Accounting for technical debt

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

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

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

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

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

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

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

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

Dealing with accounting for technical debt

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

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

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

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

Revenue stream disruption

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

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

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

Extended time-to-market

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

Data flow disruption

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

Last words

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

References

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

Available: here; Retrieved: August 15, 2018.

Cited in:

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

Cited in:

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

Available here; Retrieved January 10, 2016.

Cited in:

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