ROI Calculator

Engineering teams frequently miss opportunities to frame the impact of their work in economic terms. The ROI Calculator turns gut-feel technical investments into dollar-denominated business cases.

Overview

Most engineering improvements start as “we should really fix this.” The problem isn’t the instinct; it’s the framing. Without a clear economic case, technical investments compete poorly against feature work for roadmap space. This calculator gives you the back-of-the-envelope math to change that conversation.

The formula is simple: take the hourly cost of an engineer (W), multiply by the time spent on a toilsome activity each time it occurs (T), multiply by how often it happens per year (F), and you have the Annual Cost of Toil. Compare that against the one-time cost of fixing it, and you have your ROI.

Inspired by the XKCD “Is It Worth the Time?” chart, which visualizes the breakeven point for automating routine tasks. The ROI Calculator extends that thinking by adding explicit dollar framing so you can present the case to stakeholders who think in budgets, not engineer-hours.

When inputs are uncertain, toggle range mode to enter low and high estimates. This is usually more honest than false precision and produces a best-case/worst-case ROI range that’s more persuasive than a single number.

Connecting to Outcomes

ROI makes the economic case, but pairing it with outcome-based framing makes the case concrete and human. Instead of “this saves $250K,” say “this reduces deployment lead time from 2 hours to 10 minutes, saving the team $250K annually.” The Outcome-Based Roadmaps workshop teaches exactly this kind of framing and is a natural complement to the Technical Investment workshop where this calculator originates.

Engineering metrics like DORA Metrics provide the “before and after” measurements that make ROI cases credible. An ROI projection paired with a baseline DORA measurement and a target gives leadership confidence that the investment will actually deliver.

A Worked Example

Take the most common case: a deploy that still needs a human. Load Eliminating Manual Deploys and do the math in your head first. An engineer at $100 an hour spends 5 hours babysitting each release, and you ship 500 times a year. That’s $100 × 5 × 500 = $250,000 of annual toil. The fix runs 20 engineer-hours plus $2,000 in tooling, about $4,000 all in. Two hundred fifty grand of recurring cost against a four-thousand-dollar one-time spend.

A 6,150% first-year ROI isn’t a number you argue about. It’s a number that ends the meeting. The dollar framing isn’t there for precision. It’s there because “we should automate deploys” and “automating deploys returns 60x in year one” get very different reactions from the person holding the budget.

Now stop pretending you know the inputs. You don’t. The hourly rate is a guess, the frequency drifts, and time-per-occurrence depends on who’s on call. Load Reducing Incident Triage Time, which enters low and high estimates instead of false-precision single values.

Read the range, not the midpoint. Worst case, incident tooling barely breaks even at a 15% return that a cheaper alternative could beat. Best case, it returns better than 5x. That spread is the honest answer, and it reframes the conversation from “is this worth it” to “which end of the range do we believe, and what would move us up it.” A single invented number hides that question. A range forces you to answer it.

The calculator won’t tell you whether your estimates are any good. It makes the economics of the guess legible. And once a stakeholder has seen $250K of toil sitting on a slide, “we’re too busy to automate” stops being a defense.

Resources

• Randall Munroe, “Is It Worth the Time?” (XKCD, 2013)
• Technical Debt — the broader framework for classifying and prioritizing technical investments
• Discover-Option-Action Cycle — framing investments as testable options rather than open-ended cleanup
• Outcomes Over Outputs — why framing impact as outcomes matters more than listing outputs
• DORA Metrics — engineering metrics that provide before/after evidence for ROI cases