Consistent Values
Shared code sets are defined once, understood consistently and reused across systems and reporting.
Reference Data Management
Reference Data Management Consulting for Controlled Codes, Hierarchies and Enterprise Consistency
DataConsultant helps organisations govern the shared codes, classifications, lookup values, hierarchies and crosswalks that connect applications, reporting and business processes. We define ownership, authoritative sources, change workflows, versioning, validation and distribution so reference data can be changed deliberately and consumed consistently across the enterprise.
Authoritative code sets and ownership made explicit
Crosswalks and hierarchies governed instead of maintained ad hoc
Change requests, approvals, effective dates and versions controlled
Distribution and downstream impact designed for traceability
Scope and timeline are confirmed after reviewing the reference domains, source systems, change processes, mappings, stakeholder ownership, platform landscape and implementation depth.
REFERENCE DATA CONTROL HUB
Governed
Controlled Change
Requests, approvals, effective dates, versions and retirement rules replace uncontrolled list edits.
Reliable Integration
Crosswalks and publishing patterns reduce downstream reconciliation caused by mismatched reference values.
Stronger Evidence
Ownership, lineage, approvals and change history support governance, risk and assurance review.
Make Shared Business Codes an Operated Data Capability
Reference data is small compared with transaction data, but a single incorrect code, mapping or hierarchy can affect interfaces, reporting, financial controls, customer journeys and analytics across many systems.
What Reference Data Management Does
Reference Data Management establishes the rules, ownership, processes and technical patterns used to create, approve, version, map, distribute and retire shared values. The objective is not simply to centralise lists. It is to make each important code set or hierarchy understandable, authoritative, controlled and usable by the systems that depend on it.
Direct answer: if several applications use different codes for the same concept, maintain separate mapping spreadsheets, or cannot explain who may change a shared hierarchy, you have a reference-data governance problem rather than only a data-cleansing problem.
Mappings live in spreadsheets
Critical crosswalk logic depends on files, individual knowledge or local scripts with weak change control.
Systems disagree on codes
ERP, CRM, finance, data platforms and reports use overlapping but inconsistent value sets.
Hierarchy changes break reporting
Organisational, financial or product structures change without controlled effective dates and downstream coordination.
Ownership is ambiguous
Technology teams maintain values but business accountability, approval rights and retirement decisions are unclear.
Good fit for this service
- Multiple systems consume the same shared code sets or hierarchies.
- A migration or integration programme needs approved source-to-target mappings.
- Reporting or regulatory processes depend on controlled classifications.
- Teams need auditable change workflows, ownership and effective dating.
- An existing RDM or MDM platform requires better governance or operating procedures.
A different or wider service may be needed when
- The main problem is duplicate customers, products or suppliers rather than shared codes.
- Data is inaccurate or incomplete across many attributes and needs a broader quality programme.
- An enterprise governance operating model has not yet defined owners or decision rights.
- The primary requirement is a software licence, legal opinion, statutory audit or cybersecurity test.
- Source systems cannot provide the data, metadata or accountable stakeholders needed for design.
Not Sure Which Shared Lists Need Formal Governance First?
Start with the code sets, mappings and hierarchies that create the most reconciliation, reporting, integration or control risk. We can help define a focused discovery scope before wider implementation.
A Reference Data Operating Model from Authority to Consumption
Effective RDM connects business authority, stewardship, technical validation and downstream distribution. Each stage needs explicit decision rights, evidence and ownership.
Identify
Catalogue important code sets, hierarchies, owners, consumers, sources and business impact.
Define
Assign authoritative sources, value definitions, naming rules, allowed extensions and decision rights.
Approve
Design request, review, segregation-of-duties, versioning, effective dating and retirement workflows.
Map
Create crosswalks, transformations, parent-child structures and semantic mappings across systems.
Publish
Synchronise approved values through APIs, files, integration services or platform-native mechanisms.
Monitor
Track changes, exceptions, failed mappings, stale values, consumer adoption and control evidence.
Reference Data Management Capabilities
The engagement can cover assessment, design, implementation, remediation or operating support. Capabilities are selected according to the data domains, platform landscape and decisions required.
Inventory & Criticality
Establish what reference data exists, where it originates, who consumes it and which sets create material business or control dependencies.
- Code-set inventory
- Consumer mapping
- Criticality and impact
- Source-of-authority register
Ownership & Stewardship
Define accountable owners, stewards, custodians, approvers and escalation routes for the lifecycle of shared values.
- RACI and decision rights
- Segregation of duties
- Approval roles
- Governance cadence
Code Sets & Hierarchies
Design identifiers, labels, descriptions, parent-child structures, alternate hierarchies, local extensions and retirement rules.
- Canonical value design
- Hierarchy modelling
- Effective dating
- Deprecated-value handling
Crosswalks & Mappings
Make source-to-target relationships explicit and testable when systems cannot use one value set directly.
