16 Causes of Technical Debt and How to Avoid It


Introduction
Did you know that, conservatively, 10-20% of software development budgets are spent addressing technical debt instead of building new features? (McKinsey & Company, 2020; Forbes, 2022; Software Improvement Group, 2025).
In 1992, Ward Cunningham coined "technical debt" to describe the lasting consequences of prioritizing quick fixes over quality in software design or development. For example, rushing flawed code to meet a deadline—knowing it will need rewriting later—creates technical debt, a persistent challenge that can hinder long-term maintainability.
Why Technical Debt Matters More Than Ever
In today’s fast-paced digital economy, organizations face pressure to deliver features quickly using Agile, DevOps, cloud-native technologies, microservices, AI/ML, embedded systems, IoT, and more. These trends drive innovation but amplify technical debt without disciplined quality controls. Technical debt extends beyond code to architecture, infrastructure, security, testing, documentation, and team culture. Unchecked, it drives software entropy, degrading system health, inflating costs, slowing delivery, and frustrating teams. Conversely, proactively managing technical debt unlocks a competitive edge—fostering faster innovation, higher quality, and resilient products and services.
Key Causes of Technical Debt
There are 16 primary causes of technical debt.
- Time Pressures: The drive to ship quickly fuels technical debt. Agile sprints, continuous delivery, and market demands pressure teams to cut corners on design, testing, or documentation, incurring debt that grows over time.
- Complex Designs: Complexity from legacy monoliths, sprawling microservices, or tangled integrations raises maintenance costs and fragility. Both over-engineered and under-engineered (overly simplistic) designs can exacerbate technical debt.
- Non-Compliance with Standards: Disregarding coding, security, or regulatory standards leads to inconsistent codebases and costly vulnerabilities.
- Skill Gaps or Turnover: Inexperienced teams or high turnover yield suboptimal code and designs. Remote work can worsen knowledge silos, amplifying debt.
- Poor Code Quality: Copy-pasting code, inadequate reviews, or outdated tools create brittle, hard-to-maintain codebases.
- Delayed Refactoring: Postponing refactoring due to backlog pressure or fear of breaking features lets issues pile up, becoming harder to fix.
- Inadequate Testing: Skipping automated unit, integration, or end-to-end tests results in fragile systems with proliferating defects, hindering future changes.
- Tooling Mismatches: Outdated libraries, unsupported frameworks, or incompatible tools generate hidden debt.
- Infrastructure Mismanagement: Mismanaged cloud resources, container sprawl, or neglected infrastructure-as-code drive related debt.
- Security Neglect: Ignoring vulnerabilities or skimping on security creates risky debt with regulatory and reputational fallout.
- Documentation Gaps: Missing or outdated documentation, such as for code, APIs, AI model parameters (e.g., unrecorded training data assumptions), or embedded system firmware (e.g., untracked hardware specs), slows onboarding and raises error rates.
- Cultural and Process Issues: Poor visibility, unclear ownership, inadequate code reviews, or siloed teams (e.g., frontend-backend disconnects causing redundant code) foster systemic debt.
- Data Debt: Poor data quality (e.g., incomplete, inconsistent, or inaccurate datasets, especially in AI/ML), inadequate data governance or lineage, data silos or inaccessible datasets, outdated or undocumented data schemas, and hardcoded data dependencies create inefficiencies and costs that compound over time. In AI/ML projects, where data is a core asset, issues like unoptimized training datasets, model drift, and lack of data traceability significantly hinder scalability and accuracy.
- External Dependency Debt: Reliance on unstable, deprecated, or poorly maintained external systems, APIs, or vendor services leads to cascading failures, forced migrations, or performance degradation that compounds over time. This refers specifically to third-party or external dependencies.
- Service Debt: Suboptimal or out-of-date internal services or service integrations (e.g., incompatible versions or unstable dependencies within the organization’s own systems) lead to maintenance overhead and system fragility. This is distinct from external dependency debt, which involves third-party systems.
- Build Debt: Inefficiencies or fragility in the build, integration, or deployment process (e.g., slow builds, broken pipelines, or manual steps) that hinder rapid development and delivery.
The High Cost of Ignoring Technical Debt
Technical debt accelerates software entropy, causing:
- Higher Maintenance Costs: More time fixing bugs or updating legacy code than innovating.
- Slower Delivery: Complexity and instability bog down teams.
- Poorer Quality: More defects and security risks.
- Lower Morale: Developers frustrated by brittle, unclear code.
- Rewrites: Severe debt may necessitate costly system rewrites.
Unmanaged technical debt turns software from an asset into a liability, hindering product viability and competitiveness. But it can be managed.
The following table—Types of Technical Debt and Their Mitigation Strategies—summarizes key information from this article.

