How do you estimate technical debt and rework costs?

Per se, there is nothing wrong with accumulating technical debt. Sometimes, this might be a calculated trade-off between the cash flow "here and now" vs long-term product stability. E.g. a startup that has no visibility into the sources of funding beyond a couple of months might be forced to make a hard trade-off that favors immediate gratification in the form of a product launch that potentially generates cash flow. Once they have adequate working capital, they could "pay off" the accumulated tech debt. Thus, it is critical to understand the context before deciding if tech debt is bad on its own!

A lot of us get stuck with estimates and estimations. Though controversial, I believe that estimations have a limited shelf life and value. The goal should be to see how the teams can create flow. Tech debt is only the problem once it hinders the team's flow. What has worked best for me, is to allow the product and technology teams to assess their flow and pace/throughput and figure out what they want to simplify from a refactoring perspective. Many times this focus on estimations and detailed plans emerges from micro-managing leaders wanting to have the comfort that because there is a detailed plan for the next six months, things will be fine.

Estimation in the world of software development, is notoriously intractable. Countless methodologies, techniques and tools have been and will be used. However, how effective these are, is still a question. Given this, estimation of technical debt is far more difficult work and often can be misleading. Still, the exercise of estimation can be quite helpful in identifying hitherto undiscovered interconnection of components / modules. This in turn, makes the estimated technical debt more visible and rework costs, more realistic. It is easier then, to decide whether to go or no-go, and how-far. In general, the outcome of estimation is expected to be a numeric figure and understandably so. The real value lies in the exercise itself, though.

If you walk through the logic of technical debt, it becomes clear that it isn't limited to the technical domain (despite its namesake). A root cause of such debt can be caused by improper understanding of requirements. Estimating technical debt then becomes a reflection around quality of communication between technical and non technical teams. The importance of tracing the root cause of such debt can uncover gaps rooted in competency, politics, business architecture, and so on. Estimating technical debt is useful insofar as it empowers cross functional teams to collectively reduce that debt. Otherwise, it can better be considered a barometer for technical anxiety since nothing of value will be done, in the short term, to address it.

Most of us see Estimation / Projections as burden and non-value add activity. However, it is a little myopic, as by doing so we are ignoring the requirements of many stakeholders. No project / program has unlimited resources, therefore, to optimize the value of that project, and value for the organization, it is pertinent to understand the true state of the project. There are so many tools which can give that info. with reasonable accuracy, w/o burdening your engg. team. For arguments sake, even if engineering team has to spend some effort and time to do so, it benefits them too, as the goal of the project is to maximize the value for its user / stakeholders. Hence, their goal can't be different from a project or an organizational goal.

Estimating technical debt is hard because it is distributed across layers of - development, architecture, operations and processes. Some metrics that can help get a sense of technical debt are - Test automation coverage in terms of unit, integration and system tests - Type and frequency of customer reported issues - Turn around time to fix an issue - Release frequency of an product increment The most important is the vibes you get from your product architects and senior engineers - they know how deep the rot has set in.

I agree with the statement that not all technical debt is bad. We can make decisions that allow teams to be flexible and address the debt if and when it is necessary. There are different types of technical debt. Technical debt at the code level is measure by the amount of rewrite, the maintainability (time to address defects or make changes) of the code, and the test coverage and testability of the code. We may also maintain a map towards a target architecture and work through each step as they are necessary. So based on performance goals and SLAs, we may move along different paths of towards the target architecture. This also allows us to be flexible as business needs change and minimize debt.

Estimating technical debt is a dynamic process that is critical for effective project management. Following practices can help to easily estimate tech debt: 1.Effort estimation for rework: Closely work with Technical Architects, Tech Lead to understand how much effort is spent on the tasks which may require rework in terms of resources, time spent and vendor cost. 2.Establishing critical success measures and metrics to asses project quality and technical debt and monitor metrics like code complexity and code churn to identify areas that may need attention. 3. Reviewing project documentation and change logs is essential. It helps in understanding the evolution of the project and any changes that might have introduced technical debt.

From what I have seen, three inputs are quite effective in estimating 'technical debt': 1) The UseCases / Features which have been 'revisited' (i.e., came back to support/QA/ENG after release of a version) or 'pushed to backlog' the most number of times so far. This exercise gives the 'Product' side, a say in the estimation. The business side must bring, on the table. what the 'cost of *not* doing something', is! 2) The Product-wide testcases/behaviour which have been red-flagged in the past but kept aside for 'time-to-market' reasons: these are QA side's inputs. 3) Finally, identification and analysis of areas where the code is brittle/tests are non-existent/change is an unknown danger: the ENG are best placed to offer these.

Eliciting feedback from engineers is the most effective way to get a sense of the amount of technical debt in your code base. Static analysis tools, like SonarQube, highlight areas that may have technical debt. But the real test is whether engineers find an area of the codebase difficult to maintain, enhance, or test. It's a qualitative label assigned to a portion of the codebase. Don't depend solely on expert opinion or static analysis to make an assessment. Gather sentiment from the engineers that operate and maintain your codebase. Measuring technical debt after it's encountered is easier than forecasting it. Predicting technical debt without attempting to modify, maintain, or test it, is very hard.

