ROI Calculator for Technical Debt Remediation
Model when a remediation investment breaks even by combining productivity gains and reduced incident spend. All inputs stay on your device.
Productivity uplift estimates should be grounded in observable waste removal. For example, Digkas et al. 2020 show teams enforcing clean code policies reduce recurring rework. Incident savings can borrow from outage research such as PagerDuty 2024 to quantify avoided downtime. Use the confidence inputs to dial the savings down if estimates feel optimistic.
We don't collect or store any data on our servers - everything stays in your browser.
Inputs
Assumptions
Update inputs to reflect your remediation plan. Confidence percentages scale the savings before ROI is calculated.
All-in cost to repay the targeted debt (engineering time, tooling, migrations).
Productivity uplift
Estimate reclaimed delivery time once debt friction is removed.
Confirm with finance so benefits, taxes, and tooling costs are captured in this hourly cost.
100% keeps the full benefit. Drop to 50-70% when pitching a conservative business case.
Hours saved Ă— engineers Ă— loaded rate Ă— 4.33 weeks/month Ă— confidence factor.
Incident reduction
Quantify avoided downtime or severity-1 firefighting.
Benchmarks span roughly $50k-$500k per sev-1. Start near $100k for SaaS outages and scale with revenue exposure.
Keep this modest (40-70%) until you have historical data supporting larger drops.
Per-quarter reduction Ă— incident cost Ă· 3 months Ă— confidence factor.
How to estimate cost per incident
- Revenue impact: revenue touched Ă— % impact Ă— duration.
- People cost: on-call/overtime + hours spent Ă— loaded hourly rate.
- Customer fallout: refunds, SLA credits, churned accounts.
- Penalties/compliance: regulatory fines or contractual breaches.
Have no data yet? Start with industry studies like PagerDuty's 2024 median (~$794k per major incident) and scale it to your context.
To scale it, compare your annual revenue or number of critical customers against the study sample and adjust proportionally.
Most teams model 12-24 months; extend if the payoff arrives later or the initiative spans multiple phases.
Optional. We only use it to convert future savings into today's dollars (net present value). Once you have finance's target, that NPV line shows whether the proposal clears it.
Outputs
ROI Summary
Results incorporate your confidence adjustments. Use them to build the business case, but accompany with qualitative risk narratives.
Monthly savings
$13,177
Productivity: $4,011
Incidents: $9,167
Annualised savings
$158,128
ROI over 12 months
31.8%
Payback period
9.1 months
Net cash flow (12 months)
$38,128
Net Present Value
$31,709
How to interpret
- Monthly savings aggregates the productivity and incident gains. Use the split above to explain where the dollars come from and sanity-check the confidence percentages if the total feels aggressive.
- ROI compares the net gain over the analysis window to what you spend upfront. Positive percentages mean the initiative pays for itself within the selected horizon.
- Payback shows when the investment recovers in nominal terms. If it exceeds the horizon, extend your analysis or revisit inputs.
- Discount rate keeps this model aligned with finance once they share their hurdle/discount rate. Until then, treat ROI and payback as directional and update the field when you get their number.
- Net present value (NPV) shows whether the proposal beats that hurdle. Positive numbers mean the savings exceed finance's required return; negative numbers signal you need more impact or a smaller investment.
This calculator keeps ROI conversations grounded. Capture the hours you expect to win back, estimate avoided incidents, dial the confidence percentages down to stay conservative, and surface the breakeven month alongside plain-language savings. Everything runs in your browser - try a scenario, share the link, and tell us what to build next.
Translate remediation work into finance-ready ROI
Engineering leaders are often asked, "When does the tech debt payback start showing up in real savings?" This calculator turns reclaimed engineering hours into monthly dollars, layers in avoided incident costs, and highlights the breakeven month in plain language. Confidence inputs let you haircut optimistic assumptions before finance asks.
The productivity lever draws on Digkas et al. 2020 for evidence that cleaner code reduces rework, while the incident side references PagerDuty's 2024 cost-of-outage study so you start with defensible numbers instead of gut feel.
Quick refresher
Return on investment (ROI) asks, "How many dollars do we keep after we pay ourselves back?" Take the net savings over the window you care about and divide by the upfront spend.
