Outsourcing Technical Debt Retirement Projects

From time to time, people ask me about the wisdom of outsourcing technical debt retirement projects. Because the answer depends so strongly on the particulars of the situation, there’s no general answer. But there are general guidelines—factors to consider when making the decision. Let’s refine the question first, in the form of a case:

Our organization uses an array of software and hardware assets to execute our mission. We developed some of these systems so long ago that the original developers have departed. They left here for other companies, or they left in spinoffs, or they moved on to other parts of our company. Some of these moves were due to reorganizations, some to promotions, and some to personal career decisions.

Most of the people who are now maintaining these assets have learned by doing.  This has been necessary because we haven’t kept the documentation current enough to be a reliable reference. We know that the systems harbor significant levels of technical debt, and the documentation itself carries debt. So we want to retire all that debt, but it’s a big job. Should we hire contractors? Or a vendor who specializes in large scale technical debt retirement projects?

This is a typical situation, but many variables are unspecified. And typically, even more variables are unknown. Those unspecified or unknown variables make the decision tricky. To illustrate, I’ve listed below seven issues that would affect decisions about outsourcing technical debt retirement projects.

In-house staff probably has useful knowledge
Deciding about outsourcing technical debt retirement?
The dilemma: outsource technical debt retirement, or do the work in-house?

If the in-house staff has much undocumented information about the current configuration of the assets, they have an enormous advantage over contractors or an outside vendor trying to do the same work. And even though the in-house staff wasn’t involved in initial development, they probably have valuable knowledge of the asset if they’ve been engaged in maintenance or enhancement to any significant degree. And they probably know more about the assets than any outsider would. So if the ultimate decision is to outsource the work, try to devise an arrangement in which the most knowledgeable in-house staff are acting in a reference role.

Debt retirement effectiveness depends on knowledge of enterprise strategy

Knowledge of enterprise strategy is useful in technical debt retirement projects. For example, suppose we know that a future project will be rendering some or all of a given asset irrelevant. We can use that knowledge to focus the debt retirement effort.

However, in some cases, revealing strategy to outside vendors is risky, even with ironclad NDAs in place. So some asset owners avoid revealing strategy information. They accept that the outside vendor might perform otherwise-wasteful tasks. This approach can be a low-cost way to manage the risks that arise from revealing strategy. Others choose to perform the work in-house. Working in-house enables them to use their knowledge of strategic direction when allocating effort in debt retirement or when deciding what the transformed asset should look like.

Detailed knowledge of the debt retirement effort is itself valuable

Knowledge of the what and why of the actual debt retirement work can be helpful in resolving any difficulties that surface after completion. That knowledge is also helpful in future work on similar assets.

With outsourcing, after the work is done, any unreported information about what the vendor did and why they did it departs with them. If in-house staff perform the work, that information remains in-house. This can be very helpful if the asset is a critical asset, or if you expect further future enhancement work or debt retirement work on that asset or similar assets.

Debt retirement work almost inevitably generates new knowledge

When people work on debt retirement, they usually have specific objectives. Even so, as they work, they generally uncover issues they hadn’t anticipated. Both in-house staff and contractors experience these aha’s. The difference between them is what happens after the work is done.

If in-house staff does the work, they can use this newfound knowledge in other projects, including new development. Not necessarily so with the outside vendor. If the same vendor is employed again for another effort, they can apply that knowledge if doing so is in scope for the next contract. But if that vendor doesn’t return, or the scope of subsequent efforts doesn’t permit it, then they can’t apply that knowledge. Moreover, the vendor might not even report what they found, though most would because they hope it will lead to more work. If they do report it, the in-house contract monitor should be sophisticated enough to recognize how valuable that kind of information is. Sadly, many are not.

Asset service disruptions can be problematic

Another difficulty with outsourcing technical debt retirement projects relates to asset service disruptions. In some debt retirement efforts, some assets must be taken out of service for periods that are moderately disruptive or worse. In-house staff likely have relationships of long standing that make cooperation, negotiation, and consideration relatively easy.

If negotiation difficulties arise, the lowest level executive or manager who’s responsible for all parties can facilitate resolution. And over time, with practice, all parties learn to work out these issues more effectively. With outside vendors, this process can be more difficult, because of the absence of existing relationships, the termination of relationships when vendors exit the scene, and the lack of formal authority of some specific executive or manager.

If in-house staff can’t do the work, consider hiring

If the in-house staff is overloaded, or if they lack the skills necessary to take on the technical debt retirement effort, outsourcing can seem like the only workable approach. Not so fast though. If a stream of debt retirement projects is in your future, consider the advantages of building a debt retirement function with a long-term agenda. Examine again the factors cited above to determine the scale of the advantages of building such a team.

Outsourcing probably works well for refactoring

The one activity for which outsourcing can be a big win is refactoring. Refactoring doesn’t usually require much knowledge of company strategy. And it doesn’t require much “non-localizable” knowledge. That is, the requirement that the refactoring not cause changes in asset behavior enables the asset owner to write a very tight contract with the debt retirement team. They can then perform their work with confidence because they can test the asset’s behavior incrementally. Also, with refactoring, asset service disruptions are usually minimal.

One last suggestion. With outsourcing, the vendor might have significantly more experience with technical debt retirement efforts than does the client. This asymmetry gives the vendor an advantage at every stage. For technical debt retirement efforts, they know more about contracting, devising statements of work, defining acceptance criteria, and managing risk. Most important, they have experience dealing with the many speed bumps that can occur in these projects. To manage the risks of that advantage, consider retaining a consultant experienced in these situations. This person’s role is to monitor communications between enterprise and vendor to ensure fairness. The mere presence of such an individual can deter the vendor from some of the abuses that can be so tempting in these asymmetric situations when trouble arises.

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Retiring technical debt can be a wicked problem

Last updated on December 11th, 2018 at 07:08 am

The theory of wicked problems originated with Horst Rittel in the mid-1960s. He was trying to address “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 intended as a moral judgment. It suggests the mischievous streak in these problems, many of which have the property that proposed solutions often lead to conditions even more problematic than the situation they were intended to resolve. 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, infrastructure, architectures, policies, or strategies.