- Crosswalk specification
- Many-to-one rules
- Transformation logic
- Unmapped-value workflow
Versioning & Change Control
Control how changes are requested, assessed, approved, scheduled, published and reversed with traceable evidence.
- Change-request workflow
- Version model
- Impact assessment
- Release and rollback
Publishing & Integration
Design distribution patterns that keep consuming systems aligned with approved values while respecting system constraints.
- API and event patterns
- Batch and file distribution
- Subscription model
- Reconciliation controls
Quality, Controls & Evidence
Define validation, uniqueness, completeness, hierarchy integrity, exception handling and audit evidence for controlled reference assets.
- Validation rules
- Control evidence
- Exception queues
- Monitoring measures
Metadata, Lineage & Standards
Document definitions, authority, provenance, external-standard dependencies and downstream use so teams understand meaning and change impact.
- Metadata model
- Lineage and provenance
- External-source tracking
- Standard documentation
ERP, CRM and Platform Mapping
Align status codes, reason codes, organisational structures and domain classifications across source and target applications.
Currency, Country and Reporting Classifications
Govern externally maintained standards and internal reporting values with controlled effective dates and downstream mappings.
Categories, Units and Operational Codes
Manage shared classifications, measurement references, location types, supplier categories and product hierarchy structures.
Source-to-Target Crosswalks
Replace undocumented migration mapping logic with approved mappings, exception handling and reconciliation evidence.
Controlled Regulatory Code Sets
Maintain regulator, jurisdiction or policy-driven classifications while retaining source authority and change history.
Consistent Semantic Categories
Improve comparability across reporting, models and retrieval systems by using governed classifications and mappings.
Need to Replace Spreadsheets with Controlled Crosswalks and Change Workflows?
Share the affected systems, code sets, hierarchy structures and current approval process. We can help define a practical target model and implementation path without assuming a platform replacement.
Reference Data Deliverables Built for Implementation and Handover
Outputs are selected to make decisions explicit, support implementation and leave accountable teams with a usable operating model rather than an isolated assessment document.
| Work area | Typical deliverable | Purpose | Client input required |
|---|---|---|---|
| Discovery | Reference-data inventory and criticality map | Identify important code sets, hierarchies, owners, consumers and risks. | System inventories, extracts, reports, issue logs and stakeholders. |
| Governance | Ownership, RACI and decision-rights model | Clarify who proposes, validates, approves, publishes and retires values. | Business accountability, control expectations and governance forums. |
| Design | Code-set, hierarchy and metadata standards | Make identifiers, labels, attributes, structure and lifecycle rules consistent. | Business definitions, existing standards and consumer requirements. |
| Mappings | Crosswalk and transformation specification | Make source-to-target relationships explicit, reviewable and testable. | Source values, target models, exception rules and acceptance criteria. |
| Workflow | Change, approval, versioning and effective-date process | Control updates and preserve decision evidence across the lifecycle. | Approvers, segregation-of-duties needs, release calendars and risk rules. |
| Technology | RDM architecture and distribution design | Define system roles, interfaces, APIs, batch feeds, metadata and reconciliation. | Architecture, platform access, security constraints and integration standards. |
| Controls | Validation, exception and monitoring framework | Detect invalid, stale, unmapped or inconsistent reference values. | Business thresholds, issue-management process and operational owners. |
| Transition | Implementation roadmap, test pack and runbook | Support rollout, acceptance, knowledge transfer and ongoing operation. | Delivery capacity, environments, change windows and named service owners. |
How DataConsultant Delivers Reference Data Management
The sequence is adapted to the estate and target decisions, but each phase keeps business authority, technical feasibility and operating ownership connected.
Assess
Inventory reference assets, systems, mappings, issues, owners, change processes and critical downstream dependencies.
Output: baseline & scopeDesign
Define authority, metadata, hierarchies, mappings, workflow, versioning, controls and target operating responsibilities.
Output: target RDM modelBuild
Configure platform capabilities or controlled data stores, integrations, approval routes, validation and migration logic where implementation is scoped.
Output: implemented controlsValidate
Test values, mappings, hierarchies, effective dates, access, distribution, reconciliation, exceptions and operational acceptance.
Output: evidence & acceptanceOperate
Transition runbooks, governance cadence, monitoring, change routines, training and improvement backlog to accountable teams.
Output: sustainable operationWhat We Need from Your Organisation
Reference data decisions cannot be made safely by technology teams alone. The engagement requires access to the people and evidence that explain business meaning and downstream impact.
- Named business owner or sponsor
- Stewards and application SMEs
- Representative code lists and hierarchies
- System and interface inventory
- Current mappings and issue logs
- Security and access constraints
- Reporting and regulatory dependencies
- Timely approval and acceptance decisions
Governance, Security and Control by Design
The solution can incorporate proportionate controls for access, change, evidence, privacy and operational resilience without representing the engagement as legal certification or statutory assurance.
