Annual team cost
$3,750,000
Team size × fully loaded salary.
Maintenance budget (est.)
$1,237,500
Assumes 33% time spent on maintenance/toil (Stripe 2018).
Potential annual savings
$694,238
Annual maintenance budget × blended improvement ratio from the cited studies.
Projected DORA outcomes with these inputs: cycle time drops to 1.8 days, deployment frequency climbs to 6 releases per week, MTTR improves to 2.2 hours, and change failure rate falls to 5.0%. Use this snapshot to compare scenarios before committing to larger DevOps investments.
Inputs reflect your environment
Team size, compensation, and current delivery metrics stay local to your browser. Change them to match your reality and see how the research scales.
Improvement ratios come straight from citations
Wilkes et al. (ICSME 2023): cycle time 3.2 → 1.8 days (–43.8%), MTTR 6.5 → 2.2 hours (–66.2%). Rüegger et al. (ICSSP 2024): deployments 0.7 → 2.1 per week (+200%), change failure 12% → 5% (–58.3%). Internal calculations reuse those exact deltas.
Want the full research context? Read our evidence summary in the Engineering Metrics: A Pragmatic Analysis of What We Actually Know.
ROI is a blended proxy
Savings estimate = annual maintenance budget × blended improvement ratio. Maintenance share defaults to 33% (Stripe Developer Coefficient 2018) and the failure-rate baseline is the 12% reported in the ICSSP study. This is not a business case—just a directional gauge for internal review.
All data stays on this page
The simulator runs entirely in your browser—no form submissions, storage, or analytics hooks yet. We collect feedback manually once you volunteer an email.
| Study | Finding | Metric |
|---|---|---|
| A Framework for Automating the Measurement of DevOps Research and Assessment (DORA) Metrics | Automated CI/CD adoption across 304 open source projects reduced median cycle time from 3.2 days to 1.8 days (-43.8%). | cycle time |
| A Framework for Automating the Measurement of DevOps Research and Assessment (DORA) Metrics | Incident response automation in the same CI/CD rollout cut median MTTR from 6.5 hours to 2.2 hours (-66.2%). | mean time to recovery |
| Fully Automated DORA Metrics Measurement for Continuous Improvement | Automated DevOps tooling integration increased deployment frequency from 0.7 to 2.1 releases per week (+200%) across 37 production microservices. | deployment frequency |
| Fully Automated DORA Metrics Measurement for Continuous Improvement | In the same DevOps tooling rollout, change failure rate decreased from 12% to 5% (-58.3%). | change failure rate |
What makes this simulator different
We’re grounding every improvement number in a citation, run entirely client-side, and treating the ROI as a directional heuristic—not a promise.
Evidence-first defaults
Improvement ratios map directly to Wilkes et al. (ICSME 2023) and Rüegger et al. (ICSSP 2024). We call out assumptions and give you the source links in the interface.
Client-side experiment
Everything runs in your browser—no backend, no data collection. We just want feedback on whether the math and presentation resonate before we invest in APIs.
No magic numbers
We’re honest about uncertainty. Savings are directional and explicitly tied to the improvement ratios—no hidden multipliers or aggressive ROI claims.
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