjamin Cashore, Steven Bernstein, and Graeme Auld. “Overcoming the tragedy of super wicked problems: constraining our future selves to ameliorate global climate change,” Policy Science 45, 2012, 123–152.

Available: here; Retrieved: October 17, 2018

Cited in:

[McConnell 2006] Steve McConnell. Software Estimation: Demystifying the Black Art. Microsoft Press, 2006.

Order from Amazon

Cited in:

[Meadows 1999] Donella H. Meadows. “Leverage Points: Places to Intervene in a System,” Hartland VT: The Sustainability Institute, 1999.

Available: here; Retrieved: June 2, 2018.

Cited in:

[Phillips 2018a] Dave Phillips. “Tyndall Air Force Base a ‘Complete Loss’ Amid Questions About Stealth Fighters,” The New York Times, October 11, 2108.

Available: here; Retrieved: October 23, 2018

Cited in:

[Phillips 2018b] Dave Phillips. “Exposed by Michael: Climate Threat to Warplanes at Coastal Bases,” The New York Times, October 17, 2108.

Available: here; Retrieved: October 23, 2018

Cited in:

[Rittel 1973] Horst W. J. Rittel and Melvin M. Webber. “Dilemmas in a General Theory of Planning”, Policy Sciences 4, 1973, 155-169.

Available: here; Retrieved: October 16, 2018

Cited in:

[Shapiro 1998] Carl Shapiro and Hal R. Varian. Information rules: a strategic guide to the network economy. Harvard Business Press, 1998.

Cited in:

[Weinberg 1992] Gerald M. Weinberg. Quality Software Management Volume 1: Systems Thinking. New York: Dorset House, 1989.

This volume contains a description of the “diagram of effects” used to explain how obstacles can induce toxic conflict. Order from Amazon

Cited in:

[Zablah 2015] Raul Zablah and Christian Murphy. “Restructuring and Refinancing Technical Debt.” Proceedings of the IEEE 7th International Workshop on Managing Technical Debt (MTD). IEEE, 2015.

Available: here; Retrieved: February 13, 2016

Cited in:

Other posts in this thread

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