Establish the baseline
ROI begins with the cost of today's process, not the tool price. Measure case volume, average handling time, fully loaded hourly cost, and errors. Separate work that disappears from time that moves into review.
Use a representative period. One busy week can inflate the benefit, while a quiet month can hide it.
A formula without magic
Monthly benefit equals saved time, fewer errors, faster cash flow, and released capacity, minus new operating costs. Payback period equals initial investment divided by conservative monthly benefit.
Investment includes discovery, development, integration, internal time, migration, and training. Operation includes licences, model/API fees, monitoring, support, and future change.
- use a conservative scenario
- subtract human-review time
- include exceptions
- do not sell the same saved minutes twice
Model calculation
A team handles 1,000 cases per month at six minutes each. Automation saves four minutes, or roughly 67 hours. At a fully loaded €25 per hour, the time benefit is €1,675 monthly. If errors fall by €400 and operation costs €275, the conservative monthly benefit is €1,800.
With an €18,000 investment, simple payback is ten months. This is an illustrative model, not a guarantee or client result.
Measure after launch
Name the metric owner and review interval before development. Compare equivalent periods and track errors, exceptions, and the experience of people operating the workflow.
Automating a poor process only creates temporary ROI. The first workflow should therefore include real-data testing, logging, and initial tuning.
Use three scenarios, not one promise
Build conservative, realistic, and optimistic cases. Vary volume, minutes genuinely removed, adoption, and operating cost. The investment should remain sensible without relying on the optimistic case.
For AI workflows, include model-price uncertainty, human review, and ongoing tuning. For conventional automation, budget for integration maintenance when external systems change their APIs.
- conservative adoption
- realistic exception cost
- monthly licences and APIs
- maintenance and change reserve