Introduction

Prototypes of President Trump’s “border wall.”
Prototypes of President Trump’s “border wall.” Building such a wall is undoubtedly an example of a wicked problem. Building prototypes in short segments of the wall to see what they would look like is a tame problem. But these are just prototypes of short segments of the wall. They aren’t prototypes of the project. They don’t demonstrate the process by which private property will be taken for the wall, or how construction access roads will be built, or how wildlife will be affected (and respond), or how the government of the adjacent nation (in this case, Mexico) will respond, or how the wall will be repaired when drug gangs destroy sections of it in isolated regions, or even if the wall would actually work as promised. Prototyping works well for tame problems. It helps us project how the finished project will perform, and how difficult it will be to complete the project. But for wicked problems, prototyping is of limited value and 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.

Horst Rittel was a design theorist at the University of California at Berkeley. His interest in wicked problems came about because of the need for designers to deal with the interactions between architecture and politics. In today’s technology-dependent enterprises, analogous problems arise when we try to retire technical debt, because multiple sets of quasi-independent stakeholders are affected by major technical debt retirement projects.

In the years since he first originated the wicked problem concept, people have extended it in ways that have led some to regard the concept as inflated and less than useful. But since extension and imitation rarely occur unless the extended concept has value, I take this phenomenon to mean that Rittel’s version of the concept is worthwhile. The focus of this post, then, is Rittel’s version of wicked problems, as applied 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. 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 affairs to a more desirable state that might still contain technical debt in some form, but it leaves us in a better position.

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, and 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.

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 is meant by definitive formulation. For wicked problems, on the other hand, one’s understanding of the problem depends on the solution one is 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, affecting 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 it isn’t practical to examine all possible candidate project plans, choosing a project plan by seeking an optimal set of effects isn’t practical. By the time you’re ready to execute the project plan you like best, the elapsed time required for such an analysis could render obsolete the data you collected first.

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

For any given tame problem, solutions have “stopping rules”—signatures that indicate clearly that they are indeed solutions. For example, in a chess problem to be solved in N moves, 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 a task breakdown, a sequence for performing the tasks (which might be only partially ordered), 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, and 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 are not 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, and the political power of the people making those demands. No single number measures that.

4. [No Test of Solutions] There is no immediate and no 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, and they’re well equipped to judge the success of the solution.

Not so with wicked problems. Any candidate solution to a wicked problem will generate waves of consequences. As these waves propagate, some of the problem’s stakeholders might find the solution unsatisfactory, and they’ll report this, possibly through politically powerful people or organizations, to the problem solving team. Because the consequences can be so diverse, the team can’t anticipate all of them, and 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 severe than any intended benefits. In other cases, the undesirable consequences might not be discovered until long after the solution has been deployed and accepted as 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 all of that be determined 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 for the solution-finding effort. 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 such that the wicked problem is effectively transformed into a new 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 may 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 leave political or financial traces like these, making future attempts riskier and more challenging.

6. [Solutions Are Not Describable] 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 may be incorporated into the plan

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

Wicked problems defy such strategies. Gathering the full set of possible solutions to a given wicked problem can in itself be a wicked problem. The set of possible solutions cannot be parameterized; no finite set of attributes fully covers the solution space. We can never be certain that the set of candidates we have is a complete set.

Candidate designs for technical debt retirement projects present this same quality. We’re confronted with a dizzying array of choices, including the order in which we retire different kinds of technical debts, the order in which we address the debts borne by different assets, the possibilities of “refinancing” portions of the debt to intermediate forms of technical debt, what kinds of refactoring to perform and when, and much more. Because options like these are neither denumerable nor parameterizable, it’s difficult to know whether a given set of candidate project designs includes all possible project designs.

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

Among tame problems, we can define classes or categories that have the property that all problems in a given class can be solved using the same method. For example, all the elements of the class of second order linear differential equations can all be solved using similar methods.

There are no classes of wicked problems that have such a property. There are no classes of wicked problems for which we can define a solution strategy that is effective for every member of the class. 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, or even 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] Every wicked problem can be considered to be 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 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. They form a hypothesis H as to the cause of the problem, conjecturing a solution. Then assuming that H is correct, and given a set of conditions C, they deduce a set of consequences E that must follow if H is correct. If any elements of E don’t occur, then H is falsified. The process repeats until an H’ is found that cannot be falsified. H’ is then used to develop a solution. This is, essentially, the scientific method.

With wicked problems, the method fails in numerous ways. Foremost among these failure modes is the absence of the ability 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 one can establish C0, the experiments one performs to determine whether E is observed tend to leave the kinds of traces discussed in Proposition 5 [No Trial-and-error]. Finally, the nature of the elements of E is usually such that determining their presence or absence is largely 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. 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 are free to 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, on the problem solvers themselves. Problem solvers are held 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 costs associated with these consequences are charged to the project, 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

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

Available: here; Retrieved: October 16, 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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Synergy between the reification error and confirmation bias

Last updated on December 11th, 2018 at 10:34 am

In deciding whether or not to undertake technical debt retirement projects, organizations are at risk of 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 in those cases in which resources are committed, there is a tendency to underestimate costs, which can lead to an elevated incidence of failures of 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 such as technical debt as if it were a real, concrete, physical thing, which, of course, it is not. (See “Metrics for technical debt management: the basics”)

And 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.

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

In the physical world, when we want cherries, we go to the produce section of the market and check the price per pound or kilo. Then we decide how many pounds or kilos we want. If the price is high, we might decide that fewer cherries will suffice. If the price is low, we might purchase more cherries. We have in mind a total cost target, and we adjust the weight of the cherries to meet the target, given the price. In the physical world, we can often adjust what we purchase to match our ability to pay for it.

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, and asks an engineer to work up 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—and asks the engineer to find a way to do it for less, with less Uncertainty, maybe by being clever or doing less.

