Technical debt and engineering resources

Last updated on July 7th, 2021 at 10:34 am

Flooding from Hurricane Katrina in New Orleans, 2005.
Flooding from Hurricane Katrina in New Orleans, 2005. The forces of Nature can overtop or undermine any levee humans can build. So it is with technology. Organizational policy and politics can overcome or undermine any technology humans can devise to attain mastery over technical debt. To master technical debt, technology isn’t enough—we must also deal with policy and politics.

Improving organizational effectiveness in technical debt management—or avoiding incurring new technical debt—should create significant savings and competitive advantages. These benefits arise from reductions in metaphorical interest charges (MICs) that result from retiring technical debt. But these benefits become available only if engineering capacity increases relative to the total debt-related workload. After the technical debt management program is in place, if the balance between engineering resources and debt-related workload becomes more favorable, then organizational effectiveness can improve. But if the balance becomes less favorable, as a result of reductions in engineering resources, organizational effectiveness won’t improve, even at lower levels of technical debt.

Unfortunately, some organizations adopt advanced technical debt management practices while reducing engineering capacity. If reductions are dramatic enough, engineering effectiveness is no better than it was before initiating the technical debt management program. The reason for this is that the engineering process isn’t the sole cause of technical debt. Improving the engineering process to eliminate technical causes of technical debt leaves nontechnical causes in place. That’s why technological solutions to the technical debt management problem might not produce benefits in organizational effectiveness and agility.

The focus of technical debt research has been technology

The focus of research in technical debt management has been on technology—recognition of technical debt, its measurement, representation, retirement, and so on. Progress on improving the engineering process has been significant, especially in software engineering, where a clear “research roadmap” has appeared [Izurieta 2017]. Effective tools for automating or partially automating technical debt detection and retirement will be widely available and very generally effective in the not-too-distant future, at least for software. But progress has transcended debt detection and retirement. Avoiding technical debt formation to the extent possible is much preferable, and in some contexts, it’s practical even today, as Trumler and Paulisch suggest [Trumler 2016].

Such developments might or might not have much impact on the limiting the effects of carrying technical debt. Given the necessary resources, engineering organizations could retire much of the technical debt now extant. That is, the will and the capacity to invest in debt retirement determines debt retirement rates. Currently, the levels of will and capacity for such activity are insufficient. But if new methods for managing technical debt become available, one might wonder whether organizations will apply resources sufficient to ensure that they actually experience a reduction in the limiting effects of technical debt.

Technological development isn’t enough

The open question is this: will technological developments alone give us control of the problem of technical debt? Perhaps not. Advancements in technical debt management do benefit organizations. But they could use that benefit to execute reductions in engineering staffing. If they do, they could divert savings to other parts of the enterprise. That would allow technical debt to remain at reduced levels that could still compromise the effectiveness of that reduced engineering staff.

For example, research has shown that schedule pressure contributes to technical debt formation and persistence. Suppose that the engineering groups of an organization become more adept at managing and preventing technical debt. Suppose further that the organization’s marketing and sales groups don’t improve their own intelligence and planning processes. Then Marketing might demand new capabilities with ever shorter timelines. That could lead to increased schedule pressure for the engineering groups. Then the enterprise might not benefit from the new technical debt management capabilities, even though the burden of technical debt has been reduced.

Until we have evidence of significant change in the behavior of non-technologists—or even acknowledgment that their behavior contributes to debt formation—we can expect the effects of nontechnical causes of technical debt to persist, and possibly even to grow.

This blog focuses on the nontechnical etiology of technical debt formation and persistence, and approaches for managing it. Watch this space.


[Izurieta 2017] Clemente Izurieta, Ipek Ozkaya, Carolyn Seaman, and Will Snipes. “Technical Debt: A Research Roadmap: Report on the Eighth Workshop on Managing Technical Debt (MTD 2016),” ACM SIGSOFT Software Engineering Notes, 42:1, 28-31, 2017. doi:10.1145/3041765.3041774

Cited in:

[Trumler 2016] Wolfang Trumler and Frances Paulisch. “How ‘Specification by Example’ and Test-driven Development Help to Avoid Technical Debt,” IEEE 8th International Workshop on Managing Technical Debt. IEEE Computer Society, 1-8, 2016. doi:10.1109/MTD.2016.10

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