AuditTemplate
ROI Model Template
The structure behind our ROI modelling approach. Use this to understand how we calculate the financial case for AI investment.
Last updated: 2026-04-07
01
Current Cost Baseline
Establish the true cost of the current manual process — the foundation for calculating savings.
- •Process volume (instances per period)
- •Average time per instance
- •Total hours per period
- •Fully loaded hourly rate (salary + overheads)
- •Total cost per period
- •Error rate and rework cost
- •Opportunity cost (what else could staff do)
02
Projected Savings
Three scenarios modelling the expected savings from AI automation.
- •Conservative: minimum realistic automation rate
- •Realistic: expected automation rate based on feasibility assessment
- •Optimistic: best-case automation rate
- •Time savings per scenario
- •Cost savings per scenario
- •Quality improvement estimate (reduced errors)
03
Implementation Cost
The investment required to build and deploy the solution.
- •Consulting / development fees (phased)
- •Infrastructure costs (cloud, APIs, storage)
- •Ongoing operational costs (monitoring, maintenance)
- •Training and change management costs
- •Contingency (typically 15–20%)
04
Payback Period
How quickly the investment pays for itself under each scenario.
- •Monthly net savings (savings − ongoing costs)
- •Payback period per scenario (months)
- •12-month ROI percentage
- •24-month cumulative value
- •Break-even point
05
Sensitivity Analysis
Test how robust the ROI is when key assumptions change.
- •What if automation rate is 20% lower than expected?
- •What if implementation takes 50% longer?
- •What if volume changes (up or down 25%)?
- •What if hourly rates change?
- •Minimum viable automation rate for positive ROI
Want us to complete this for your business?
This template shows the framework. The real value is in applying it to your specific business context with expert analysis. Start with an audit and we’ll do the work for you.