Management—the “customer” in this scenario—makes this request, in part, based on the belief that it’s possible to adjust the work to meet a (possibly unstated) target, in analogy to buying cherries in the produce department. 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

Now back to the interaction between Management and 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 comes back with 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, hoping for a final cost that isn’t too high.

In adjusting their estimates, engineers have a conflict of interest that can compromise their objectivity through the action of confirmation bias. In the case of technical debt retirement efforts, engineers are usually highly motivated to gain Management approval of the project, because the technical debt in question depresses engineering productivity and induces frustration. 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, they have an incentive to convince themselves that the budget and schedule adjustments they make are reasonable. Because of the confirmation bias, they tend to seek justifications for the belief that lowering costs and tightening schedules is reasonable, while 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

So, because of the reification error, Management tends to believe that the work needed to retire technical debt of a particular kind is more adjustable than it actually is. And because of confirmation bias, engineers tend to believe that they can do the work for a cost and within a schedule that Management is willing to permit. 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 interprets estimates as commitments. Engineers do not equate estimates with commitments. Management usually forgets or ignores the upside Uncertainty. So typically, when Management finally 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. Few engineering teams are actually asked to make an explicit commitment to perform the work for a cost Total with zero upside Uncertainty. 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 affected assets must be temporarily withdrawn from production—and for how long—to support the technical debt retirement effort. Revenue stream interruptions, which can be significant portions 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], which I discussed in an earlier post, “Leverage points for technical debt management.”

In that post, I summarized Meadows’ idea that to alter the behavior of a complex system, 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 this post, I’ll sketch the use of interventions at Leverage Point #8, which Meadows calls, “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, provides budgetary control. It influences managers who might otherwise overrun their budgets by triggering some sort of organizational intervention when they do overrun their budgets. And it leads to increases in the portfolios of managers who handle their budgets responsibly.  Presumably, that’s 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, to hold down their estimates, and later their actual expenditures.

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, 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.

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.)

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 seek to limit spending so as 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, the estimates that are now typically generated for such projects cover only the cost of performing the work required to retire the TDBCR. It’s then left to Management to decide whether, when, and to what extent to commit resources to execute the project. The primary consideration is the effect on the decision-maker’s budget, and the consequences for achieving the goals for which the decision-maker is responsible.

Since the retirement project can potentially provide benefits beyond the manager’s own portfolio, failing to undertake the project can have negative consequences for which the manager ought to be held accountable. That’s the heart of the problem. So let’s look at some examples of considerations that must be taken into account.

Adjustments that would be needed in these feedback loops to gain control of technical debt

In making a resource allocation decision for a technical debt retirement project, there are considerations beyond the cost of retiring the debt. A responsible decision regarding undertaking technical debt retirement projects is possible only if other kinds of estimates are also generated and available. Here are some examples:

  • The effects of retiring TDBCR on the cost of executing any other development or maintenance efforts contemplated or already underway
  • 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 be generated (and timing thereof) by any new products or services that would be enabled by 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. That’s the core of the problem we now face: 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 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

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

Available: here; Retrieved: October 16, 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:

[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:

[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:

Other posts in this thread

Managing technical debt

Last updated on May 21st, 2019 at 06:11 am

Managing technical debt is something few organizations now do, and fewer do well. Several issues make managing technical debt difficult and they’re discussed elsewhere in this blog. This thread explores tactics for dealing with those issues from a variety of initial conditions. For example, tactics that work well for an organization that already has control of its technical debt, and which wants to keep it under control, might not work at all for an organization that’s just beginning to address a vast portfolio of runaway technical debt. The needs of these two organizations differ. The approaches they must take might then also differ.

A jumble of jigsaw puzzle pieces. Managing technical debt can be like solving a puzzle.
A jumble of jigsaw puzzle pieces. Where do we begin? With these puzzles, we usually begin with two assumptions: (a) we have all the pieces, and (b) they fit together to make coherent whole. These assumptions might not be valid for the puzzle of technical debt in any given organization.

The first three posts in this thread illustrate the differences among organization in different stages of developing technical debt management practices. In “Leverage points for technical debt management,” I begin to address the needs of strategists working in an organization just beginning to manage its technical debt, and asking the question, “Where do we begin?” In “Undercounting nonexistent debt items,” I offer an observation about a risk that accompanies most attempts to assess the volume of outstanding technical debt. Such assessments are frequently undertaken in organizations at early stages of the technical debt management effort. In “Crowdsourcing debt identification,” I discuss a method for maintaining the contents of a database of technical debt items. Data maintenance is something that might be undertaken in the context of a more advance technical debt management program.

Whatever approach is adopted, it must address factors that include technology, business objectives, politics, culture, psychology, and organizational behavior. So what you’ll find in this thread are insights, observations, and recommendations that address one or more of the issues related to these fields. “Demodularization can help control technical debt” considers mostly technical strategies. “Undercounting nonexistent debt items” is an exploration of a psychological phenomenon.  “Leverage points for technical debt management” considers the organization as a system and discusses tactics for altering it. And “Legacy debt incurred intentionally” explores how existing technical debt can grow as long as it remains outstanding.

Accounting issues also play a role. “Metrics for technical debt management: the basics” is a basic discussion of measurement issues. “Accounting for technical debt” looks into the matter of accounting for technical debt financially. And “Three cognitive biases” is a study of how technical debt is affected by the way we think about it.

Posts in this thread:

References

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

Available: here; Retrieved: October 16, 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:

[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:

[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:

Tension between policymakers and technologists

Last updated on July 24th, 2018 at 08:17 pm

Tension between policymakers and technologists, which can manifest as misalignment of their respective priorities, is a significant contributor to uncontrolled growth of technical debt. In this thread I explore sources of this tension and introduce concepts that can assist policymakers and technologists in their efforts to control the growth of technical debt.

