Automation without a yardstick ends in opinion. “It feels faster” is not evidence for further investment. “The team finds it difficult” is equally insufficient reason to stop.
Choose one primary KPI in advance that best captures the operational pain. Add two or three supporting KPIs to understand why the result is or is not being achieved.
Choose one primary KPI
The primary KPI must be directly connected to the problem you want to solve.
For order processing, this could be processing time per order. For product data, it could be the percentage of complete product records. For procurement matching, it could be handling time per price list.
Also agree on what constitutes a meaningful improvement. Not as a general promise, but for this workflow, with this baseline and these people.
Six KPIs that help in practice
1. Processing time per item
Measure the active handling time per order, quote, invoice or product update. Define whether waiting time is included.
2. First-time-right rate
Measure the percentage processed correctly the first time, without later rework. Define in advance what “correct” means.
3. Cost per item
Add labour time and average recovery costs, then divide by the processed volume. Use the same cost basis before and after automation.
4. Lead time
Measure the time from receipt until the next step or customer confirmation is ready. This is often the KPI the customer notices first.
5. Exception rate
Measure the percentage sent to an employee. A lower rate is not automatically better. Human review may be exactly what is intended for high-risk or unusual work. Determine in advance which exceptions are justified and which are caused by poor data or unclear rules.
6. Adoption in the daily process
Measure the proportion of total volume that follows the new way of working. A technically functioning agent only delivers results when the team uses it and follows the agreed workflow.
Create a reliable baseline
Use the same items before and after the change:
- definition;
- data source;
- selection of orders or transactions;
- person responsible for measurement;
- method for recording exceptions.
Measure across a representative set that includes busy periods and unusual cases. A selection containing only simple orders creates an overly positive picture.
Measure corrections, but do not draw conclusions too quickly
Many corrections can point to poor recognition, unclear data or an overly broad scope. Few corrections can also mean employees are not checking the output carefully enough.
Do not only look at the number of corrections. Also examine:
- which corrections recur;
- which source data cause the problem;
- whether employees understand when to intervene;
- whether the controls fit the risk of the workflow.
What evidence looked like at INSPIRED
At INSPIRED Pet Nutrition, the business case focused on processing time and processing costs per order. In this specific workflow, order processing became 9 times faster and processing costs fell by 60 to 80 per cent. A working solution was live within six weeks.
These figures belong to INSPIRED’s workflow, baseline and systems. New clients receive their own measurement framework. Read the INSPIRED case.
From measurement to an evidence-based decision
In the free 30-minute conversation, we assess whether a workflow has enough volume, repetition and ownership.
During the paid Prove session, we then investigate the current situation, exceptions, data, systems and the outcome that matters. The result is to build, improve the prerequisites first, or not proceed.
A concrete build plan only follows after a positive build decision. After delivery, KPIs remain necessary for management and focused improvement.