Services / Governance & Supply
Master Data Governance
Every reporting problem we are called in to fix has the same root: the same thing exists under four names. We clean the master data, then install the standard, the workflow and the stewardship that stops it degrading again.
- Practice
- Governance & Supply
- Best fit
- Best fit before a migration, after a merger, or whenever two departments cannot agree on a stock or revenue figure.
- Industries
- Manufacturing · Distribution · Retail · Textile · Healthcare
What’s included
Scope, stated before we start
Six work-streams that make up a standard engagement. Anything outside them is priced separately and named in the proposal — never absorbed quietly.
Data-quality assessment
Profiling of customer, item, vendor and asset masters: duplicate rate, completeness, validity, orphan records — quantified, with a cost attached to each defect class.
Naming & attribute standards
Written conventions, mandatory attribute sets, code structures, unit-of-measure and classification hierarchies your teams can actually apply consistently.
Cleansing, dedupe & enrichment
Matching, survivorship rules, merge with full audit trail, and enrichment of the attributes reporting depends on. Nothing merged without a reversible record.
Creation & change workflow
Request-review-approve flows for new masters, with validation at entry so the standard is enforced by the system rather than by reminder emails.
Stewardship model
Named data owners and stewards per domain, a decision forum, and a RACI that survives the people currently in the roles.
Quality scorecard
A monthly data-quality dashboard with thresholds and trend, so degradation is visible in weeks instead of at the next audit.
Outcomes
What changes when this is done properly
These are the three differences clients describe six months after go-live — not feature claims.
- Duplicate masters reduced to a measured floor
- New records validated at entry, by rule
- A named owner for every data domain
Not sure this is the right service? Discover is a fixed-price, two-to-three week assessment that answers the question with evidence — and it is usable whether or not you appoint us. Start there instead →
Who it’s for
Industries where this comes up most
Each links to how the service is shaped for that sector — the requirements differ more than vendors admit.
Our approach
The same four phases, applied to this scope
Reused deliberately. A consistent method is what makes a fixed price honest and a date holdable.
01
Discover
Process mapping before software selection.
We walk the floor and the ledger. Two to three weeks of structured interviews and document tracing produce a current-state process map, a data-quality baseline, and a written list of the decisions your systems cannot currently answer.
02
Design
One target architecture, agreed on paper.
Chart of accounts, item and customer master rules, approval hierarchies, integration contracts and reporting model are designed together — not discovered during build. You sign off a blueprint, not a demo.
03
Deliver
Configure, migrate, test, train — in that order.
Iterative configuration with fortnightly conference-room pilots. Data migration runs three times before go-live: trial, dry run, and cutover, each reconciled to the closing trial balance. Users train on their own data.
04
Sustain
Hypercare, then measurable adoption.
Four to eight weeks of hypercare with named owners and a burn-down of issues. Then a governance rhythm: master-data stewardship, monthly close review, and a Power BI adoption dashboard that shows whether the system is actually being used.
Related case study
One inventory engine behind three sales channels
Wholesale, retail and e-commerce moved onto one Odoo inventory and pricing engine, with integration contracts, batch and expiry control, and margin reported at SKU and customer level.
We had eleven versions of our item master across three companies. Techlyst rebuilt it as one governed standard and then made sure it stayed that way. Stock accuracy went from an argument to a number.
Rarely at mid-market scale. Most organisations get further with ERP-native validation, a request workflow and real stewardship than with a tool nobody owns. We only recommend a platform when domain count and volume justify it.
Assessment takes two weeks. Cleansing depends on volume and decision latency — a 40,000-item master typically takes six to ten weeks, most of it waiting on business decisions rather than processing.
Your stewards, using survivorship rules we agree upfront. We prepare candidate matches with evidence and confidence scores; the business decides, and the decision is logged.
Entry validation, a creation workflow with approval, a named steward per domain, and a monthly scorecard with a threshold that triggers action. Governance without measurement decays within two quarters.
More in Governance & Supply
Delivered by the same team
GRC & SoD
A control framework and segregation-of-duties matrix enforced inside the system.
GRC_SODProcess Reengineering
Fix the process before you automate it — otherwise you buy a faster version of the problem.
BPRSOPs & Policies
Documentation people actually use — role-based, versioned, and tied to the system.
SOPNext step
Talk to someone who has implemented Master Data Governance before
Not a sales call. A working conversation with the person who would run the engagement, and a straight answer on scope, sequence and cost.