Effective, sustainable control of technical debt is the objective of technical debt management policy. In an enterprise that has achieved this objective, technical debt serves as a strategic tool that assists in attaining and maintaining market leadership. In such an organization, technical debt does exist, and some legacy technical debt might remain in place, but technical debt growth is managed strategically, if growth occurs at all. Any technical debt that carries significant MICs, and which compromises productivity and enterprise agility, is addressed and retired with appropriate priority. In short, technical debt is addressed not solely as a technological issue, but as a component of business strategy.

Raindrops on a grapevine
Raindrops on a grapevine. We often think of tension as a negative, destructive force. But tension—in the case of raindrops, surface tension—is what holds a raindrop together. Tension gives the raindrop structure and integrity. The tension between technologists and policymakers can also be constructive. It can ensure that the enterprise manages its technical debt in ways that balance the political imperatives of both technology and strategic health.

This stance is at odds with the historical position most enterprises have adopted vis-à-vis technical debt. Historically, technical debt has been seen as a technical problem, if it has been recognized at all. Most enterprises have left the management of technical debt to the technologists. Frequently, then, the policymaker who enters the discussion about technical debt might be seen by technologists as an interloper, arriving late to the discussion, or as a less-than-knowledgeable invader attempting to seize control of a piece of the technologists’ domain. Tensions can arise between policymakers and technologists. Such tensions complicate the problem of managing technical debt.

One possible source of this tension is revealed in a study of the literature of technical debt, which is evolving so rapidly that it has itself become a focus for research. Li et al. [Li 2015] have produced a review of the software engineering technical debt literature, from which we can extract insights useful to policymakers. Although they studied only the literature relating to technical debt in software engineering, their conclusions are, at least in part, applicable to any field in which the components of the finished product are executed within software tools before being committed to operational form. This covers a wide array of knowledge-intensive endeavors, including mechanical system design, electronic design, framing of legislation, process design, architecture, and even book authorship.

In this thread, I explore the sources of the tension between the modern reality of technical debt as an enterprise issue, and the historical situation of technical debt as a technological issue. This can serve as a guide for policymakers in reframing technical debt from a technological issue dependent for resolution on enterprise resources, to an enterprise issue dependent for resolution on technological resources.

References

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

Available: here; Retrieved: October 16, 2018

Cited in:

[Li 2015] Z. Li, P. Avgeriou, and P. Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.

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:

[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:

[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:

Other posts in this thread

Cultural debt can be the primary driver of technical debt

Last updated on June 2nd, 2018 at 10:35 pm

Cultural debt can be expensive because, like technical debt, it can incur ongoing metaphorical interest charges. Schein defines organizational culture as “…a pattern of shared basic assumptions learned by a group as it solved its problems of external adaptation and internal integration…” [Schein 2016]. Following the concept of technical debt, we can regard as cultural debt the subset of shared basic assumptions comprising enterprise culture that are no longer fitting for enterprise realities. We can also include as cultural debt any assumptions that ought to be shared, but which are missing or are only partially shared. And we can include shared assumptions that conflict with each other and need to be resolved.

An example of cultural debt: the term “IT”

A tape measure calibrated in both feet/inches and meters/centimeters
A tape measure calibrated in both feet/inches and meters/centimeters. The need to possess tools that serve both measurement systems can be viewed as the metaphorical interest charges on a technical debt resulting from the failure to retire the older “English” system. But from another perspective, the debt involved is actually cultural. Retiring the older system would truly involve a cultural shift.

For most modern enterprises, one element of cultural debt is the very term IT itself — information technology. Coined in 1958 by Leavitt and Whisler [Leavitt 1958], the term was apt up to as recently as 20 years ago, when the role of IT was primarily management, storage, retrieval, manipulation, and presentation of data — information — by technological means. Although those functions remain relevant, the responsibilities of IT have expanded dramatically since 1958. In many organizations, IT is now responsible for designing, implementing, and maintaining the communication infrastructure, including Internet access, personal computers, networking, Web presence, telephones, video conferencing equipment, and television.

In modern organizations in which communication plays a critical and strategic role, an essential element for success is a clear understanding of what IT does and what it contributes. To regard IT as the “information technology” function of the enterprise is, therefore, to risk overlooking and undervaluing these more recently acquired responsibilities. And since the IT function is no longer solely responsible for enterprise information, using the name “IT” or the term information technology risks overvaluing the role of the IT organization relative to information management, while undervaluing its role relative to communications.

In Schein’s culture framework, the term IT reflects a shared assumption about the focus and span of the IT function. That assumption is that IT is responsible for information—an assumption that is no longer well aligned to the reality of the role of IT. We can regard this misalignment as a cultural debt.

The consequences of this particular kind of cultural debt can be severe. For instance, IT is typically responsible for selecting and configuring software for personal computers (PCs) — both desktop and laptop. This responsibility can arise as a consequence of two shared assumptions. First, that computers process information, and second, that IT is responsible for technology-based information processing. The result is that decisions about what many regard as a “personal” computer are not in the control of the person who uses the computer. This conflict in shared assumptions can lead to conflict between PC users and IT, when the IT decision is at variance with their personal preferences.

Worse, a centralized decision process for determining PC configurations is likely to produce outcomes less suitable than would a process more focused at the individual level, which only adds to the frustrations of PC users, and exacerbates the conflict between them and IT. To mitigate the risk that some PC users might try to circumvent IT policy, IT must deploy technology to ensure adherence to their policies. We can regard all of that activity, on the part of both IT and the PC users, as metaphorical interest charges on cultural debt.

An example of retiring cultural debt

In 1987, Edward Yourdon founded a magazine then known as American Programmer. In 1990, Cutter Information Corporation purchased the rights to American Programmer and created Cutter IT Journal, which name includes the term IT. At the time IT was more suitable than the term programmer. As noted above, the term IT, while once useful and apt, is now outmoded at best and often misleading. Just as the functional name IT in organizations constitutes cultural debt, so it does in the name of a journal.

