Understanding ROI

The ROI multiplier is the headline number on your Dashboard. It tells you, in plain English, how many dollars of value you got back for every dollar spent on AI tools in the period.

A 5× ROI means: you spent $1, got $5 of value back. A 1× means you broke even. Below 1× means the tool is losing you money.

This article is the 60-second version. For the deeper methodology — including why we cap extrapolation and how we handle negative time-saved — see the blog post The 2.5× rule: why most AI ROI numbers are quietly lying to you.

The formula

ROI multiplier  =  Estimated value of hours saved  ÷  Monthly cost

Where:

• Monthly cost = (assigned users × cost per seat per month), summed across every tool that has a cost set
• Estimated value of hours saved = (estimated hours saved × your blended hourly rate)
• Estimated hours saved = the bucketed time-saved answers from your team's AI Pulse responses, with a small extrapolation factor to account for survey cadence (capped at 2.5×)

We calculate this at the org level (your dashboard headline) and at the per-tool level (the by-tool table in Reports).

A worked example

Imagine you have:

• 30 ChatGPT Team seats at AUD $30 each → $900/month cost
• 17 of those 30 users active this period (13 unused seats — worth chasing)
• 2,300 minutes of reported time saved across the period
• Blended hourly rate = $95/hr

The maths:

Reported hours    = 2300 min ÷ 60       = 38.3h
Estimated hours   = 38.3 × 2.5 (capped)  = 96h
Estimated value   = 96 × $95             = $9,120/mo
ROI multiplier    = $9,120 ÷ $900        = 10.1×

So ChatGPT is delivering about 10× ROI at this org. Nice.

How ROI becomes a health score

On your Dashboard, the ROI gauge shows two numbers: the raw multiplier (10.1× in the example above) and a health score from 0 to 100. The health score is what drives the dial colour.

The mapping isn't linear — because a 2× ROI is fine but not compelling, and a 15× ROI is nearly indistinguishable from a 20× ROI in practice. The curve is opinionated:

We cap at 20× so a single runaway tool doesn't peg every gauge to "excellent" and wash out the signal from the rest. More on normalised health scores →

Three things to be honest about

1 · It's an estimate

Self-reported time-saved is inherently optimistic. Our safeguards:

• A 2.5× cap on the extrapolation factor, so a single enthusiast can't blow up the org-wide estimate
• A negative bucket in the time-saved question ("I lost time because of it") that gets subtracted, not ignored
• We always show reported hours alongside estimated hours, so you can choose how aggressive a claim to make

2 · It excludes tools with no cost set

If you've added a tool but not set its monthly cost, it's excluded from the cost denominator. The dashboard shows you how many tools are missing cost data so you can keep that number honest.

3 · It depends on your hourly rate

The dollar value of an hour saved varies wildly by industry and seniority. If your rate is too low, ROI looks artificially weak; too high and it looks artificially strong. Pick a number you'd be comfortable defending in a board pack — see Setting your blended hourly rate.

What if it shows "—"?

Means you're missing one of the inputs. See Why is ROI showing "—"?.

Related: The 2.5× rule (blog) · Normalised health scores (blog) · Setting your blended hourly rate · Reported vs. estimated hours saved · Setting tool costs and why it matters