How to Avoid and Manage Technical Debt
Technical debt is inevitable in real-world projects, but proactive management mitigates its impact:
- Simplify Designs: Prioritize straightforward, modular architectures.
- Refactor Regularly: Leave code cleaner than you found it.
- Test Rigorously: Automate unit, integration, and end-to-end tests to catch issues early.
- Review Code: Use peer reviews and pair programming to maintain quality.
- Track Debt: Log technical debt in backlogs or dedicated systems.
- Address Debt in Sprints/Cycles: Include debt remediation in the definition of done.
- Allocate Debt Control Budgets: Dedicate time to reduce debt.
- Enforce Standards: Use linter tools which automatically flag code issues and enforce style rules, static analysis tools like SonarQube, and architectural reviews.
- Automate Operations: Use DevOps and infrastructure-as-code to minimize operational debt.
- Build a Quality Culture: Promote learning, collaboration, and ownership.
For more, see the table above.
Turning Technical Debt into an Advantage
Teams that manage technical debt gain agility and resilience. Transparent debt tracking enables better prioritization. Ongoing investment in code and processes boosts delivery and innovation. Managing technical debt is a strategic necessity in today’s fast-evolving software landscape.

Conclusion
Technical debt is an inevitable part of software development, but that doesn’t mean it has to spiral out of control. With a clear understanding of its causes and consequences, teams can take proactive steps to manage it effectively and deliver lasting value. Often, technical debt arises from decisions that prioritize speed or short-term wins—whether due to tight deadlines, inadequate design, skill gaps, or deeper cultural challenges within an organization. When left unchecked, this debt compounds, increasing costs, slowing down delivery, and chipping away at team morale. However, with a commitment to practices like refactoring, rigorous testing, and transparent tracking—anchored by a strong culture of quality—teams can keep technical debt in check. In doing so, they don’t just maintain stability; they gain a real strategic advantage.
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Continue reading for:
- Bibliography,
- Additional Articles,
- About Scott M. Graffius,
- How to Cite This Article,
- and more.


Bibliography
- Brown, N., Cai, Y., Guo, Y., Kazman, R., Kim, M., Kruchten, P., Lim, E., MacCormack, A., Nord, R. L., Ozkaya, I., Seaman, C., & Sullivan, K. (2019). Managing Technical Debt: Reducing Friction in Software Development (SEI Series in Software Engineering). Addison-Wesley Professional.
- Cunningham, W. (1992). The WyCash Portfolio Management System. Addendum to Proc. Object-Oriented Programming Systems, Languages, and Applications, ACM, 29-30.
- DeWyze, John (2023, February 16). The 25 Percent Rule for Tackling Technical Debt. Shopify Engineering. Available at: https://shopify.engineering/technical-debt-25-percent-rule.
- Ernst, N. A., Bellomo, S., Ozkaya, I., Nord, R. L., & Kruchten, P. (2015). Measure It? Manage It? Ignore It? Software Practitioners and Technical Debt. Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, 50-60. Available at: https://doi.org/10.1145/2786805.2786848.
- Ernst, N., Kazman, R., & Delange, J. (2021). Technical Debt in Machine Learning Systems. In Technical Debt in Practice: How to Find It and Fix It. MIT Press. Available at: https://direct.mit.edu/books/monograph/5160/chapter/3403977/Technical-Debt-in-Machine-Learning-Systems.
- Ernst, N. (2015, July 27). A Field Study of Technical Debt. Carnegie Mellon University Software Engineering Institute. Available at: https://insights.sei.cmu.edu/blog/a-field-study-of-technical-debt/.
- Forbes (2022, August 10). Measuring And Managing Technical Debt. Forbes. Available at: https://www.forbes.com/councils/forbestechcouncil/2022/08/10/measuring-and-managing-technical-debt/.
- Forbes (2025, June 2). How Today's Technical Debt Becomes Tomorrow's AI Roadblock. Forbes. Available at: https://www.forbes.com/councils/forbestechcouncil/2025/06/02/how-todays-technical-debt-becomes-tomorrows-ai-roadblock/.
- Fowler, Martin (2018). Refactoring: Improving the Design of Existing Code (2nd Edition). Addison-Wesley Professional.
- Graffius, Scott M. (2017, September 25). 7 Causes of Technical Debt and How to Avoid It. Available at: https://scottgraffius.com/blog/files/7-Causes-of-Technical-Debt-and-How-to-Avoid-It.html.
- Graffius, Scott M. (2019). Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change. Scotts Valley, CA: CreateSpace.
- Graffius, Scott M. (2025, January 24). When Agile, AI, and Strategic Thinking Converge. Available at: https://scottgraffius.com/blog/files/when-agile-ai-and-strategic-thinking-converge.html.
- Graffius, Scott M. (2025, June 16). Agile for Unicorns: 7 Keys to Thrive; Scott M. Graffius’ Workshop. Available at: https://scottgraffius.com/blog/files/agile-for-unicorns---7-keys-to-thrive---scott-m-graffius-workshop.html.
- Graffius, Scott M. (2016). Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions. North Charleston, SC: CreateSpace.
- Graffius, Scott M. (2025, May 27). AI in Agile: Benefits, Risks, Outlook. Available at: https://scottgraffius.com/blog/files/ai-in-agile-benefits-risks-and-outlook-by-scott-m-graffius.html.
- Graffius, Scott M. (2025). Agile Protocol: The Transformation Ultimatum. Seattle, WA: Amazon Digital Services.
- Kruchten, P., Nord, R. L., & Ozkaya, I. (2012). Technical Debt: From Metaphor to Theory and Practice. IEEE Software, 29 (6): 18-21. Available at: https://doi.org/10.1109/MS.2012.167.
- Martin, Robert C. (2008). Clean Code: A Handbook of Agile Software Craftsmanship. Pearson.
- Martin, Robert C. (2019). Clean Agile: Back to Basics. Pearson.
- McKinsey & Company (2020). Tech Debt: Reclaiming Tech Equity. McKinsey. Available at: https://www.mckinsey.com/~/media/McKinsey/Business%20Functions/McKinsey%20Digital/Our%20Insights/Tech%20debt%20Reclaiming%20tech%20equity/Tech-debt-Reclaiming-tech-equity.pdf.
- McKinsey & Company (2023, April 25). Breaking Technical Debt’s Vicious Cycle to Modernize Your Business. McKinsey. Available at: https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/breaking-technical-debts-vicious-cycle-to-modernize-your-business.
- Software Improvement Group. (2025, March 26). Technical Debt and Its impact on IT budgets. Software Improvement Group (SIG). Available at: https://www.softwareimprovementgroup.com/technical-debt-and-it-budgets/.
- Tom, E., Aurum, A., & Vidgen, R. (2013). An Exploration of Technical Debt. Journal of Systems and Software, 86 (6): 1498-1516. Available at: https://doi.org/10.1016/j.jss.2012.12.052.

