Every duplicate customer, mismatched product code, and orphaned supplier record costs you money — in wasted headcount, blown campaigns, failed audits, and AI projects that never leave the lab. We build the single trusted version of your core business data, and the governance that keeps it trustworthy after we leave.
It usually shows up the same way.
None of these are separate problems. They're the same problem wearing different clothes: nobody owns the definition of your core business entities.
That last number is the one that matters to you. Most MDM programmes don't fail on technology. They fail on scope, ownership, and a business case nobody believed. That's the part we're built for.
Finance and Sales report different revenue for the same account.
The CRM has four records for a customer who has one contract.
A product launches with the wrong dimensions on three marketplaces.
A regulator asks a question that takes eleven people two weeks to answer.
Then someone proposes an AI initiative, and the first pilot stalls because the model can't tell which record is real.
Master data is the small set of things your whole business refers to constantly: customers, patients, members, products, suppliers, employees, locations, accounts, materials. It's maybe 5% of your data volume and close to 100% of your cross-functional pain.
Master data management is the discipline of agreeing what those things are, matching the many versions scattered across your systems into one trusted record, and keeping that record correct as the business changes.
Who owns "customer"? What makes two records the same customer? Which system wins when they disagree? This is governance, and it's the part organisations skip.
Software that ingests records from every source, matches and merges them, applies survivorship rules, and publishes the trusted result back out. This is the MDM platform.
Data stewards who resolve what the machine can't, monitor quality, and hold the line as new systems get added. Without this, quality decays within two quarters.
Not every organisation needs a full centralised hub. We'll recommend the lightest pattern that solves your problem.
read-only index that points to source records. Fast, cheap, low disruption. Good for compliance and reporting use cases.
records copied into a hub, cleaned, published downstream for analytics. Good first step.
hub and source systems both maintain data, kept in sync bidirectionally. The common enterprise landing point.
the hub is the system of entry. Highest control, highest change-management cost.
Most MDM proposals you'll receive are shaped by what the vendor sells. Platform partners scope big, because licences drive their margin. Generalist consultancies scope big, because bodies drive theirs.
We do both advisory and delivery, and we start with advisory deliberately — because roughly a third of the assessments we run conclude that the client does not yet need a full MDM platform. Sometimes the answer is a data quality firewall at the point of entry, a governance operating model, and a two-domain consolidation hub. That's a smaller invoice for us and a far higher chance of success for you.
We quantify the cost of the current state in your numbers — duplicate spend, rework hours, denied claims, failed campaigns — before we design anything. If we can't build a defensible case, we tell you.
We're not a reseller. We'll shortlist platforms against your requirements, and we'll also implement the one you pick. You get the honesty of an advisor with the accountability of an integrator.
No 18-month big-bang. One domain, one high-value use case, live in 90 days. Then the next. Funding follows demonstrated results.
Every engagement includes steward enablement and a documented operating model. Our managed stewardship service exists for clients who want it — not because we've made it impossible to leave.
A structured conversation with a practitioner, not a salesperson. We map your systems, your symptoms, and your master data domains, and tell you where the money is leaking.
You leave with a verbal read on your top two domains by value, and an honest answer on whether MDM is your actual problem.
Our flagship entry engagement. We profile your real data, interview your stakeholders, score your maturity, and build the business case your CFO will actually sign.
You leave with a board-ready document and a defensible number.
We stand up the platform, model the domain, build match and survivorship rules, integrate sources, migrate and remediate, and hand over to trained stewards.
Typical first domains Customer/Party, Patient, Member, Product/Item, Supplier/Vendor, Location, Employee, Material, Chart of Accounts.
Includes platform configuration, data model design, match/merge tuning, survivorship rules, integration build, data remediation, steward workbench setup, UAT, hypercare, and enablement.
Trained stewards operating your MDM platform as a service. Match queue resolution, exception handling, quality monitoring, monthly quality scorecards, and continuous rule tuning.
Why clients buy this stewardship is a real job, it's hard to hire for, and it's the single most common reason a successful implementation degrades in year two.
The Challenge
Impact & Cost
repeated diagnostics, denied claims, unsafe care decisions, failed interoperability with outside providers, and transparency-reporting exposure.
Architectural Solution
The Challenge
Impact & Cost
KYC remediation cycles, AML exposure, BCBS 239 risk-data-aggregation findings, capital add-ons, missed cross-sell, and onboarding times that lose deals. Regulators have imposed substantial penalties on major institutions specifically for risk-data and controls failures.
Architectural Solution
The Challenge
Impact & Cost
returns driven by wrong or thin product content, delayed launches, marketplace listing rejections, chargebacks, and lost volume discounts because you can't see consolidated spend. Gartner has reported that a substantial share of organisations put the cost of poor product data in eight figures annually.
Architectural Solution
The Challenge
Architectural Solution
Customer, Supplier, Employee, Location, and Finance master data — with a strong bias toward the domain that unlocks your next strategic move, whether that's post-merger integration, a migration to a single ERP, or an AI programme that needs a clean foundation.
Symptoms, systems, domains. We tell you whether to keep talking.
