Technical debt, a term first coined by Ward Cunningham, is not unlike financial debt: It refers to the practice of making coding or design decisions to expedite production or gain other short-term benefits, knowing that these decisions may require corrections later. Like financial debt, technical debt offers both benefits and costs.
Why technical debt accrues
Typically, technical debt results when developers take shortcuts that enable them to quickly deliver features or functionality to keep up with customer demand. This might mean being first to market, responding to time-critical customer needs, and/or improving performance and value.
[ Before you discuss tech debt with your bosses, customers, or partners, learn how to explain technical debt in plain English.]
Technical debt can also accrue because a product’s technology or architecture no longer scales and needs refactoring. Sometimes it accrues because it is invisible or inadvertent, as shown in this technical debt quadrant.
Left untracked, technical debt can quickly become difficult to manage, or even to recognize. Often it becomes such a burden that it prevents developers from making consistent progress on critical business needs.
Still, taking on technical debt is not necessarily a bad thing, as long as you recognize that you are taking it on and understand that the debt needs to be paid down. Sometimes it makes sense to take a coding shortcut if it helps you get to market sooner or be more responsive to your customers’ needs.
Often, the benefits outweigh the costs of taking on technical debt. The ability to get customer feedback quickly is critical, for example. But if a feature that was rushed doesn’t meet customer needs, refactoring is irrelevant because the feature will be deprecated or little-used. On the other hand, if the feature proves to be valuable and heavily used, it should be a candidate for refactoring, or paying down that debt.
When to pay down your technical debt: 4 signs
Here are four signs that it is time to address your technical debt:
Flow velocity decreases: Flow velocity gauges whether value delivery is accelerating. It represents the number of work items completed over a specific time period, which enables you to measure throughput. As such, a decrease in flow velocity is an important sign that intervention may be needed.
Flow time increases: Flow time can identify when time to value is getting longer. It measures the time it takes for work items to go from “work start” to “work complete,” including both active and wait times. This allows you to measure time-to-market for the desired throughput to ensure that it is fast enough for the short feedback cycles needed when dealing with uncertainty. When flow time increases, organizations can’t respond fast enough to business needs.
Quality decreases as the code base becomes more fragile: Quality can be measured in several different ways, but the most common is the number of production incidents your customers experience. A decrease in quality should never be ignored.
Costs increase: Costs include all those associated with the product, including people resources, infrastructure, and license costs. An increase in costs should be addressed promptly to ensure your company can remain competitive.
How to measure technical debt
You can’t fix what you can’t measure. Before you can pay back technical debt, you must first measure the current state of work (e.g., technical debt, customer feature work, addressing defects, and managing security/risk issues). Correlating the impact of tech debt with value-adding work can help your business understand its danger on the bottom line. Set aside time and resources every financial year to tackle technical debt, as it can accumulate because of a lack of funding and sponsorship.
When developers take shortcuts, it’s a good practice to create technical debt work items as a reminder that this debt work needs to be paid back.
Making this visible as a work item, along with features, defects, and risk, is key to ensuring it can be prioritized appropriately and given the resources required. As a rule of thumb, some teams set aside 20 percent of their bandwidth to ensure that debt gets paid off.
What to measure: 3 tips
Measure technical debt ratio: First, figure out where you stand. Tools such as SonarQube and Coverity can help you measure technical debt and determine your technical debt ratio (TDR), which is the ratio of the cost to fix the software system vs. the cost to build it. The TDR is important as it tells you how long it might take to convert problematic code into quality code.
Determine payback time: Next, IT and business should look at trends that determine an appropriate level for when to pay back debt. Like any business that maintains a healthy level of debt on its books, IT and the business need to understand the right level of technical debt for their situation. This may vary from company to company, product to product, and even team to team. It involves determining how much capacity to allocate to debt until the metrics (flow velocity, flow time, and quality) improve to produce the desired business results.
Prioritize debt: Finally, determine which debt is most important to address in terms of what will improve productivity, reduce flow time, and improve quality. Focus on the highest-priority items first, utilizing the capacity determined in the previous step.
Tracking and measuring technical debt may seem cumbersome, but left unmonitored, technical debt will gradually impact the flow of value to customer-facing products. Ensure that technical debt is visible and measured so that the business and IT can team up to proactively tackle and manage technical debt. This will help you maintain a healthy product portfolio that can sustain your business.
[ How can automation free up more staff time for innovation? Get the free eBook: Managing IT with Automation. ]
What to read next
Subscribe to our newsletter.
Keep up with the latest advice and insights from CIOs and IT leaders.
Nice Articles.... Thank You So Much....
No mention of GitClear in here? They have been instrumental in helping us identify specific directories where our developers get stuck.