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About Scott M. Graffius

Scott M. Graffius is an AI, Agile, and Project Management/PMO leader, researcher, author, and speaker. Along the way, he spearheaded initiatives that have generated over $2.3 billion in impact for organizations across tech, entertainment, finance, healthcare, and beyond. The following sections provide additional information on his experience, contributions, and influence.
Experience
Graffius heads the professional services firm Exceptional PPM and PMO Solutions, along with its subsidiary Exceptional Agility. These consultancies offer strategic and tactical advisory, training, embedded expertise, and consulting services to the public, private, and government sectors. They help organizations enhance their capabilities and results in agile, project management, program management, portfolio management, and PMO leadership, supporting innovation and driving competitive advantage. The consultancies confidently back services with a Delighted Client Guarantee™.
Graffius is a former VP of project management with a publicly traded provider of diverse consumer products and services over the Internet. Before that, he ran and supervised the delivery of projects and programs in public and private organizations with businesses ranging from e-commerce to advanced technology products and services, retail, manufacturing, entertainment, and more.
He has experience with consumer, business, reseller, government, and international markets.
Award-Winning Author
Graffius has authored three books.
- Agile Scrum: Your Quick Start Guide with Step-by-Step Instructions, his first book, earned 17 awards.
- Agile Transformation: A Brief Story of How an Entertainment Company Developed New Capabilities and Unlocked Business Agility to Thrive in an Era of Rapid Change, his second book, was named one of the best Scrum books of all time by BookAuthority.
- Agile Protocol: The Transformation Ultimatum, his third book and his first work of fiction, was released in April 2025. The book trailer is on YouTube.
International Public Speaker
Organizations worldwide engage Graffius to present on tech (including AI), Agile, project management, program management, portfolio management, and PMO leadership. He crafts and delivers unique and compelling talks and workshops. To date, Graffius has conducted 94 sessions across 25 countries. Select examples of events include Agile Trends Gov, BSides (Newcastle Upon Tyne), Conf42 Quantum Computing, DevDays Europe, DevOps Institute, DevOpsDays (Geneva), Frug’Agile, IEEE, Microsoft, Scottish Summit, Scrum Alliance RSG (Nepal), Techstars, and W Love Games International Video Game Development Conference (Helsinki), and more.
With an average rating of 4.81 (on a scale of 1-5), sessions are highly valued.
The speaker engagement request form is here.
Thought Leadership and Influence
Prominent businesses, professional associations, government agencies, and universities have showcased Graffius and his contributions—spanning his books, talks, workshops, and beyond. Select examples include:
- Adobe,
- American Management Association,
- Amsterdam Public Health Research Institute,
- Bayer,
- BMC Software,
- Boston University,
- Broadcom,
- Cisco,
- Coburg University of Applied Sciences and Arts - Germany,
- Computer Weekly,
- Constructor University - Germany,
- Data Governance Success,
- Deimos Aerospace,
- DevOps Institute,
- Dropbox,
- EU's European Commission,
- Ford Motor Company,
- Gartner,
- GoDaddy,
- Harvard Medical School,
- Hasso Plattner Institute - Germany,
- IEEE,
- Innovation Project Management,
- Johns Hopkins University,
- Journal of Neurosurgery,
- Lam Research (Semiconductors),
- Leadership Worthy,
- Life Sciences Trainers and Educators Network,
- London South Bank University,
- Microsoft,
- NASSCOM,
- National Academy of Sciences,
- New Zealand Government,
- Oracle,
- Pinterest Inc.,
- Project Management Institute,
- Mary Raum (Professor of National Security Affairs, United States Naval War College),
- SANS Institute,
- SBG Neumark - Germany,
- Singapore Institute of Technology,
- Torrens University - Australia,
- TBS Switzerland,
- Tufts University,
- UC San Diego,
- UK Sports Institute,
- University of Galway - Ireland,
- US Department of Energy,
- US National Park Service,
- US Soccer,
- US Tennis Association,
- Verizon,
- Wrike,
- Yale University,
- and many others.
Graffius has played a key role in the Project Management Institute (PMI) in developing professional standards. He was a member of multiple teams that authored, reviewed, and produced:
- Practice Standard for Work Breakdown Structures—Second Edition.
- A Guide to the Project Management Body of Knowledge—Sixth Edition.
- The Standard for Program Management—Fourth Edition.
- The Practice Standard for Project Estimating—Second Edition.
Additional details are here.
He was also a subject matter expert reviewer of content for the PMI’s Congress. Beyond the PMI, Graffius also served as a member of the review team for two of the Scrum Alliance’s Global Scrum Gatherings.
Acclaimed Authority on Teamwork Tradecraft