The 'rework' cost primarily consists of: 1) Identifying/(re)writing testcases to ensure zero regression 2) Design of components/APIs etc. that the rework results in (more w/board than IDE) 3) Beta-testing (or STAGE testing) Tools/techniques help, but at the end, the team which build and manage the software, know what's best! Human judgment is necessary.

Incorporate Time Value: Don't just look at the direct costs of rework. Factor in the opportunity cost—the projects you could have tackled if not for the rework. Use your project management software to track time spent on rework and multiply it by hourly rates to get a fuller picture of rework costs.

The best way is comparing the rework costs to the expected benefit (ROI) and the opportunity cost which is being lost by not paying off a tech debt. For example, a bad design in a code can lead to not only a degraded performance but at times also increased infrastructure costs. In such cases, clearing the tech debt helps in both ways. Generally speaking, if we can categorize the tech debts as per the impact areas like Performance, Cost, User experience etc. the comparison and also prioritization become much easier. At the end of the day, its important to realize (and also help others realize) that a tech debt is always a hindrance to a smooth evolution of a software. It either hurts itself at scale or increases the cost of an upgrade.

Leverage Metrics for Informed Decisions: Use KPIs like 'Time to Market' and 'ROI' alongside interest rates and principal repayment. This multi-metric approach offers a nuanced understanding of when to tackle technical debt versus when to proceed with rework.

Ultimately the goal of all business systems is to support some portion of the business; to increase revenues, reduce costs or otherwise enable the business to meet their goals. Rework and technical debt need to be tied back to some goal of the business. If there is no way to do that, it becomes suspect to invest scarce organizational resources into tackling the issue. This is why it is not only important to understand the cost of doing the work, but also the benefit of doing it (this may be reducing costs, enabling a business objective, customer satisfaction, etc). It can be difficult to get technical debt or rework scheduled because the business benefits are not always articulated as such they do not seem important to decision makers.

Leverage Metrics for Strategic Choices Use technical debt and rework costs as critical metrics in your decision-making toolbox. They help you decide what to tackle first and what can wait. Prioritize issues that, when resolved, offer the highest ROI. These metrics also enable you to evaluate the financial viability of new features or changes, giving you a clear roadmap for your project's future.

For decision making - which finally is done by the chief stakeholders - the most important data is the 'cost of *not* doing something'. ENG and QA can help them to reach this data, but the decision lies with them, ultimately. The stakeholders must remember that despite the best effort of reducing the cost to a numerical value, the subjectivity persists. Moreover, the act of removal of 'tech-debt' may cause newer 'debts' to spring up.

We have to make choices about where we’ll apply our efforts. Spending time on X means we’re not going to spend time Y. So we want to apply some thought to our decision-making. Technical debt (the good kind) and rework are features of software development (not bugs).

Most important points to remember: 1. Technical Debt is not always bad, sometimes people accumulate knowingly for various business reasons. 2. It may not really be important to estimate technical debt as this estimate will be valid for a limited time. 3. Technical Debt depends heavily upon evolution of technology happening around us. Technologies are born, they evolve, die and sometimes pivot, every such thing would have a significant impact on the estimates of tech debt. 4. Main focus of businesses is profitability & ROI. An enterprise would happily accumulate technical debt if it translates to higher margins in near future.

There are different types of tech debts created: to validate an assumption, to build an MVP, a quick fix for a critical issue. Others are related to a new version of a library or framework. One of the biggest issues is the lack of visibility. People talk about it but don't capture it, don't discuss it, and get trapped with a massive cost of delay. I worked in a company suffering from tech debt. After an agreement to make them visible in the backlog, it was prioritized along with the product. We got 20% of the teams' capacity dedicated to tech debt, reducing lots of discussions at a leadership level It is important to discuss its costs, but as a part of the day-to-day, it is crucial to understand/take action on how we can reduce them first.

The text is AI generated so is missing the actual ideas. Let's think from the two types of management In "Agile" management the point in it is to obtain very quick result to market, the technical debt & rework it is part of initial architecture but not really think about. The second way of work is "Waterfall" management, when you stay a lot of time and mitigate all aspects. So everything is related how much time and cost want to put in the planning phase, how quick you want to reach the market.

The best way to remove debt is to 'prevent' them. Often, the stakeholders see this as an obstacle to business! The 'time-to-market' is indisputably a driver for the business, and because prevention entails thinking, analyzing, simulating etc., the exercise eats into that time. Hence, the decision to accumulate debt! While this is pragmatic, the very nature of software (as opposed to hardware) invites changes which are seemingly 'easy to make'. This ease underlies the cheer for accumulation of debt (and 'come back to it later'). What is missed though is the 'context': a piece of non-trivial software is a store-house of 'contextual knowledge', often un-tracked. Tech-debt is a manifestation of this. Worth-remembering!

Tech Debt is primarily related to your strategic and tactical approach. It involves understanding the gaps that arise while planning your strategic and tactical advantages. It's also about having a precise vision of how your concept fits into the market and assessing the technical capabilities of your team to execute it effectively.