Technical debt refers to the implied costs and risks of shortcuts taken early in product development that make it more difficult to add features efficiently later on. When engineering teams take actions like copying and pasting code or postponing needed refactoring in order to hit an aggressive launch timeline, it speeds up short-term delivery but slows velocity over time. Code entropy increases, quality suffers, and development costs mount. Balancing technical debt is often described as a tug-of-war between providing new features to customers faster and rewriting old code to facilitate future releases. Product managers feel constant pressure to prioritize shiny new features that drive adoption and revenue. However, allowing too much technical debt makes it exponentially harder for developers to build upon existing infrastructure. There needs to be a thoughtful balance between new feature work and paying down technical liabilities.
This blog post will examine best practices for effectively prioritizing and balancing technical debt repayment with an aggressive product roadmap. Through establishing clear processes for quantifying debt, restricting high-liability areas, and rotating teams through refactoring work, product and technology leaders can align on optimal levels of technical debt given business goals and engineering capacity. Overcoming resistance from stakeholders impatient for new features is critical as well through data-driven communication about debt-induced slowdowns.
Why Technical Debt Accumulates
Time-to-market pressures often result in engineering teams taking on technical debt to hit aggressive launch goals. Startups in particular feel immense pressure to release an MVP and get traction with early adopters before funding runs dry. As a result, developers feel forced to copy and paste code, skimp on testing and documentation, and avoid wholesale architectural changes in favor of quick fixes. What feels expedient in the short term sets the product up for velocity-killing debt later on.
Lack of architectural planning and oversight also leads to accumulating layers of technical debt over time. Without someone guiding the overall technical vision and having the authority to restrict subpar coding practices, inconsistencies pile up and components become highly interdependent. Knowledge gaps with new technologies likewise result in debt; if developers are unsure how to leverage new capabilities properly, they often cobble together makeshift solutions while they skill up. Finally, continually changing product requirements and scope creep results in teams postponing structural improvements until after features ship. But the right “later” time never comes.
Costs and Risks of Technical Debt
Carrying excessive technical debt has tangible costs and risks that compound over time. Every new feature released adds more waste and inefficiency on top of the existing debt burden.
From a cost perspective, technical debt increases the pricing of future changes and updates. As the codebase grows more complex and interconnected, developers spend vastly more time understanding existing logic and untangling dependencies before they can add anything new. Simple changes take longer, and major new features can require near-total rearchitecture. Hundreds of developer hours go solely towards compensating for past expediency.
Technical debt also actively slows velocity and throughput over time. Engineering teams may continue releasing features on a roadmap, but they deliver less and less value per sprint. Eventually, velocity grinds to a halt as developers spend their time solely addressing quality issues and outages resulting from past quick fixes rather than building anything new. Pressure mounts as stakeholders wonder why throughput has decreased sharply without changes in resourcing or process.
The compounding interest costs of technical debt even extend to live sites and applications. Products carry more bugs and quality issues, reliability suffers, performance lags, and incidents happen more frequently. Customers experience firsthand the slowdowns caused by past engineering expediency, and satisfaction as well as retention suffers.
Finally, excessive technical debt increases security, regulatory, and compliance risks for companies. Security vulnerabilities, exposure of customer data, and violations of government regulations become more likely over time if no effort is made to repay debt and improve engineering practices. The consequences for companies can be severe.
Prioritizing Technical Debt Effectively
To balance new feature development with responsible technical debt repayment, organizations need consistent, objective processes for quantifying, prioritizing, and paying back technical liabilities already incurred.
Quantifying debt requires analysis tools calculating the time, resources, and scope required to address each liability based on factors like dependencies and code quality. Granular visibility into existing liabilities is needed first before teams can prioritize what to tackle and in what sequence.
Technical debt then gets categorized by both risk level and estimated cost to address. High-risk debt with lower repayment costs gets prioritized first, while moderately risky debt with extensive scope and unknowns may be postponed. The goal of sequencing is to maximize engineering efficiency and reduce organizational risks through payments.
Standardizing the definition of “done” for a technical debt repayment story is critical as well to avoid further liabilities being taken on. Requirements like updated documentation, full test coverage, and decoupled architecture need enumeration so that teams don’t inadvertently accumulate debt while trying to reduce it. Developer incentives should connect to debt reduction metrics wherever possible.
