We want to deploy an AI agent to forecast material shortages and automate purchase orders, but our ERP contains phantom inventory counts, duplicate part numbers, and outdated vendor lead times. What data hygiene work must we complete first?

Question

Tyler Smith · Accepted Answer

Connecting an AI agent to a corrupted ERP is operational suicide. If your underlying inventory counts, vendor lead times, and part catalogues are filled with legacy errors, the algorithm will execute wrong purchase orders at machine speed, draining your cash flow and jamming warehouse space with unusable stock.

Before writing a single prompt or workflow integration, establish three non-negotiable hygiene protocols:

- Execute a physical wall-to-wall inventory audit. You must reconcile actual physical stock with ERP balances down to ninety-five percent accuracy. Any system dependent automation requires trusted baseline numbers.

- Cleanse the part catalogue. Consolidate duplicate stock keeping units, purge obsolete legacy codes, and standardize the naming architecture across all raw materials and sub-assemblies. Eliminate any item that lacks a defined unit of measure or verified minimum reorder point.

- Re-verify supplier master records. Contact your top twenty percent of suppliers by spend and establish exact current lead times, minimum order quantities, tiered pricing schedules, and active purchasing contacts. Remove legacy vendors that have been inactive for over eighteen months.

Once this data foundation is verified, assign ownership of master data changes on your Accountability Chart. Master data updates cannot be open to every warehouse clerk. Only after your data reflects operational reality can an autonomous agent accurately calculate consumption curves, identify real shortages, and draft accurate purchase orders for human review.