Strategies for Managing and Preventing Technical Debt
Technical debt is a critical concept in technology management, representing the accumulated cost of past decisions that slow down future development. Effectively managing this debt is crucial for an organization's long-term health and growth.
Defining and Clarifying Technical Debt
Technical debt is essentially the "tax" a company pays on development to address existing technology issues. It results from a conscious or unconscious decision, often one that made good business sense at the time, but without diligence, it leads to a costly downward cycle involving wasted time and lost opportunities.
Common examples of actions that create this debt include:
- Implementing a temporary fix that becomes permanent.
- Failing to update systems as new versions are released.
- Prioritizing fast delivery over long-term benefits.
- Developing one-off solutions to meet specific business priorities.
To manage the concept more effectively, it is helpful to break the term down into three clarifying categories:
- Technical Debt: The cost of past shortcuts. This slows down development and adds risk, such as legacy code preventing a desired business outcome.
- Technical Maintenance (Upkeep): The ongoing upkeep required for stability, security, reliability, and compliance, including activities like patches and upgrades.
- Technical Transformation: Strategic modernization for growth or innovation, such as a major system upgrade, cloud migration, or new architecture.
Crucially, neglecting Technical Debt and/or Technical Maintenance is what ultimately leads to the necessity of a Technical Transformation.
The High Cost of Technical Debt: Measuring ROI
The impact of significant technical debt can be measured and quantified in a clear loss of productivity and value.
For example, comparing two equally sized 10-person teams (estimated at $1.5 million annually):
| Team | Technical Debt Level | KTLO Activities | New Feature Development | Yearly Spend on New Features |
|---|---|---|---|---|
| Team A | None | 25% of effort | 75% of effort | $1.125 Million |
| Team B | Significant | 40% of effort (due to system complexity) | 40% of effort (complexity reduces effective time) | $600 Thousand |
In this scenario, a net loss of $525,000 in value is lost in just "running the business" due to the technical debt, demonstrating its expense.
Strategy for Remediation: The Architectural Assessment Process
Addressing technical debt requires a structured and business-aligned process:
- Document the Current State Architecture: This must go beyond a simple diagram to include the Source of Truth for data and a clear understanding of dependencies between systems, data, and events.
- Document the Problems/Gaps in the current architecture.
- Document the Desired Future State Architecture (Create a Blueprint): This is the future state architecture, and it must include the "why" that is tied to specific business objectives, such as needing to scale 10x or deliver a specific new feature.
- Define, Size, and Prioritize Initiatives necessary to bridge the gap from the current state to the future state.
The difference between the current state and the desired state can be termed the "Technical Opportunity".
Key Factors for Considering Technical Debt Remediation
When tackling technical debt, not all debt is created equal, and focus is key:
- Focus: Technical debt is typically concentrated in a few systems that will have the largest business impact; this is where effort must be focused.
- Tie to Business Objectives: Some technical debt is best left alone if the cost of addressing it is not worth the benefit. All remediation efforts must be tied to specific business objectives.
- Clear Commitment to Outcomes: Any initiative to address tech debt needs a clear commitment to specific KPIs and business outcomes, such as improving resiliency, increasing customer satisfaction, or generating incremental revenue.
Preventing Future Technical Debt
To prevent the accumulation of new debt, a clear framework of governance and measurement is necessary:
- Ensure Strong Technical Governance.
- Document Decisions and agree on future steps at the time of the decision.
- Measure Productivity and Speed to Market: Track Team productivity (time spent on new capabilities versus dealing with tech debt) and speed to market (the rate and pace of new capabilities released).
Leveraging DORA metrics is a strong way to track these factors:
- Deployment Frequency: How often the team successfully deploys code to production.
- Lead Time for Changes: The time from a code commit to it running successfully in production.
- Change Failure Rate: The percentage of deployments that result in a failure or require a rollback.
- Mean Time to Restore (MTTR): How quickly the team can recover from a production failure.