So in the autumn of 2016, Cutter IT Journal retired the cultural debt in its name, and became Cutter Business Technology Journal. Journals rarely change their names. When they do, the impact of the journal is temporarily depressed because of the split of citations between the former title and the new title for two years or so [Tempest 2005]. But as research fields change, their journals must keep pace. Evidently Cutter felt a significant need to retire its cultural debt — significant enough to justify a temporary effect on impact.

What about cultural debt retirement in companies?

Difficulties associated with retiring cultural debt in companies depend strongly on both the nature of the culture and the nature of the debt. To provide insight into the issues that can arise, let’s continue with our exploration of the term IT and its cultural implications.

In many organizations, IT reports to an enterprise Chief Information Officer (CIO). Associated with this official’s title are some of the same cultural debts we find associated with the name of the IT organization. First, within their organizations, CIOs aren’t the only officers with information management responsibility. Second, many CIOs have responsibilities that extend beyond information management, to include, for example, the communication infrastructure. And unlike other peer titles such as CEO, CFO, CMO, and COO, the CIO title evokes separation from business-oriented decisions. That separation contributes to a cultural wall between “IT” and “the business.”

When cultures view IT as an information-centric service organization, a remnant perhaps of the middle or late 20th century, they tend to regard IT as a source of expense to be minimized, rather than as a strategic partner [Ross 2000]. Trends toward strategic acceptance of IT are nevertheless favorable, with room for improvement, according to recent surveys of CIOs [CIO 2018], probably because of reality.

The reality is that business technology must contribute to formulation and implementation of enterprise strategy. To the extent that CIOs and their organizations are viewed as separate from “the business,” their ability to help shape enterprise strategy is limited. This situation subjects CIOs to cultural assumptions about their responsibilities that in some instances conflict with each other, or with enterprise reality. That’s a significant source of the metaphorical interest charges on the cultural debt.

One possible way to retire this debt might entail retitling Chief Information Officer to Chief Business Technology Officer (CBTO). That’s precisely what happened at Forrester Research in 2011 [Plant 2014].

Unfortunately, the name CBTO conflicts with the three-word pattern of enterprise officer titles (C*O), which might create an urge to name the office Chief Technology Officer (CTO). But that role usually has responsibility for the functions that create technological products or services. Thus, for many organizations, to create a CBTO where there is already a CTO might create further sources of conflict. Using the CTO designation for the CBTO is probably impractical.

But we must find some way to retire this particular cultural debt, because it is such an effective generator of technical debt. CBTO seems to be the best available path.

References

[CIO 2018] CIO. “2018 State of the Cio: CIOs Race Towards Digital Business,” CIO, winter 2018.

Available: here; Retrieved March 30, 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:

[Leavitt 1958] Harold J. Leavitt and Thomas L. Whisler. “Management in the 1980s,” Harvard Business Review, November-December, 36, 41-48, 1958.

Cited in:

[Li 2015] Z. Li, P. Avgeriou, and P. Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.

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:

[Plant 2014] Robert Plant. “IT Has Finally Cracked the C-Suite,” Harvard Business Review, July 16, 2014.

Available: here; Retrieved: April 8, 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:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

Order from Amazon

Cited in:

[Tempest 2005] “The effect of journal title changes on impact factors,” Learned Publishing 18, 57–62, 2005.

Available: here; Retrieved: April 5, 2018

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:

Other posts in this thread

Contract restrictions can lead to technical debt

Last updated on March 22nd, 2018 at 11:18 pm

When the owner of an asset, especially a software asset, contracts to provide a capability to a customer incorporating a use of that asset, the work involved might require modification or enhancement of that asset. When the contract permits such work, without transferring ownership of the asset itself, performing it is relatively straightforward, provided the work can be done in a manner compatible with any pre-existing or anticipated future other uses of the asset. But some contract restrictions can cause the owner of the asset to incur technical debt.

A power adaptor/converter for international travelers with U.S. standard equipment.
A power adaptor/converter for international travelers with U.S. standard equipment. This device provides conversion for both hardware connection and voltage supplied.
The wide variation in electric power standards worldwide can be viewed as a technical debt. Someday, in the probably distant future, a world standard will emerge and that debt will be retired. Until then, adaptors like these are travel necessities.

But some contracts restrict such work. For example, for a government customer, ownership of the work performed might be required to transfer to the government customer. Potentially, all of the work might be classified as a national secret. In either of these cases, to retain control of the asset, the owner/contractor arranges to perform all of the work outside the periphery of the asset. To accomplish this, the owner/contractor might interface to the asset through an adaptor that can be transferred to the government customer, or which can be classified as secret as the case may be, thereby insulating the original asset from these ownership restrictions.

The result is tolerable after one such contract is completed. But over time, as the number of adaptors increases, they become a form of technical debt. Each must be maintained against any changes in the original asset. Moreover, making changes to the original asset can become a project of such scale that the temptation to create a static “clone” of the asset for each customer is irresistible. When that happens, any technical debt already present in the asset is also cloned. And any work performed to correct defects in the asset must be performed on each affected clone.

The problem is more general than suggested above. It also appears in the case of software offered for multiple platforms, or multiple versions of a single platform.

But it gets worse. Suppose the maintainers decide to update the asset to make it more extensible, or to make it more maintainable. That update, including all testing and documentation, must then be performed on each clone. If the asset owner elects not to update all clones, then the clones will begin to diverge from each other. Engineers performing tasks on one of the clones must then have knowledge of how it differs from other clones. If a new defect is discovered, it might or might not be present in every clone. Implementing a new extension or other modification might not be possible in all clones, or it might have to be implemented differently in some clones. Life can get very complicated.

Organizations entering into contracts of this kind would be wise either to include language limiting their obligations to maintain the original asset against any changes, internal or external, in its ability to perform its functions. Or they might include an explicit statement of the parties’ intentions relative to financial support for any continuing obligations to maintain that asset.

Organizations offering products for multiple platforms would be wise to consider as strategic the management of technical debt that arises from platform multiplicity. Sound management of this form of technical debt can extend their ability to support multiple platforms, which can dramatically increase returns on investment in the core asset.

