Training ROI Calculator: Prove the Number Leadership Can't Poke Holes In
Turn a training program's full cost and one measurable business metric into a defensible, conservative ROI summary — with every attribution assumption shown and your L&D manager approving the model before the number is finalized.
A logged-in tool where you enter training costs, a chosen business metric with before/after values, and your attribution assumptions, then get a conservative ROI summary with a sensitivity range — approved by you before it's finalized and exportable as CSV.
Before you start
- A free Vercel account
- A free Supabase account
- A free Resend account (optional, for emailed summaries)
- Your program cost components and one before/after business metric (a spreadsheet is fine)
The problem this kills
You ran the training. It went well. Now finance wants a number — "what did we get back for that spend?" — and you're staring at a blank slide.
So you reach for a single magic figure. "Training delivered 312% ROI!" Then the CFO asks one question — "how much of that improvement was actually the training, versus the new manager, the pricing change, and the season?" — and the whole number collapses. Because you claimed 100% of the change, and everyone in the room knows training rarely causes 100% of anything.
The honest version is harder and far more convincing: total up every real cost, pick one metric you measured before and after, state plainly how much of the change you're willing to attribute to the training, and show a range instead of a single fragile number. That's the difference between a number that gets challenged and a number that gets believed. The problem is that building it defensibly — with the assumptions visible and the math owned — takes a tool, and you don't have one.
What you'll build
A small, private web app — just for you and your L&D team — that turns cost inputs and one before/after metric into an ROI model you can defend in a room full of skeptics:
- Enter the full cost. Delivery, facilitator time, materials, software, and the participants' time off the floor — all the pieces, not just the invoice.
- Pick one metric you actually measured. Reduced errors, faster ramp, lower turnover, higher sales — with its before value, after value, and what one unit of it is worth.
- State your attribution honestly. A plain percentage saying how much of the change you credit to the training — never 100% by default.
- Get a range, not a magic number. A conservative, expected, and optimistic ROI so the figure survives a challenge.
- Own it before it ships. You review the costs, the metric, and the assumptions and approve the model before the ROI is finalized — the math is owned, not hand-waved.
- Export clean. A CSV of the whole model and every input, ready to paste into a board deck or hand to finance.
What's inside the Implementation Plan
A complete, step-by-step runbook you paste into an AI coding agent (Claude Code) — written for a non-coder. You don't write the code; the agent does, and you guide it.
It opens by interviewing you about your business. Before a single line is built, the plan has the agent ask how you currently estimate training value, what your loaded labor rates are, which metric you can actually measure before and after, how you think about attribution, and where your messy exceptions live. Then it reflects a short tailored spec back to you and waits for your thumbs-up — so the tool fits your programs and your numbers, not a generic template.
From there it walks through every step: setting up the database, login, the cost and metric input screens, the conservative ROI math with a sensitivity range, the approval gate, the emailed summary, and the CSV export. Every build step ends with a ready-to-copy prompt.
The governance it includes (this is the point)
This isn't a throwaway spreadsheet. The plan builds in the controls that make the number trustworthy:
- Login so only your team can use the tool.
- Row-level security so you only ever see your own organization's models.
- A complete audit trail — who entered what, who approved, and when.
- A human approval gate — the tool drafts the ROI, but you review the costs, metric, and attribution assumptions and approve before the figure is finalized and presented.
- Duplicate guards so the same program-and-version analysis can't be saved twice.
- Conservative by design — attribution is shown plainly, never assumed at 100%, and the output is a range, not a single number you can't defend.
Who it's for
L&D and training managers who are asked to justify training investment with real numbers — and who'd rather present a defensible, conservative figure they own than a flashy one that falls apart under the first hard question.
You've got this — paste the first prompt and let the agent interview you.