# Master Data Management Maturity Self-Assessment for ERP Teams > Source: https://netray.co/tools/master-data-maturity-self-assessment > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Free Tools ## Short answer Ten questions that place your master data practice on a maturity scale and suggest the next steps. ## Category erp-operations ## Audience - MDM analyst - Data governance lead - ERP admin - CIO ## Tool **Kind:** assessment **Questions:** #### Who owns each master data domain (item, vendor, customer, BOM)? **Help:** Ownership means someone accountable for quality, not only someone who has system access. **Options:** ##### Nobody, whoever needs it creates it **Score:** 0 ##### IT looks after it by default **Score:** 1 ##### Business owners exist for some domains **Score:** 3 ##### Named owner and steward for every domain **Score:** 4 #### How are new master records requested and approved? **Options:** ##### Users create records directly in the ERP **Score:** 0 ##### Email requests to a central person **Score:** 1 ##### Standard form with approval for key domains **Score:** 3 ##### Workflow with validation, approval and audit trail for all domains **Score:** 4 #### Do you have written naming and numbering standards? **Options:** ##### No standards **Score:** 0 ##### Informal habits that differ by team **Score:** 1 ##### Documented standards, partly followed **Score:** 3 ##### Documented, enforced by system validation **Score:** 4 #### How do you detect duplicate records? **Options:** ##### We find them when something goes wrong **Score:** 0 ##### Occasional manual search **Score:** 1 ##### Periodic query-based duplicate checks **Score:** 3 ##### Check at creation plus scheduled scans with review queue **Score:** 4 #### How is data quality measured? **Options:** ##### It is not measured **Score:** 0 ##### One-off cleanup projects only **Score:** 1 ##### Some metrics reported occasionally **Score:** 3 ##### Defined rules, targets and a monthly scorecard **Score:** 4 #### How are changes to existing master data controlled? **Options:** ##### Anyone with access can change anything **Score:** 0 ##### Restricted by role but not logged or reviewed **Score:** 1 ##### Change logs kept and reviewed for sensitive fields **Score:** 3 ##### Approval workflow and periodic audit of changes **Score:** 4 #### How do you handle obsolete and inactive records? **Options:** ##### Nothing is ever deactivated **Score:** 0 ##### Cleanup happens before major projects **Score:** 1 ##### Annual review of inactive records **Score:** 3 ##### Rule-based lifecycle with automated flags and blocking **Score:** 4 #### How consistent is master data across systems (ERP, PLM, CRM, MES)? **Options:** ##### Each system has its own versions **Score:** 0 ##### Manual re-keying between systems **Score:** 1 ##### Interfaces for key objects, with reconciliation gaps **Score:** 3 ##### Defined system of record per domain and monitored synchronisation **Score:** 4 #### Is there a governance forum with authority to decide standards? **Options:** ##### No forum **Score:** 0 ##### Ad hoc meetings when problems appear **Score:** 1 ##### Regular meetings but limited authority **Score:** 3 ##### Governance council with charter, RACI and executive sponsor **Score:** 4 #### How trained are the people who create and maintain master data? **Options:** ##### No training **Score:** 0 ##### Learned on the job **Score:** 1 ##### Training at onboarding **Score:** 3 ##### Role-based training, guides and periodic refreshers **Score:** 4 **Bands:** #### Reactive **Min:** 0 **Max:** 29 **Verdict:** Master data is managed by habit, and problems are found when transactions fail. **Recommendations:** - Name an owner for each master data domain before anything else - Introduce a request form with mandatory fields for vendors and items - Run a one-off duplicate and completeness scan to size the problem - Restrict who can create and change records #### Emerging **Min:** 30 **Max:** 54 **Verdict:** Some standards and owners exist, but they are not consistently enforced or measured. **Recommendations:** - Write down naming and numbering standards and publish them - Define five to ten data quality rules and measure them monthly - Add duplicate checks at record creation - Set up a small governance group that meets regularly #### Managed **Min:** 55 **Max:** 79 **Verdict:** Governance and measurement are in place, with room to automate enforcement and cross-system consistency. **Recommendations:** - Move approvals into a workflow with an audit trail - Automate scheduled quality scans with a steward review queue - Define the system of record for each domain and monitor synchronisation - Add lifecycle rules for inactive and obsolete records #### Optimised **Min:** 80 **Max:** 100 **Verdict:** Master data is governed, measured and mostly enforced by the system. **Recommendations:** - Review targets annually and raise them where defects are low - Use quality metrics in supplier and customer onboarding decisions - Extend governance to new domains such as assets and contracts - Share practices across plants and business units ## Content **Intro:** Master data management is less about software than about ownership, standards and discipline. This ten question self-assessment places your practice on a four-level maturity scale and gives concrete next steps, using plain questions an ERP team can answer in ten minutes. **Sections:** #### How to use the assessment **Body:** Answer each question for your organisation as it works today, not as it is documented. Involve at least one business user and one IT person, because they often answer differently. The questions cover ownership, request and approval, standards, duplicate control, measurement, change control, lifecycle, cross-system consistency, governance and training. Your score is shown as a percentage of the maximum and mapped to one of four bands. Repeat the assessment every six months to see progress. #### The maturity scale **Body:** The four bands follow a common pattern in data governance maturity models. Reactive organisations fix data after it breaks. Emerging ones have started to set standards and owners. Managed organisations measure quality and control changes through workflow. Optimised organisations enforce rules in the system and review targets continuously. The scale is deliberately simple: it is meant to start a conversation and select priorities, not to rate you against a formal certification. **Bullets:** - Reactive: no owners, no measurement - Emerging: standards exist but are not enforced - Managed: workflow, metrics and audit trail - Optimised: enforced, automated and continuously improved #### Interpreting the result **Body:** Look at individual answers as well as the total. A company can score well on tooling and still have no owners, which rarely lasts. If ownership and governance questions score lowest, start there, since software will not fix unclear accountability. If measurement scores lowest, begin with a handful of automated checks. Use the recommendations under your band as a first ninety-day plan, and share the result with leadership to secure sponsorship for the data owners. #### Common mistakes **Body:** Do not answer aspirationally. A policy that nobody follows is a one, not a four. Do not buy an MDM platform before ownership and standards are settled; the tool will only automate confusion. Do not try to govern every domain at once: choose the one with the highest business pain, usually vendor or item, and prove value there. And do not treat the assessment as a one-time exercise; maturity decays without continuing attention. **Cta:** If you want an outside view on your results, our team can walk through the assessment with you and suggest a practical first ninety days. **Faq:** #### Do I need an MDM software platform? **Answer:** Not at first. Many organisations improve a great deal with clear ownership, request forms, standards and scheduled queries inside the ERP. A dedicated MDM platform helps when you have many systems that must stay consistent. #### How often should I repeat the assessment? **Answer:** Every six months is a good rhythm. It is short enough to track progress after changes and long enough for new practices to show up in the answers. Compare the trend per question rather than only the total. #### Which domain should I govern first? **Answer:** Start where bad data costs the most or is easiest to see, often vendor master because of payment risk, or item master because of its effect on purchasing and planning. Prove the approach, then extend it. #### Is this an official maturity model? **Answer:** No. It is a practical self-check modelled on common data governance maturity ideas. It is not tied to a certification or a vendor framework, and the scoring is for internal comparison. ## Search terms master data management maturity assessment, mdm maturity model, data governance maturity self assessment, master data readiness score, erp data governance assessment, data stewardship maturity, mdm health check --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json