What Data to Clean Before Implementing AP Automation

1. Vendor master: remove duplicates, retire stale vendors, fill missing details. 2. Chart of accounts: retire unused accounts, fix labels and structure. 3. Dimensions and entities: update departments, projects, and entity lists. 4. Open POs: close completed orders, resolve mismatches. 5. Approval matrix: confirm approvers, limits, and routing rules. 6. Open invoices: reconcile aging and in-flight items for cutover. 7. Tax and compliance: confirm vendor tax IDs and documents.

The vendor master is the highest-priority cleanup, because it drives matching, payment, and compliance. Duplicate vendor records lead to duplicate payments, stale vendors invite misdirected funds, and missing banking, tax, or compliance details cause failures and exceptions once automation starts.

Cleaning it means removing duplicates, retiring inactive vendors, and filling gaps in banking details, tax IDs, and compliance documents. A clean vendor master is what lets automation match invoices to the right vendor and pay safely from the start.

The chart of accounts, dimensions, and entities are what coding runs on. An overgrown chart of accounts with unused or mislabeled accounts, or outdated departments, projects, and entities, produces inconsistent coding and confuses both people and automated suggestions. Cleaning these gives coding a clear, current structure to work against.

Open purchase orders are the matching foundation. Stale or already-completed POs that were never closed, and POs that do not match reality, create matching exceptions as soon as automation begins. Closing completed orders and resolving mismatches before go-live keeps matching reliable rather than noisy.

The approval matrix drives routing. Outdated approvers, wrong limits, or stale rules send invoices to the wrong people the moment automation routes against them. Confirming who approves what, at which limits, and under which rules ensures the automation routes correctly from day one.

Open invoices and aging need attention for the cutover itself. Reconciling in-flight invoices and the aging picture before go-live avoids carrying a backlog of unclear items into the new system. A clean cutover starts the automation with a known, current set of open work rather than a tangle.

Stampli keeps the ERP as the system of record and mirrors its chart of accounts, entities, dimensions, vendors, approval logic, and tax rules, so the quality of that ERP data directly shapes Stampli's coding, routing, and matching. Cleaning the ERP master data before implementation is what lets Stampli start with accurate suggestions and validations.

Stampli vendor management provides a secure self-service portal where vendors submit and maintain their own banking, tax, and compliance details, which helps keep the vendor master accurate over time. Organizations can define what makes a vendor payable, so incomplete vendor data is caught rather than passed through.

Because Stampli validates against ERP rules before posting, gaps and invalid combinations in the underlying data surface early. Clean source data lets that validation confirm good invoices rather than constantly flagging problems rooted in the master data.