Example: invest $120k in remediation and unlock $15k/month in savings for a year. You recover the spend in eight months, and the 12-month ROI is (180k - 120k) Ă· 120k = 50%.
Net present value (NPV) converts those future savings into today's dollars using the discount rate you enter. In the example above, using an 8% annual rate yields an NPV of roughly $53k, meaning the initiative beats finance's hurdle by that amount.
Sample scenario: untangling a legacy payment core
Load the sample data to explore a realistic migration project. A $185k engineering spend reduces weekly toil by 2.8 hours for 14 engineers (backed by cleaner code practices) and cuts 0.6 severity-one incidents per quarter. After applying cautious confidence discounts, you still unlock roughly $ 52k in monthly savings - about $38k from avoided incidents and $14k from reclaimed focus time - reach payback in under five and a half months, and stay cash-flow positive for the rest of the horizon.
We use $320k as the cost-per-incident assumption here - roughly half of PagerDuty's 2024 median - to show how you can scale the dollar impact to your own environment. Adjust the horizon to test different planning windows; 15 months captures the stabilisation period observed by Lenarduzzi et al. 2020 once microservices settle and debt growth slows.
Keep assumptions defensible and revisitable
ROI models age quickly. We don't store your data - keep snapshots locally and revisit them as assumptions change. If velocity gains plateau or incident reductions stall, update the hours, headcount, or cost-per-incident figures. This mirrors the component-level measurement approach from Paudel et al. 2024, who show that debt impact varies across modules. Treat the model as a living artefact, not a one-off justification slide.
Confidence fields make the caution explicit - no more hidden "gut feel" adjustments during exec reviews.
Citations
- Digkas et al. - Can Clean New Code Reduce Technical Debt Density? (2020)
Evidence that enforcing clean-code policies reduces recurring rework - used for productivity assumptions.
- Lenarduzzi et al. - Does Migrating a Monolithic System to Microservices Decrease Technical Debt? (2020)
Longitudinal case study showing remediation investment slows debt growth after the stabilisation period.
- Paudel et al. - Towards Measuring the Impact of Technical Debt on Lead Time (2024)
Industrial evidence that debt impact varies by component - informing our recommendation to revisit inputs regularly.
- PagerDuty - The Cost of an Outage (2024)
Non-peer-reviewed but widely cited benchmark for incident cost assumptions.
Related reading
- Technical Debt Ratio Calculator
Establish a baseline remediation-to-development ratio before you model ROI scenarios.
- Tech Debt Cost Calculator
Quantify maintenance spend using Stripe's Developer Coefficient to feed into ROI discussions.
- Engineering Metrics Simulator
Stress-test productivity and incident scenarios alongside your ROI model.
Frequently Asked Questions
Questions we hear from teams evaluating this tool for their roadmap and estimation workflow.
Where do the productivity gains come from?
Use observed waste removal (e.g., fewer context switches, less rework) informed by studies like Digkas et al. 2020. If you do not have hard data, start with small hour-per-engineer assumptions and keep the confidence percentage conservative.
How should we estimate incident costs?
Combine customer-impact metrics (lost revenue, support load) with downtime cost benchmarks. PagerDuty's 2024 study reports a median $794k per severe incident - adjust for your business size and risk appetite, then discount via the confidence percentage.
How do I share a scenario with stakeholders?
Use the Share scenario button above the calculator to copy a link with your inputs encoded. Drop that link into your deck or chat thread so finance reviews the exact same numbers.
How often should we revisit the model?
Update the inputs whenever roadmap priorities or actuals shift—quarterly is a good cadence. Refresh the hours, headcount, incident assumptions, and confidence percentages so the ROI stays aligned with reality.
What discount rate should I use?
Ask finance what annual return they expect from investments. They may call it a hurdle rate or cost of capital. If you don't have a number yet, leave it at 0% (NPV will then match the net cash flow) or use a simple placeholder like 8% until finance provides their target.
Will this integrate with ScopeCone's roadmap tooling?
That's the goal. We're validating the model and UX here before wiring it into the product. Send feedback so we can sharpen the assumptions that matter most.
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