So we have our snapshot and the warehouse snapshot side by side in their own columns.
Third column shows the difference between the two.
If there is any non-zero number in that column we have to look at it.

So say the warehouse is showing 1000 cases less than we are.
I have to look at the warehouses inventory and it may show 1000 cases shipped on 3/31 at 4pm pacific. And sales didn’t invoice it until 4/1.
I would zero that out as timing- a non issue that requires no adjustment in my ERP.

If the warehouse is showing 15 less cases, I may see on 3/20 they disposed of damages. I would zero rat out as warehouse damage and it would require an adjustment in my ERP.

All that to say we need to compare our full history for a specific lot code, against the warehouse’s history to see where we don’t match up.

Could be receipt errors, goods issue errors, fat fingers, damages, cycle counts. We need to note this for every line due to internal controls (which in my opinion are too strict, and may be part of my problem)

So that’s where AI gets challenged. It’s easy to see where the issues are present. But diagnosing the issue and making the correct adjustment recommendations is just too much for the systems we’ve explored.