🔍 Master Data & Governance Readiness Self-Check

A 5-Minute Self-Check for CEOs, COOs & MDs of Mid-Market Manufacturers

Score yourself across 6 dimensions. Find out whether your data foundations are ready to support transformation — or whether they’re the hidden blocker.

⏱ 5 minutes · 6 dimensions · Instant result

This isn’t a maturity model. It’s a practical diagnostic. Score yourself honestly, and you’ll know in 5 minutes whether your next investment should be in systems, people, or the data underneath both.

Rate your organisation across 6 dimensions. For each, pick the statement that best describes where you are today.

🔴 1 point — Not in place
🟡 2 points — Partially in place
🟢 3 points — In place and working

Data Ownership

Is there a named person accountable for master data — not just the clean-up, but the rules?

🔴 1 Nobody owns master data. It’s everybody’s problem, which means it’s nobody’s priority. IT “looks after the system” but nobody owns the data itself.
🟡 2 We have informal ownership — certain people are “known” as the go-to for certain data, but it’s not formalised, not in job descriptions, and not governed.
🟢 3 We have named data owners by domain (items, suppliers, customers, BOMs). They have decision rights, and people know to go to them. It’s written down.

Naming Conventions & Standards

Can your teams agree on what things are called — and are those rules enforced?

🔴 1 No naming conventions exist. Item codes, supplier names, and product descriptions are created ad hoc. The same thing has multiple names in different systems or teams.
🟡 2 We have some naming rules (perhaps for items or suppliers), but they’re not consistently followed. New records are still created without checking for duplicates.
🟢 3 We have published naming conventions for key entities. They’re enforced — new records must follow the standard, and there’s a process to catch non-compliance.

Data Quality & Trust

Do your people trust the data in the system — or do they run parallel spreadsheets?

🔴 1 Widespread distrust. Planners, buyers, and operations teams maintain their own spreadsheets because they don’t trust what’s in the ERP. “The system is wrong” is a common phrase.
🟡 2 Mixed trust. Some areas are reliable (e.g. finance data), but operational data (BOMs, routings, planning parameters) is patchy. People check the system but verify elsewhere.
🟢 3 High trust. Teams use the system as the single source of truth. When data issues arise, they’re flagged and fixed through a defined process — not worked around.

ERP & Planning System Utilisation

Is your ERP actually being used for planning — or has the planning engine been bypassed?

🔴 1 The ERP’s planning engine is switched off or effectively bypassed. Planning is done manually in spreadsheets. Purchase orders and production schedules are created outside the system.
🟡 2 The ERP runs planning for some product lines but not others. Output is used as a “suggestion” but planners override extensively. Key parameters are incomplete or untrusted.
🟢 3 The ERP runs planning across the business and planners work from its output. Parameters are maintained and reviewed regularly. Exceptions are managed, not the norm.

Governance Cadence

Is there a regular rhythm for reviewing, auditing, and improving data quality?

🔴 1 No regular review. Data gets cleaned up reactively — usually when something goes wrong (a wrong shipment, a costing error, an audit finding). Nobody reviews data quality proactively.
🟡 2 Periodic reviews happen in some areas (e.g. annual stock-take triggers a clean-up), but there’s no standing governance cadence. Data quality is addressed project-by-project.
🟢 3 We have a standing data governance cadence — regular reviews, quality reporting, and a defined escalation path for data issues. Data stewards meet on a rhythm.

Decision Rights & Change Control

Is it clear who can create, change, or retire master data records — and is that enforced?

🔴 1 Anyone can create or modify records. There’s no approval process, no change control, and no audit trail for who changed what. Duplicates and errors accumulate unchecked.
🟡 2 Some controls exist (e.g. only certain people can create new items), but they’re inconsistent across entities. Changes to BOMs, routings, or supplier records don’t have formal sign-off.
🟢 3 Clear decision rights are published. We know who can create, modify, and retire records for each data domain. Changes go through an approval workflow, and there’s an audit trail.

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Dimension	Score

Scored 14 or below? The good news: these are fixable problems, and they don’t require a big IT project. They require clarity — who owns what, what the rules are, and how you’ll enforce them.

I work with mid-market manufacturers to build exactly these foundations — typically in 90 days, alongside the day job, not instead of it.

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