Graffius is a renowned authority on teamwork tradecraft. Informed by the research of Bruce W. Tuckman and Mary Ann C. Jensen, over 100 subsequent studies, and Graffius' first-hand professional experience with, and analysis of, team leadership and performance, Graffius created his 'Phases of Team Development' as a unique perspective and visual conveying the five phases of team development. First introduced in 2008 and periodically updated, his work provides a diagnostic and strategic guide for navigating team dynamics. It provides actionable insights for leaders across industries to develop high-performance teams. Its adoption by esteemed organizations such as Yale University, IEEE, Cisco, Microsoft, Ford, Oracle, Broadcom, the U.S. National Park Service, and the Journal of Neurosurgery, among others, highlights its utility and value, solidifying its status as an indispensable resource for elevating team performance and driving organizational excellence.
The 2025 edition of Graffius' "Phases of Team Development" intellectual property is here.
Expert on Temporal Dynamics on Social Media Platforms

Graffius is also an authority on temporal dynamics on social media platforms. His 'Lifespan (Half-Life) of Social Media Posts' research—first published in 2018 and updated annually—delivers a precise quantitative analysis of post longevity across digital platforms, utilizing advanced statistical techniques to determine mean half-life with precision. It establishes a solid empirical base, effectively highlighting the ephemeral nature of content within social media ecosystems. Referenced and applied by leading entities such as the Center for Direct Marketing, Fast Company, GoDaddy, Pinterest Inc., and PNAS, among others, his research exemplifies methodological rigor and sustained significance in the field of digital informatics.
The 2025 edition of Graffius "Lifespan (Half-Life) of Social Media Posts" research is here.
Education and Professional Certifications
Graffius has a bachelor’s degree in psychology with a focus in Human Factors. He holds eight professional certifications:
- Certified SAFe 6 Agilist (SA),
- Certified Scrum Professional - ScrumMaster (CSP-SM),
- Certified Scrum Professional - Product Owner (CSP-PO),
- Certified ScrumMaster (CSM),
- Certified Scrum Product Owner (CSPO),
- Project Management Professional (PMP),
- Lean Six Sigma Green Belt (LSSGB), and
- IT Service Management Foundation (ITIL).
He is an active member of the Scrum Alliance, the Project Management Institute (PMI), and the Institute of Electrical and Electronics Engineers (IEEE).
Advancing AI, Agile, and Project/PMO Management
Scott M. Graffius continues to advance the fields of AI, Agile, and Project/PMO Management through his leadership, research, writing, and real-world impact. Businesses and other organizations leverage Graffius’ insights to drive their success.
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How to Cite This Article
Graffius, Scott M. (2025, June 23). 16 Causes of Technical Debt and How to Avoid It. Available at: https://scottgraffius.com/blog/files/16-causes-of-technical-debt-and-how-to-avoid-it.html.
Digital Object Identifier (DOI)
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