Your Best ERP Consultant Is 58. What Happens When They Leave?
Your best ERP consultant is 58 years old and planning to retire.
Everything they know about your system: the workarounds, the reasons behind the configuration, the tribal knowledge that keeps your operations running. It all lives in their head.
When they leave, that knowledge leaves with them. And you will pay consultants like me to figure out what your own people already knew.
The pattern repeats everywhere
I have seen this at every manufacturing company I work with. The ERP has been running for 10 or 15 years. The people who set it up are gone. Nobody remembers why certain parameters are set the way they are.
So when something breaks, it takes weeks instead of hours to fix. Not because the problem is complex. Because nobody wrote down why it was configured that way in the first place.
One client called us after a plant manager retired. We spent three weeks reverse-engineering decisions that would have taken three hours to document while he was still in the building.
Documentation does not work the way you think
The instinct is to write things down. Create a manual. Run exit interviews.
The problem is that 200-page manuals do not get read. Exit interviews capture what someone remembers under pressure in their last two weeks. Neither approach gets at the knowledge people use daily without thinking about it.
That knowledge is also never fully written down, because the person who has it does not know what they know. They just know how to solve the problem when it shows up.
What actually works
The answer is not more documentation. It is making knowledge searchable and accessible at the moment someone needs it.
This means capturing knowledge in the flow of work: during meetings, during training sessions, during troubleshooting. And then making that knowledge available through a simple search, so when the next person faces the same problem, they find the answer before they call a consultant.
We built KnowKit for exactly this problem. It captures knowledge from meetings, trainings, and your existing systems, then makes it available through a simple search connected to your ERP context.
But the underlying principle applies regardless of what tool you use: the time to capture knowledge is while the people who have it are still in the building.
The cost of waiting
Most companies start thinking about this after the problem shows up. After the retirement. After the weeks of lost productivity.
The companies I see doing this well started two or three years before any visible crisis. Not because they predicted a specific retirement, but because they understood that accumulated knowledge is a business asset that needs to be actively maintained.
This is also where the first practical AI project tends to land. In The Two AI Projects I See First at Industrial Companies I walk through why knowledge capture and process automation almost always come before any customer-facing AI work.
Start now, while the people who know your systems are still around. The cost of capturing knowledge is small. The cost of losing it is not.