Technical Debt 101: Managing Technical Debt with Automation

Technical debt is often framed as a developer problem. But for operations leaders, it’s a silent budget drain and a barrier to scaling efficiently. It accumulates when teams opt for quick fixes over solid architecture, sometimes deliberately, sometimes out of necessity. Over time, this “debt” must be repaid, often at the cost of slowed deployments, higher maintenance, and unpredictable outages.

Unlike pure engineering debt, technical debt in operations appears in clogged intake processes, duplicated manual tasks, and brittle workflows. These symptoms lead to higher costs, missed deadlines, and over-reliance on staff for low-value work.

Unmanaged debt erodes productivity. A 2023 Stripe report found that developers spend over 40% of their time dealing with technical debt. In ops, this inefficiency translates into late shipments, manual workarounds, and customer churn. The opportunity cost is staggering. Every hour spent patching is an hour not spent optimizing.

Non-technical leaders need metrics that translate engineering complexity into business risk:

• • Cycle time delays from inefficient handoffs
  • Cost of poor quality due to legacy code or outdated workflows
  • Compliance risks from unmonitored scripts or undocumented 

Justin Weber, CTO at Sourcetoad, offers a clean analogy: “My kids put their dishes in the sink when they are done with them… I put them in the dishwasher. That is technical debt.” 

Small shortcuts-like leaving dishes in the sink may save effort in the moment but creates more work later, slowing down the entire system. In operations, each manual workaround or deferred task adds up the same way, compounding inefficiencies that must eventually be addressed. It might take a little longer, but it’s better to put the dishes in the dishwasher… unless it needs to soak of course. 

Start with a technical debt register. List known issues, their impact, and remediation complexity. Use a scoring model like the Technical Debt Quadrant to bucket each item as prudent or reckless, and deliberate or inadvertent.

Tools like SonarQube and CodeClimate help automate analysis. For operations workflows, consider process-oriented tools that track workflow duration, touchpoints, and failure rates.

Manual workflows are like hiring someone to turn a crank all day. It works until they call in sick.

Off-the-shelf automation tools such as Zapier, Make, or UiPath let ops teams orchestrate intake-to-delivery without heavy dev resources. These tools reduce human touchpoints by automating:

• • Form intake to ticket creation
  • Customer orders to scheduling
  • Approval routing across systems

A mid-sized logistics firm used Make and Airtable to automate intake-to-delivery workflows. Before automation, fulfillment involved 12 human interventions. After automation, it required only 5. The ops team estimated a 60% reduction in manual work, which freed up staff for customer escalations and quality checks.

While this is just an example, this type of lightweight automation can easily shorten delivery timelines and reduce error rates. It also helps offset technical debt.

Phased modernization is less risky than a full rebuild. It also suits ops teams that cannot afford downtime.

Begin by isolating pain points, such as a brittle intake form, an email-based approval chain, or a custom integration that frequently breaks. Use AI code diagnostics to identify which modules need attention. Tools like GitHub Copilot or Codacy can suggest refactors automatically. 

Refactor modules incrementally. Replace outdated scripts with modular APIs. Shift manual steps to automation tools that connect to your CI/CD pipeline.

Debt control is not a one-time fix, it requires a cultural practice.

Use sprint retrospectives to log emerging debt, and incorporate this into backlog grooming. Encourage code reviews that flag not just syntax issues, but architectural decisions that sacrifice stability for speed.

Adopt DevSecOps practices that embed security, compliance, and debt checks into every deployment. This approach reduces rollback risk and allows ops teams to ship confidently.

Executives do not care about refactor coverage, they care about impact. Report technical debt metrics in operations terms:

• • Backlog hours reduced
  • Tickets resolved faster
  • Release frequency improvements
  • Lower headcount needs due to automation

Tools like ClickUp or Tableau can visualize progress in dashboards for leadership visibility.

• • Technical debt is not just an engineering problem. It affects operations directly.
  • Off-the-shelf automation can cut manual workflow steps by 60% or more.
  • Start with a debt register to score impact and effort.
  • Use AI-powered tools for faster diagnostics and refactoring.
  • Embed debt review into your sprint and CI/CD practices.
  • Show ROI in business terms: cycle time, backlog reduction, and cost savings.

What is a technical debt register? A prioritized list of known technical and process liabilities with scores for impact and remediation complexity.

How does technical debt show up in operations? In the form of manual workarounds, outdated workflows, and delays in service delivery.

Which tools help reduce technical debt for ops teams? SonarQube, ClickUp, UiPath, Make, Airtable, and GitHub Copilot.

Can technical debt be completely eliminated? No, but it can be managed proactively through phased remediation and continuous review.

What’s the best way to show ROI on technical debt remediation? Use metrics that tie to business outcomes, including reduced backlog, improved delivery speed, and automation-enabled savings.