Integrating with New Feature Workflow
Efficient technical debt prioritization and repayment needs to integrate tightly with new feature development workflows rather than compete for resources and bandwidth. Engineering teams should not feel that they need to swap between two distinct modes of working.
A common approach is to allocate a percentage of each development cycle expressly towards paying back technical debt before any new feature work can commence. For example, 20% of all sprint capacity gets earmarked for debt repayment tasks above a certain threshold cost before new stories are pulled into the sprint. This creates constant throughput for both debt and feature work.
Another method is to rotate different engineering teams through the backlog of technical debt stories once their feature assignments are completed. This establishes orderly queues and consistency rather than having one dedicated “B team” addressing all debt. The continued context switching helps prevent teams from becoming disengaged only working on repayment.
Certain high-liability components and services should face restrictions from accepting new feature work altogether until their issues are addressed. Routing all modification requests to debt repayment stories first forces architectural simplification before layering on added complexity.
Finally, mandating that all new feature work include reasonable refactoring and documentation updates helps incrementally repay some principal on technical debt even during new development. This prevents the accrual of “interest” on existing liabilities.
Overcoming Resistance from Business Stakeholders
The largest barrier to consistent technical debt repayment is often resistance from business stakeholders who see these efforts as distracting from feature velocity. Without direct visibility into the engineering burden, they often argue that repayment work delivers no tangible customer or market value compared to shiny new products.
Countering this mindset starts with data-driven communication about the measurable drag that technical debt exerts on developer throughput over time. Quantifying the likely acceleration of delivery velocity after conducting repricings makes the ROI of repayment work clear. This also builds engineering support.
Another persuasion mechanism is to demonstrate incremental velocity gains after initial technical debt repayment sprints/cycles to prove acceleration. This makes the purported benefits tangible rather than abstract and hypothetical. Early examples of features shipping faster after concerted repayment efforts help justify further remediation.
Technical debt repayment should focus first on the liabilities with the greatest customer impact in order to align with business value. Rewrites delivering huge performance gains or removing despised bugs should come first. This phased approach also helps balance competing priorities.
Finally, instilling “technical excellence” as a cultural value and one of the company’s competitive advantages helps the entire organization rally behind debt reduction. Stakeholders need to take pride in flawless architecture just as much as cash flows.
Key Takeaways for Product Teams
For product managers facing rising tensions with engineering teams over technical debt repayment competing with aggressive roadmaps, several key takeaways can help reframe the balance discussion:
- Quantify existing technical liabilities and their drag on velocity through code analysis and benchmarking. Forecast, don’t speculate.
- Institute orderly technical debt workflows integrated with feature development, such as XX% repayment quotas per cycle. No more all-or-nothing tradeoffs.
- Restrict engineering work on fragile components until remediation, forcing architectural simplification first.
- Communicate velocity acceleration and quality gains from debt repayment through incremental working examples, not hypotheticals.
- Phase technical excellence efforts around customer priorities first to demonstrate business value rather than solely technical wins.
Ultimately, balancing engineering health with product delivery commitments comes down to transparency and accountability on both sides. The path forward requires acknowledging core dependencies, restricting case-by-case tradeoffs around technical debt, working off objective risk and cost data, and celebrating both feature releases AND architectural improvements. With shared context and ownership, balanced outcomes happen organically.
Conclusion
Technical debt presents a constant tug-of-war between speeding up immediate feature delivery and facilitating long-term engineering efficiency. But with the right blend of technical analysis, workload balancing processes, and cross-functional buy-in across stakeholders, paying down debt does not need to forestall an aggressive product roadmap.
By quantifying the economic and risk costs of excessive technical liabilities, restricting high-impact areas from accumulating further debt, integrating repayment workflows with new feature sprints, and communicating returns through incremental working examples, product teams can justify ongoing remediation efforts. The end goal should be optimizing for both customer value NOW and sustainable delivery velocity later through holistic product and technical excellence.
Superior outcomes derive from transparency, accountability and bringing engineering considerations into strategic product planning conversations early on. While it requires short-term patience from stakeholders, maintaining a balance between new and old ultimately enables companies to confidently build upon their past for years rather than having to restart from scratch every few quarters.