# Item Master Data Quality Checklist for ERP > Source: https://netray.co/tools/item-master-data-quality-checklist > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Free Tools ## Short answer A 33-point checklist for auditing item or material master records before they cause wrong MRP, wrong cost or wrong shipments. ## Category erp-operations ## Audience - ERP administrator - MDM lead - Data steward - Materials planner ## Tool **Kind:** checklist **Groups:** #### Identity and description **Items:** **Text:** Every item number is unique and follows the documented numbering rule **Critical:** true **Text:** No two active items share the same manufacturer part number and manufacturer **Critical:** true Descriptions follow one naming convention (noun first, then attributes) No test, dummy or temporary items remain active in production Long description and short description are both populated where the ERP has both Item type or material type (purchased, manufactured, phantom, service) is correct #### Units of measure **Items:** **Text:** Stock, purchase, sales and production UoM are all populated and intentional **Critical:** true **Text:** Conversion factors between UoMs are verified against the supplier pack size **Critical:** true No item uses a UoM that is not in the approved UoM list Weight and dimension fields are populated for freight-relevant items Decimal handling for each UoM is right (EA is whole, KG allows decimals) #### Planning and procurement **Items:** **Text:** Planning method (MRP, reorder point, make-to-order) is set for every active item **Critical:** true **Text:** Lead times are populated and have been reviewed in the last 12 months **Critical:** true Lot size rule, safety stock and minimum order quantity are intentional, not defaults Default supplier and approved manufacturer list exist for purchased items Make or buy flag matches how the item is actually sourced Scrap or yield percentages are set only where they are real #### Costing and finance **Items:** **Text:** Standard cost or valuation price is non-zero on every costed item **Critical:** true Costing method (standard, average, FIFO) matches policy for the item class **Text:** Inventory and COGS account determination class is correct **Critical:** true Item cost has been rolled or reviewed since the last material price change Tax class, commodity code and HS or HTS code are populated for traded items Country of origin is populated where customs or defense rules need it #### Quality, traceability and compliance **Items:** **Text:** Lot, serial or batch control flag is correct and matches the quality plan **Critical:** true Shelf life and expiry settings exist for perishable or controlled items Inspection requirement (receiving, in-process, final) is set where needed Hazmat, RoHS, REACH and export classification flags are set where applicable Revision and engineering status are consistent with PLM or the released drawing #### Lifecycle and governance **Items:** Obsolete items have an obsolete status and no open demand or supply Items with no transactions in 24 months are reviewed for deactivation Every item has a named owner or data steward Changes to critical fields go through a documented request and approval A duplicate-item scan runs on a schedule, not only at cleanup projects **Scoring Note:** Score each group as items passed over items checked. Anything below 90 percent in planning, UoM or costing deserves a fix list before the next MRP or cost roll. Critical items failing means wrong orders or wrong inventory value. ## Content **Intro:** Bad item master data is the root cause behind a surprising share of ERP complaints: MRP suggests the wrong quantity, a standard cost is zero, a pallet is received in the wrong unit. This checklist gives ERP admins and data stewards a structured way to audit item or material master records, whatever the ERP. **Sections:** #### How to use the checklist **Body:** Pull a sample of 100 to 300 active items, stratified by item class so that raw material, purchased components, assemblies and finished goods are all represented. Work down each group and tick what passes for the whole sample. For any item that fails, note the item number so it feeds your cleanup list. Run the full audit before a go-live, an upgrade or a cost roll, and a lighter version quarterly. Export the result as PDF or Excel to attach to a data governance review or audit file. #### Why these groups **Body:** The groups follow how the item record is consumed. Identity decides whether people can find and trust a record. Units of measure decide whether quantities are right when they cross purchasing, stores and production. Planning fields drive MRP. Costing fields drive inventory value and margin. Quality fields drive traceability and compliance. Governance decides whether any of it stays fixed. The critical flags mark checks where a failure usually produces a visible business error rather than a cosmetic one. **Bullets:** - Identity: duplicates and naming - UoM: conversion and decimals - Planning: lead time, lot size, planning method - Costing: cost, accounts, tax class - Quality: lot, serial, expiry, classification #### Reading your results **Body:** Treat the result as a heat map rather than a single score. A sample with strong identity but weak planning fields tells you the data was migrated carefully but never tuned. Weak governance with decent current quality means the data will drift again. Prioritize fixes by blast radius: a wrong lead time on a high-volume item hurts more than a missing description on a dormant one. Re-run the same sample after cleanup to prove the improvement. #### Common mistakes **Body:** Auditing only the fields that are easy to query leaves silent errors like wrong UoM conversion untouched. Cleaning once without an owner and a change process means the same defects return within a year. Mass-updating planning values from a spreadsheet without a test run in a non-production client is another frequent cause of self-inflicted incidents. Always check item changes with planners before loading them, because a corrected lead time can flood the buyer with new exception messages. **Cta:** If you want this audit run automatically against live ERP tables with a ranked defect list, we can build it read-only on top of your system, on-prem if needed. **Faq:** #### How many items should I sample for an item master audit? **Answer:** For a population under 5,000 active items, review 100 to 150. For larger populations, 200 to 300 stratified by item class is usually enough to see patterns. If the sample shows a defect rate above a few percent in a critical field, query the whole table for that field instead of sampling. #### Does this work for SAP material master and Infor item master? **Answer:** Yes. The checks are system neutral. Map each line to your ERP field names, for example the material type and MRP views in SAP, or the item and item-warehouse records in Infor SyteLine. The logic of identity, UoM, planning, costing and quality applies everywhere. #### What data quality score should we aim for? **Answer:** There is no universal standard. Many manufacturers aim for 98 percent or better on fields that drive MRP and costing, and accept lower on descriptive fields. Pick a target per group, publish it, and measure it at the same cadence each time. #### How often should the item master be audited? **Answer:** Run a full audit before go-live, upgrades and annual cost rolls, and a lighter automated scan monthly or quarterly. New-item requests should be validated at creation so that the audit only has to catch drift and legacy problems. ## Search terms item master data quality checklist, material master data quality checklist, item master cleanup checklist, ERP item master audit, master data quality audit template, item master validation rules, MDM checklist manufacturing, item master best practices --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json