Why so many pilots fizzle out
Most AI pilots do not fail because of the technology. They fail because nobody has defined what should be different at the end, who owns the result and who operates it afterwards. The demo is liked, then nothing happens.
The seven questions
- Which workflow? One, named, recurring. Not “controlling with AI” but “the monthly report for management”.
- Who owns it? One person who is responsible for the workflow today and who declares acceptance.
- Who releases the budget? Often not IT, but the person responsible for the costs of the workflow.
- Which data, which access? The sources the problem needs, read-only, with a contact person in IT.
- How do we measure? One quantity, before and after, under comparable conditions: processing time, number of corrections, usage.
- What is excluded? Write access to the ERP, personnel evaluation, machine control, undocumented legacy systems.
- How do we get back? The previous procedure remains possible until acceptance is declared.
The Pilot Check asks you these questions in two minutes.
What should remain after the pilot
Many pilots end with a demo that nobody continues. A good pilot leaves more than a result: connected data, validated terms and people who can solve the next problem themselves. This is exactly how the Onagero entry is built. How the entry works.
When a pilot should end
A pilot that misses its goal is a useful result if you stop. It should end when the permitted data does not support the question, when people do not use the tool, when the checking eats up the time savings or when the total costs exceed the agreed value. With Onagero, you decide after the measurement whether the platform keeps running.
Which workflows suit a start
Well suited are workflows that recur every week, consist of exports and manual work, and whose data is available digitally. Examples: the monthly report, the scrap analysis, the delivery date inquiry.