Last updated on July 11th, 2021 at 04:57 pm
We need a high-caliber discussion of accounting for technical debt [Conroy 2012]. It’s a bit puzzling why there’s so little talk of it in the financial community. Perhaps one reason for this is the social gulf between the financial community and the technologist community. But another possibility is the set of pressures compelling technologists to leave technical debt in place and move on to other tasks.
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 we actually needed to reach our goals. Because of our advanced understanding, 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.
Echo releases and management decision-making
A (potentially) lower-cost approach involves immediately retiring the debt and re-releasing the improved asset. I call this an “echo release.” An echo release is one in which the asset no longer carries the technical debt we just incurred and immediately retired. But echo releases usually offer no immediate, evident advantage to the people and assets that interact with the asset in question. That’s why decision makers have difficulty allocating resources to echo releases.
This problem arises, in part, from the effects of a what I regard as 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. MICs appear in multiple forms: lower productivity, increased time-to-market, lost market share, elevated turnover of technologists, and more (see “MICs on technical debt can be difficult to measure”). Enterprise accounting systems don’t generally represent these phenomena very well.
The cost of not accounting for the cost of not retiring technical debt
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. These discussions usually omit from consideration altogether any mention of the cost of not retiring the debt. That cost can be enormous, because it is a continuously recurring periodic charge with no end date. Those costs are the costs of not accounting for the cost of not retiring technical debt.
If we do make long-term or intermediate-term projections of MICs or costs related to echo releases, we do so to evaluate proposals for retiring the debt. Methods vary from proposal to proposal. Few organizations have standard methods for making these projections. And lacking a standard method, comparing the benefits of different debt retirement proposals is difficult. This ambiguity and variability further encourages decision makers to base 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. But few balance sheets mention outstanding technical debt. Ignorance of the liabilities outstanding technical debt represents creates an impression that the enterprise has capacity that it doesn’t actually have. That’s why tracking our technical debts as liabilities would alleviate many of the problems associated with high levels of technical debt.
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-standard patterns for debt retirement proposals. Such standards would make possible 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 retirement projects, or when defects in production systems need attention. When those systems are out of production for repairs or testing, revenue capture might undergo short disruptions. 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. Technical debt consisting of misalignment between the testing and production environments can allow defects to slip through. Undetected defects can create new disruptions. Even a short disruption of a high-volume revenue stream can be expensive.
In advance of any debt retirement effort, we can identify some associations between classes of technical debt and certain revenue streams. This knowledge is helpful in estimating the contributions to MICs or MPrin from revenue stream disruption.
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 it can cause persistent and irreparable reductions in market share. To facilitate comparisons between different technical debt retirement proposals, estimates of these effects are invaluable.
Data flow disruption
All data flow disruptions aren’t created equal. Some data flow processes can detect their own disruptions and backfill as needed. For these flows, the main contribution to MICs or MPrin is delay. And the most expensive of these are delays in receiving or processing orders. Less significant but still important are 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. We can develop standard packages for doing so. And we can apply them repeatedly to MICs or MPrin estimates for different kinds of technical debt.
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. 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.
[Conroy 2012] Patrick Conroy. “Technical Debt: Where Are the Shareholders' Interests?,” IEEE Software, 29, 2012, p. 88.
Available: here; Retrieved: August 15, 2018.
[Cunningham 1992] Ward Cunningham. “The WyCash Portfolio Management System.” Addendum to the Proceedings of OOPSLA 1992. ACM, 1992.
- Metaphors and the term technical debt
- Technical debt in software engineering
- Exogenous technical debt
[Fowler 2009] Martin Fowler. “Technical Debt Quadrant.” Martin Fowler (blog), October 14, 2009.
Available here; Retrieved January 10, 2016.
- Technical debt in software engineering
- Team composition volatility
- How performance management systems can contribute to technical debt
- Unrealistic definition of done
- Spontaneous generation
- Legacy debt incurred intentionally
- Controlling incremental technical debt
- Refactoring for policymakers
Other posts in this thread
- Managing technical debt
- Leverage points for technical debt management
- Undercounting nonexistent debt items
- Crowdsourcing debt identification
- Demodularization can help control technical debt
- Legacy debt incurred intentionally
- Metrics for technical debt management: the basics
- Three cognitive biases
- The resilience error and technical debt
- Synergy between the reification error and confirmation bias
- Retiring technical debt can be a wicked problem
- Retiring technical debt can be a super wicked problem
- Degrees of wickedness
- Accounting for technical debt