References

[CIO 2018] CIO. “2018 State of the Cio: CIOs Race Towards Digital Business,” CIO, winter 2018.

Available: here; Retrieved March 30, 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:

[Leavitt 1958] Harold J. Leavitt and Thomas L. Whisler. “Management in the 1980s,” Harvard Business Review, November-December, 36, 41-48, 1958.

Cited in:

[Li 2015] Z. Li, P. Avgeriou, and P. Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.

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:

[Plant 2014] Robert Plant. “IT Has Finally Cracked the C-Suite,” Harvard Business Review, July 16, 2014.

Available: here; Retrieved: April 8, 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:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

Order from Amazon

Cited in:

[Tempest 2005] “The effect of journal title changes on impact factors,” Learned Publishing 18, 57–62, 2005.

Available: here; Retrieved: April 5, 2018

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:

Other posts in this thread

How outsourcing leads to increasing technical debt

Most of the non-technical precursors of technical debt that afflict in-house work also afflict outsourced work. For example, the planning fallacy affects internal planners, but it also afflicts the bidders for contracts offered by the enterprise in the context of outsourcing. As described in “Unrealistic optimism: the planning fallacy and the n-person prisoner’s dilemma,” Boehm, et al., [Boehm 2016] call this the “Conspiracy of Optimism.” But outsourcing engineering work can introduce pathways for incurring technical debt that are specific to outsourcing.

Green fields
Green fields. Greenfield outsourcing, also known as startup outsourcing, is the outsourcing of activity that has never been performed within the enterprise. It’s especially tricky with respect to technical debt formation, because much of the expertise necessary to perform the work being outsourced is probably not resident within the enterprise. That void in enterprise expertise makes for difficulties in managing technical debt in the outsourced artifacts.

The risks of incurring technical debt associated with outsourcing are inherently elevated, even setting aside those factors that also afflict in-house activity. When most enterprises contract for development of systems or software, the criteria for acceptance rarely include specifications for maintainability or extensibility. This happens, in part, because such qualitative specifications are so difficult to define quantitatively. That’s why the condition of deliverables relative to maintainability and extensibility is so variable. Outsourced deliverables can best be described as bearing an unknown level of technical debt.

The root cause of the problem is likely a lack of a universally accepted metrics for quantifying technical debt [Li 2015]. That’s why it’s difficult to specify in the vendor contract an acceptability threshold for technical debt. And since the consequences of the presence of technical debt in deliverables potentially do not become clear during the lifetime of the contract under which the debt was incurred, years may pass before the issue becomes evident, which complicates the task of understanding the root cause of the problem.

In what follows, I use the term vendor to denote the organization to which work has been outsourced, and the term enterprise to denote the organization that has outsourced a portion of its engineering work. The retained organization is the portion of the enterprise directly relevant to the outsourced work, but which was not itself outsourced. Among the mechanisms that lead to incurring technical debt in the outsourcing context are the six mechanisms sketched below. Gauging the size of these effects by auditing deliverables or by auditing the internal processes of the vendor could be helpful in managing levels of technical debt arising from outsourcing.

This list isn’t intended to be exhaustive. Quite possibly other phenomena also contribute to technical debt formation in the context of outsourcing.

Progressive erosion of retained organization capabilities

Over time, the enterprise can expect erosion of the engineering expertise needed to manage, evaluate, understand, or, if need be, to re-insource (or backsource) the work that has been outsourced [Willcocks 2004][Beardsell 2010]. Typically, staff who formerly performed the outsourced work do move on to other work, voluntarily or not, either within the enterprise or elsewhere. Indeed, cost savings from terminations and employee buyouts often accompany — and economically justify — outsourcing decisions. But even if the enterprise continues to employ the people who formerly performed the work that is now outsourced, those employees, filling new roles, can become less familiar with the current work and therefore less able to perform it. And since they are now engaged in other assignments, their availability is limited. In the public sector, the organizations that perform the outsourced work exacerbate this phenomenon by recruiting from the agencies they serve [Kusnet 2007]. In manufacturing, Kinkel et al. suggest that, paraphrasing, outsourcing disturbs the formation of internal competence [Kinkel 2016].

In short, outsourcing engineering efforts can erode the ability of the enterprise to perform internally the work that is outsourced, or to monitor or evaluate it when performed by the vendor. Consequently, the enterprise is less able to monitor, evaluate, or retire any technical debt that accumulates in the outsourced work products. A policy that would address this risk is one that would (a) require retained organizational capability sufficient to assess the effect on technical debt of any outsourced engineering work; (b) require attention to technical debt issues in any financial models used in making the initial outsourcing decision; (c) require financial models to include the effects of technical debt and controlling technical debt when deciding whether to extend outsourcing contracts with vendors.

Stovepiping among vendors

Most multi-vendor efforts use a separation-of-concerns approach [Laplante 2007] to dividing the work. That is, each vendor is empowered to use any approach it can, consistent with its own contract and statement of work. In some cases, two or more vendors might have overlapping needs that cause them each to produce similar capabilities as elements of their respective deliverables. Sharing of their results is of course possible, but unless both of their contracts anticipate the need for sharing, sharing is unlikely. Failure to share those results that could have been shared can lead to incurring unrecognized technical debt.

Stovepiping within vendors

With regard to the efforts of a single outsource vendor, it’s possible that different teams or individuals working for that vendor might unwittingly create elements with overlapping capabilities. That duplication could lead to technical debt, or it could constitute technical debt in itself. For example, two teams working for the same vendor might have similar testing needs, and might develop testing tools independently. As a second example, in a version of stovepiping combined with temporal displacement, suppose that one team is unaware that a previous effort for the same customer had already developed a capability that it now needs. That team then might re-create that already-existing capability.

Stovepiping within vendors is less likely when the vendor operates under a single vendor technical lead, and the enterprise interacts with that single lead through a single in-house technical lead. When either side of the relationship is managed through multiple contacts, stovepiping is more likely, and new technical debt is more likely to form.

