Step 1: the baseline
Before switching anything on, measure the current workflow for two to four weeks: volume, time per task, error rate, and any customer measure affected (response time, satisfaction).
Step 2: all the costs
- Tool subscriptions and usage charges.
- Set-up and integration work.
- Staff time for training and reviewing outputs.
- Ongoing oversight and maintenance.
Step 3: the benefits
| Benefit | How to measure |
|---|---|
| Time saved | (Old time − new time) × volume × hourly cost |
| Quality | Error rate, rework, complaints |
| Speed | Response or turnaround time |
| Revenue effects | Conversion or retention changes you can reasonably attribute |
Step 4: decide with pre-agreed rules
Write down before the pilot: “We’ll scale if we save at least X hours a month with no drop in quality. We’ll stop if errors rise above Y.” This prevents pilots that never end.
From our work: [An AI pilot PURSHO measured: baseline, costs, results and the scale-or-stop decision]
Common mistakes
- Counting time saved that isn’t used for anything valuable.
- Ignoring the time people spend checking outputs.
- Measuring only the first week, when novelty inflates results.
We design pilots and measures in our AI and automation consulting.
How PURSHO approaches this
See how we help with this in AI & Automation Consulting, or book a free 30-minute consultation. Related case study: [Industry] distributor going online.
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