Automate processes: selection matrix for the first use case
By Kevin Kröger, Geschäftsführer, Software und Plattformbetrieb
A good first case of automation occurs frequently, follows mostly clear rules, has reliable inputs, has testable output, and has limited consequences for errors. Benefits, exception rates, integration effort and operational responsibility should be assessed together.
Which criteria belong in the selection matrix?
Evaluate frequency, current processing time, standardizability, data quality, number of exceptions, consequences of errors and necessary system access. A high amount of time alone does not make a process suitable. Many unclear decisions or poor input data can increase the automation effort more than the visible manual step.
How is benefit measured without invented savings?
Record the number of cases, lead times, rework and typical errors in advance with a clear time frame. Then define a success signal, such as fewer transmission errors or a shorter time until the technical test. Don't use a blanket percentage. The pilot must be measured against the actual baseline and including human control.
When should the use case be deferred?
Revert if ownership, rules, data access, or error handling are unclear. The same applies if a rare exception has serious consequences and is not reliably recognized. It often makes sense to first simplify the process or improve data quality. Software and AI components are only then selected to suit the remaining task.
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Frequently asked questions
- Should the most time-consuming process be automated first?
- Not automatically. A slightly smaller, clearer and measurable process can deliver actionable insights more quickly and create less operational risk.
- Does process automation always need AI?
- No. Clear rules, interfaces and classic software are often more predictable. AI makes sense when unstructured input or linguistic evaluation plays a limited, measurable role.