Loss of continuity in the outsourced engineering staff

Unless specified in the agreement between the vendor and the enterprise, staff turnover or reassignment within the vendor organization, between one version of the product or service and the next, can lead to technical debt in just the same way that turnover in-house can lead to technical debt. With outsourcing, however, the vendor has little internalized motivation to control this phenomenon, and the enterprise likely has less control—and less awareness—of staff assignments within the vendor organization than it does within the enterprise. Thus, loss of continuity in the outsourced engineering staff is both more likely and more likely to lead to technical debt.

Reduced coordination of engineering approaches and business objectives

Lack of coordination between engineering approaches and business planning can cause engineers to create and deploy artifacts that must be revisited later, when they learn of business plans that were unknown to the engineers at the time they produced those artifacts. See “Failure to communicate long-term business strategy.” This scenario is more likely, and possibly irresolvable, when the enterprise withholds its long-term plans from the outsourcing vendor to protect its strategy.

Hiring and retention problems

In some instances, commonly called startup outsourcing or greenfield outsourcing, the work being outsourced has never been performed within the enterprise [Delen 2007]. In these cases, typically, the enterprise must then reassign existing employees or hire new employees to interface with the outsource vendor. These roles are analogous to remote supervisors, except that the teams they supervise are not employees of the enterprise. Hiring and retaining people for these roles can be difficult, because of startup challenges both within the enterprise and within the vendor organization. Recruitment and especially retention problems in these roles can decrease the likelihood of controlling technical debt, and increase the likelihood of incurring technical debt.

References

[Beardsell 2010] Julie Beardsell. “IT Backsourcing: is it the solution to innovation?”, SMC Working Paper Series, Issue: 02/2010, Swiss Management Center University, 2010.

Available: here; Retrieved: February 15, 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:

[CIO 2018] CIO. “2018 State of the Cio: CIOs Race Towards Digital Business,” CIO, winter 2018.

Available: here; Retrieved March 30, 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:

[Delen 2007] Guus Delen. “Decision and Control Factors for IT-sourcing,” in Handbook of Network and System Administration, Jan Bergstra and Mark Burgess, eds., Boston: Elsevier, 929-946, 2007.

Order from Amazon

Cited in:

[Kinkel 2016] Steffen Kinkel, Angela Jäger, Djerdj Horvath, and Bernhard Rieder. “The effects of in-house manufacturing and outsourcing on companies’ profits and productivity,” 23rd International Annual EurOMA Conference, At Trondheim, Volume: 23, June 2016.

Cited in:

[Kusnet 2007] David Kusnet. “Highway Robbery II,” report of the National Association of State Highway and Transportation Unions (NASHTU).

Cited in:

[Laplante 2007] Phillip A. Laplante. What Every Engineer Should Know About Software Engineering. New York: CRC Press, 2007.

Order from Amazon

Cited in:

[Leavitt 1958] Harold J. Leavitt and Thomas L. Whisler. “Management in the 1980s,” Harvard Business Review, November-December, 36, 41-48, 1958.

Cited in:

[Li 2015] Z. Li, P. Avgeriou, and P. Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.

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:

[Plant 2014] Robert Plant. “IT Has Finally Cracked the C-Suite,” Harvard Business Review, July 16, 2014.

Available: here; Retrieved: April 8, 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:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

Order from Amazon

Cited in:

[Tempest 2005] “The effect of journal title changes on impact factors,” Learned Publishing 18, 57–62, 2005.

Available: here; Retrieved: April 5, 2018

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:

[Willcocks 2004] L. Willcocks, J. Hindle, D. Feeny, and M. Lacity. “IT and Business Process Outsourcing: The Knowledge Potential,” Information Systems Management 21:3, 7-15, 2004.

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

[Beardsell 2010] Julie Beardsell. “IT Backsourcing: is it the solution to innovation?”, SMC Working Paper Series, Issue: 02/2010, Swiss Management Center University, 2010.

Available: here; Retrieved: February 15, 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:

[CIO 2018] CIO. “2018 State of the Cio: CIOs Race Towards Digital Business,” CIO, winter 2018.

Available: here; Retrieved March 30, 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:

[Delen 2007] Guus Delen. “Decision and Control Factors for IT-sourcing,” in Handbook of Network and System Administration, Jan Bergstra and Mark Burgess, eds., Boston: Elsevier, 929-946, 2007.

Order from Amazon

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

[Kinkel 2016] Steffen Kinkel, Angela Jäger, Djerdj Horvath, and Bernhard Rieder. “The effects of in-house manufacturing and outsourcing on companies’ profits and productivity,” 23rd International Annual EurOMA Conference, At Trondheim, Volume: 23, June 2016.

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:

[Kusnet 2007] David Kusnet. “Highway Robbery II,” report of the National Association of State Highway and Transportation Unions (NASHTU).

Cited in:

[Laplante 2007] Phillip A. Laplante. What Every Engineer Should Know About Software Engineering. New York: CRC Press, 2007.

Order from Amazon

Cited in:

[Leavitt 1958] Harold J. Leavitt and Thomas L. Whisler. “Management in the 1980s,” Harvard Business Review, November-December, 36, 41-48, 1958.

Cited in:

[Li 2015] Z. Li, P. Avgeriou, and P. Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.

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

Order from Amazon

Cited in:

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

Available: here; Retrieved November 10, 2017.

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:

[Plant 2014] Robert Plant. “IT Has Finally Cracked the C-Suite,” Harvard Business Review, July 16, 2014.

Available: here; Retrieved: April 8, 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:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

Order from Amazon

Cited in:

[Tempest 2005] “The effect of journal title changes on impact factors,” Learned Publishing 18, 57–62, 2005.

Available: here; Retrieved: April 5, 2018

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:

[Willcocks 2004] L. Willcocks, J. Hindle, D. Feeny, and M. Lacity. “IT and Business Process Outsourcing: The Knowledge Potential,” Information Systems Management 21:3, 7-15, 2004.

