An MDM readiness assessment is a structured self-check that scores your organization's preparedness for master data management across five areas: strategy and sponsorship, governance and ownership, data, technology and integration, and people and change. It turns a vague "are we ready?" into a prioritized list of gaps to close before and during implementation.
Use this free, 25-question checklist to score your readiness for a master data management program. It reflects the factors that most often decide whether a program delivers value or stalls, as described in our implementation roadmap. It is platform-neutral and works whether you are evaluating Profisee or another platform.
How to use it
- Pick the domain you are considering first (customer, product, supplier, location or asset).
- Score each statement: 0 = not in place, 1 = partly in place, 2 = fully in place.
- Ideally have a business owner and an IT lead score it separately, then compare answers. Disagreements are findings too.
- Add up each section (maximum 10) and the total (maximum 50), then read the interpretation below.
Print this checklist and complete it with your team.
The checklist
Strategy & sponsorship
| # | Statement | Score (0–2) |
|---|---|---|
| 1 | We have a named executive sponsor for master data management. | ☐ 0 ☐ 1 ☐ 2 |
| 2 | We have identified the first domain (e.g., customer, product, supplier) and why it matters. | ☐ 0 ☐ 1 ☐ 2 |
| 3 | We have a measurable objective and a baseline for that domain. | ☐ 0 ☐ 1 ☐ 2 |
| 4 | Funding is approved or a business case is in progress. | ☐ 0 ☐ 1 ☐ 2 |
| 5 | The program is aligned with current initiatives (ERP, cloud, analytics, AI). | ☐ 0 ☐ 1 ☐ 2 |
Governance & ownership
| # | Statement | Score (0–2) |
|---|---|---|
| 6 | A business data owner is named for the first domain. | ☐ 0 ☐ 1 ☐ 2 |
| 7 | Data stewards are identified and have time allocated. | ☐ 0 ☐ 1 ☐ 2 |
| 8 | Critical attributes and data standards are documented. | ☐ 0 ☐ 1 ☐ 2 |
| 9 | Decision rights (who can create, change or retire records) are agreed. | ☐ 0 ☐ 1 ☐ 2 |
| 10 | There is a process to resolve definition disputes between departments. | ☐ 0 ☐ 1 ☐ 2 |
Data
| # | Statement | Score (0–2) |
|---|---|---|
| 11 | We know every system that creates or changes this master data. | ☐ 0 ☐ 1 ☐ 2 |
| 12 | We have profiled duplicates, completeness and format issues. | ☐ 0 ☐ 1 ☐ 2 |
| 13 | We know which source is most trusted for each key attribute. | ☐ 0 ☐ 1 ☐ 2 |
| 14 | Unique identifiers (e.g., tax ID, DUNS, GTIN) exist for at least part of the data. | ☐ 0 ☐ 1 ☐ 2 |
| 15 | Reference data (codes, units, classifications) is managed consistently. | ☐ 0 ☐ 1 ☐ 2 |
Technology & integration
| # | Statement | Score (0–2) |
|---|---|---|
| 16 | Source systems can export or expose the data (APIs, extracts, connectors). | ☐ 0 ☐ 1 ☐ 2 |
| 17 | Downstream systems that should consume golden records are identified. | ☐ 0 ☐ 1 ☐ 2 |
| 18 | We have an integration platform (e.g., Azure Data Factory, Fabric, iPaaS). | ☐ 0 ☐ 1 ☐ 2 |
| 19 | Security, identity and data-residency requirements are known. | ☐ 0 ☐ 1 ☐ 2 |
| 20 | We have shortlisted or selected a master data management platform. | ☐ 0 ☐ 1 ☐ 2 |
People & change
| # | Statement | Score (0–2) |
|---|---|---|
| 21 | Business users affected by the change are identified. | ☐ 0 ☐ 1 ☐ 2 |
| 22 | There is capacity for testing and match-rule reviews. | ☐ 0 ☐ 1 ☐ 2 |
| 23 | Training and support after go-live are planned. | ☐ 0 ☐ 1 ☐ 2 |
| 24 | Success will be reported to leadership on a regular cadence. | ☐ 0 ☐ 1 ☐ 2 |
| 25 | Lessons from previous data initiatives are documented. | ☐ 0 ☐ 1 ☐ 2 |
Interpreting your score
| Total score | Readiness | Recommended next step |
|---|---|---|
| 0–19 | Early | Focus on sponsorship, a single domain and named owners. Profile data before choosing a platform. |
| 20–34 | Developing | Close the lowest-scoring section first; you can start design work in parallel. |
| 35–44 | Ready | Proceed to detailed design and match/survivorship planning for the first domain. |
| 45–50 | Advanced | Plan the next domain and strengthen automation, metrics and integration back to sources. |
Also look at section scores. Any section at 4 or below is a likely risk, whatever the total. Pay particular attention to Governance & ownership and Technology & integration: without named owners or a path to publish golden records back to systems, a program struggles even when the other areas score well.
What a full assessment adds
The self-check gives a direction. A facilitated assessment by our master data management consultants adds stakeholder interviews, data profiling on your real records, a source-system and integration map, and a phased plan with effort ranges. Woven Measure uses Check-It, its own assessment platform, internally.
Contact us to discuss your results. Email customers@wovenmeasure.com or call +1 (833) 33-WOVEN.
Frequently asked questions
What is an MDM readiness assessment?
A master data management readiness assessment scores how prepared your organization is to start or expand an MDM program, across strategy, governance, data, technology and people, and identifies the gaps to close first.
How long does the self-assessment take?
About 15–20 minutes if you know your data landscape. It is most useful when completed separately by a business owner and an IT lead, then compared.
What should we do with a low score?
A low score is not a reason to delay. It tells you what to fix in the first phase, usually naming owners, profiling data and narrowing scope to one domain.
Can someone help us interpret the results?
Yes. Contact Woven Measure at customers@wovenmeasure.com or +1 (833) 33-WOVEN to discuss your results and next steps.
Related guides and services
Related Woven Measure products
Check-It runs scored assessments and audits; we use Check-It internally. Praxis Point brings structure, lineage and governance to your data ecosystem. Secur-A-Suite provides encrypted collaboration spaces for sensitive project work.