Profile the real data. Interview 8–15 stakeholders. Score maturity. Build and pressure-test the business case. Prioritise domains. Recommend a platform or recommend against one. Deliver the roadmap.
Stand up governance before technology: a data governance council with real decision rights, named domain owners, a stewardship structure, and agreed policies. In parallel, provision the platform and design the first domain's model, match rules, and survivorship logic.
One domain, one high-value consuming use case, in production. Not a sandbox. Measured against baseline metrics captured in Phase 1.
Next domain, next use case. Each increment funded on the evidence of the last. Hierarchies, additional sources, and downstream consumers added as the value case supports them.
Quality scorecards, rule tuning, steward coaching, and an annual maturity re-score. Delivered by your team, our managed service, or a blend.
We publish a metrics baseline in Phase 1 and report against it every quarter. If the numbers don't move, you'll know before we do.
Supplied by the site owner once certifications and partnerships are confirmed.
Supplied by the site owner once a methodology asset is ready to publish.
Common, and usually diagnosable. The recurring causes are a programme scoped across too many domains at once, governance treated as a documentation exercise instead of a decision-rights structure, and a business case that never named a specific person's specific problem. We start every engagement by finding out which of those happened to you, because a second failed attempt costs more than the first — politically as well as financially.
It doesn't, and the distinction matters. A warehouse tells you what happened. MDM decides what is true, and writes that decision back into the operating systems where work gets done. Deduplicating inside a BI layer fixes the report; the call centre still sees four records. If the goal is only analytics, we'll say so and scope accordingly.
For a single system with one source of truth, sometimes. The moment you have two systems that both create customers, native dedupe can't arbitrate between them, can't hold a cross-system identifier, and can't apply survivorship across sources. It also can't tell you why a merge happened eighteen months later, which is the question auditors ask.
First domain in production by day 90 on our standard model, with the business case delivered in week 5. Longer if your source systems have no reliable APIs or your data volumes are extreme — we'll flag that in the assessment rather than in month seven.
The assessment is fixed-fee and quoted before we start. Implementation cost depends on domains, sources, and whether you're licensing a platform. We'll give you a TCO range including licence, implementation, and run cost in the assessment — including the option where you spend nothing on new software.
No. A meaningful share of our assessments recommend governance changes, entry-point quality controls, and a lightweight registry rather than a licensed hub. We'd rather have a reference than a licence commission we don't earn anyway.
Business, with IT as the delivery partner. If MDM is owned entirely by IT it will be de-prioritised the first time a system upgrade lands. Establishing that ownership is part of Phase 2, and it's non-negotiable in our engagements — it's the single strongest predictor of whether this works.
They're right, and the sequencing question is fair. Agentic and analytical AI both need entity resolution to function — a model can't reason about a customer it sees as four customers. But you don't need every domain mastered before you start. We scope the mastering to the AI use case, not the other way round.
Master data management is the practice of creating and maintaining a single, trusted version of the core entities a business depends on — customers, products, suppliers, patients, employees, locations. It combines governance rules, matching technology, and human stewardship.
Data governance sets the policies, ownership, and decision rights for data across the organisation. MDM applies those decisions to a specific set of core entities and enforces them technically. Governance without MDM is a policy nobody can implement. MDM without governance is a tool nobody maintains.
A golden record is the consolidated, best-available version of an entity, assembled from multiple source records using survivorship rules that decide which system's value wins for each attribute. It carries lineage back to every contributing source.
PIM manages rich, channel-facing product content — descriptions, imagery, marketing copy, channel-specific attributes. Product MDM manages the governed, structural truth about an item — identifiers, hierarchy, key attributes, relationships — and syndicates it. Many organisations need both, with a clearly drawn boundary. Buying both without drawing that boundary is a common and expensive mistake.
A first domain in production typically takes around 90 days from the end of the assessment, when scope is held to one domain and one consuming use case. Enterprise-wide multi-domain programmes run in phases across 18–36 months, funded incrementally.
There is no single best platform — the answer depends on your domains, your existing cloud estate, your integration landscape, and your stewardship capacity. Gartner's most recent Magic Quadrant for Master Data Management Solutions places Profisee, Informatica (Salesforce), Reltio, Stibo Systems, and Semarchy in the Leaders quadrant, and evaluates roughly twenty vendors in total. We shortlist against your weighted requirements rather than a default.
You need entity resolution for the entities your AI use case touches. You don't need a complete enterprise MDM programme first. Gartner has forecast that a majority of AI projects will be abandoned through 2026 because of inadequate data foundations — the practical implication is to master the specific domains your AI depends on, early and narrowly.
Our readiness assessment is fixed-fee and scoped before work begins. Implementation is quoted per phase. We provide a full TCO range — licence, implementation, and annual run cost — as part of the assessment so you can compare it against the quantified cost of doing nothing.
Thirty minutes with a practitioner. We'll map your systems, name your highest-value domain, and tell you whether MDM is the right answer for you right now. If it isn't, we'll say so.
No pitch deck. No platform recommendation you didn't ask for. If we can't build a business case worth acting on, we won't invoice you for pretending otherwise.
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