Cited in:

Other posts in this thread

Failure to communicate long-term business strategy

Last updated on August 25th, 2018 at 09:47 am

Failure to communicate long-term business strategy can lead to increased technical debt, because engineering decisions that aren’t aligned with business strategy can result in what later becomes technical debt. As business strategy veers away from the assumptions underlying those misaligned engineering decisions, engineers must alter implementations to track the strategy. Technical debt can form during those alteration efforts. Moreover, the expenditure of resources to support those alteration efforts might have been unnecessary if engineers had been better informed about long-term business strategy. In some cases, those resources could have been allocated to other pursuits, including technical debt retirement. To ensure alignment of engineering decisions with long-term business strategy, engineering decision-makers must be aware of long-term and intermediate-term enterprise strategy. When they’re well informed, they can anticipate the engineering needs of the enterprise. And they’re more likely to make decisions that are compatible with strategy.

A plug-in electric vehicle being recharged
Recharging a  plug-in electric vehicle. The dominance of petroleum-powered vehicles is nearing its end. Further investment in the petroleum-based fuels infrastructure is now  inconsistent with what the global economy has chosen as its strategic intent. Electric vehicles are still out of the reach of most consumers, but they would be wise to favor long range vehicles. As electric vehicles become ascendant, petroleum filling stations will become more widely spaced, because they add to the metaphorical interest charges on the technical debt of yet-to-be-retired petroleum powered vehicles. During the transition to electric power dominance, a long-range petroleum-powered vehicle offers clear advantages over its shorter-range cousins.

Moreover, the effect is bi-directional. Strategists can benefit from understanding the effect their strategies have on technological activity. For example, consider the process of choosing among strategic options. A favorable outcome is more likely if strategists know the effects of each option on the technical debt portfolio.

To gain effective control of technical debt, senior management must regard the technical elements of the enterprise as strategic partners [Woodard 2013] [Ross 2000] [Brenner 2016a]. Policymakers can make important contributions to enhancing communication between strategists and technologists.

For example, when engineers know the general direction of the enterprise, they can focus efforts on assets that are compatible with future needs. Inversely, when they’re unaware of what the business strategy might soon require, they’re more likely to make decisions that they must later rescind.

What about legacy technical debt retirement?

Analogous considerations apply to legacy technical debt  retirement efforts. Major technical debt retirement efforts are often subject to review for alignment with enterprise strategy. But we tend not to review incidental retirement efforts that occur in the context of routine maintenance or development. Consequently, engineers might allocate effort to incidental  debt retirement unnecessarily if the asset is due for overhaul or replacement. Communicating long-term strategy effectively is likely the most reliable way to prevent such misspent effort.

Some managers elect to communicate business strategy to technologists only when they “need to know.” Often, technologists needed to know long before that.

References

[Beardsell 2010] Julie Beardsell. “IT Backsourcing: is it the solution to innovation?”, SMC Working Paper Series, Issue: 02/2010, Swiss Management Center University, 2010.

Available: here; Retrieved: February 15, 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:

[Brenner 2016a] Richard Brenner. “The Psychology and Politics of Technical Debt: How We Incur Technical Debt and Why Retiring It Is So Difficult,” Cutter Business Technology Journal, 29:3, 2016, 21-27.

Cited in:

[CIO 2018] CIO. “2018 State of the Cio: CIOs Race Towards Digital Business,” CIO, winter 2018.

Available: here; Retrieved March 30, 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:

[Delen 2007] Guus Delen. “Decision and Control Factors for IT-sourcing,” in Handbook of Network and System Administration, Jan Bergstra and Mark Burgess, eds., Boston: Elsevier, 929-946, 2007.

Order from Amazon

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

[Kinkel 2016] Steffen Kinkel, Angela Jäger, Djerdj Horvath, and Bernhard Rieder. “The effects of in-house manufacturing and outsourcing on companies’ profits and productivity,” 23rd International Annual EurOMA Conference, At Trondheim, Volume: 23, June 2016.

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:

[Kusnet 2007] David Kusnet. “Highway Robbery II,” report of the National Association of State Highway and Transportation Unions (NASHTU).

Cited in:

[Laplante 2007] Phillip A. Laplante. What Every Engineer Should Know About Software Engineering. New York: CRC Press, 2007.

Order from Amazon

Cited in:

[Leavitt 1958] Harold J. Leavitt and Thomas L. Whisler. “Management in the 1980s,” Harvard Business Review, November-December, 36, 41-48, 1958.

Cited in:

[Li 2015] Z. Li, P. Avgeriou, and P. Liang. “A systematic mapping study on technical debt and its management,” Journal of Systems and Software 101, 193-220, 2015.

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

Order from Amazon

Cited in:

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

Available: here; Retrieved November 10, 2017.

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:

[Plant 2014] Robert Plant. “IT Has Finally Cracked the C-Suite,” Harvard Business Review, July 16, 2014.

Available: here; Retrieved: April 8, 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:

[Ross 2000] Jeanne W. Ross and David F. Feeny. “The Evolving Role of the CIO,” in Framing the Domains of IS Management Research: Glimpsing the Future through the Past, edited by Robert W. Zmud. Pinnaflex, 2000.

Available: here; Retrieved: December 20, 2017.

Cited in:

[Schein 2016] Edgar H. Schein. Organizational Culture and Leadership, Fifth Edition, San Francisco: Jossey-Bass, 2016.

Order from Amazon

Cited in:

[Tempest 2005] “The effect of journal title changes on impact factors,” Learned Publishing 18, 57–62, 2005.

Available: here; Retrieved: April 5, 2018

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:

[Willcocks 2004] L. Willcocks, J. Hindle, D. Feeny, and M. Lacity. “IT and Business Process Outsourcing: The Knowledge Potential,” Information Systems Management 21:3, 7-15, 2004.

Cited in:

[Woodard 2013] C. Jason Woodard, Narayan Ramasubbu, F. Ted Tschang, and V. Sambamurthy. “Design Capital and Design Moves: the Logic of Digital Business Strategy,” MIS Quarterly 37:2, 537-564, 2013.

Cited in:

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