- Least-privilege access
- Segregation of duties
- Approval and audit trail
- Version and effective dates
- Exception and rollback process
- Metadata and lineage
- Retention and minimisation review
- Change impact and reconciliation
Preparing for a Migration, Reporting Change or New Shared-Service Model?
Reference data should be resolved before cutover logic hardens around inconsistent values. We can help identify authoritative sources, mapping decisions, approval dependencies and acceptance controls early.
Technology and Standards Should Support the Operating Model
RDM can be implemented with dedicated platforms or existing enterprise technology. Tooling should follow governance, hierarchy, mapping, integration, control and operating requirements rather than define them.
Technology Ecosystem
DataConsultant can assess the role of current and planned platforms, including dedicated RDM or MDM tools, ERP and finance applications, workflow services, metadata catalogues, data-quality tools, integration layers and cloud data platforms.
RDM / MDM platformsERP & finance systemsWorkflowAPIs & integrationMetadata & lineageData qualityCloud data platformsBI & reporting
Where relevant, platform fit can include current products such as Informatica Reference 360 and SAP Master Data Governance. Exact feature availability, licensing and implementation responsibilities should be validated for the client environment before commitment.
Reference Standards and Controlled Code Sources
Applicable standards depend on the data domain and jurisdiction. RDM commonly needs a formal process for adopting externally maintained values, tracking changes and controlling local extensions.
ISO 3166 country codesISO 4217 currency codesISO/IEC 11179 metadata conceptsISO 8000 master-data conceptsClient data standardsSector code setsRegulatory classificationsInternal taxonomies
Custom Scope and Pricing for Reference Data Management
A fixed generic price would hide the variables that drive effort and risk. DataConsultant therefore confirms commercial terms after the affected reference domains, systems, workflows, mappings and implementation responsibilities are understood.
Request a Scoped Proposal
Commercial treatmentRequest a Quote
Final pricing and timeline are confirmed after discovery. No fixed public fee is presented for this service.
Number and complexity of reference domains
Source, target and consuming systems
Hierarchy and crosswalk complexity
Change workflow and approval requirements
Data profiling, remediation and migration effort
Platform configuration or engineering scope
Integration, APIs and publishing patterns
Security, privacy and regulatory controls
Stakeholder workshops and business units
Testing, documentation and transition depth
Reference Data Assessment
Inventory selected code sets and hierarchies, identify control and ownership gaps, assess system dependencies and recommend a prioritised next step.
Governance & Target Operating Model
Define ownership, standards, workflows, metadata, versioning, crosswalks, distribution principles and implementation requirements.
Implementation & Migration Support
Configure or build selected RDM capabilities, mappings, controls, integrations, migration logic, testing and operational handover.
Reference Data Operations Enablement
Support monitoring, change governance, exception handling, documentation, training and continuous improvement under agreed responsibilities.
The central issue is shared code sets, classifications, hierarchies, mappings, versions and controlled changes across systems.
The main objective is governing core entities such as customers, products or suppliers, including identity, matching, survivorship and golden records.
The dominant problem is inaccurate, incomplete, invalid, stale or inconsistent data across broader datasets, not only shared reference values.
Need a Proposal That Separates Advisory, Platform and Implementation Scope?
Tell us whether you need a diagnostic, governance design, platform enablement, migration workstream or ongoing operating support. We can structure the proposal around the decisions and deliverables you actually require.
Why Use DataConsultant for Reference Data Management
The value of RDM comes from connecting business authority, governance, architecture and day-to-day operation. The engagement is structured around practical controls and reusable deliverables rather than a tool-only implementation.
Business Meaning First
Reference values are defined with business owners and consumers, not only inferred from technical source fields.
Governance Built In
Ownership, approvals, effective dates, exceptions and evidence are designed alongside code sets and integrations.
Platform-Aware, Requirements-Led
Existing tools can be improved or new platform needs assessed without assuming that technology replacement is the answer.
Transition to Operations
Runbooks, roles, test evidence, monitoring and knowledge transfer are included when they are needed for sustainable adoption.
Reference Data Management FAQs
Answers to common enterprise questions about scope, governance, platforms, standards, delivery, pricing and implementation.
What is reference data management?
Reference data management is the governed management of relatively stable code sets, classifications, lookup values, hierarchies and mappings that are reused across systems and business processes. Examples can include country codes, currency codes, status values, reason codes, product classifications, organisational hierarchies and source-to-target crosswalks.
How is reference data different from master data?
Reference data usually provides controlled values used to classify or describe other data, while master data represents core business entities such as customers, products, suppliers, employees, assets or locations. The disciplines are closely related, but reference data often needs different lifecycle, approval, versioning, hierarchy and distribution controls.
What is included in DataConsultant’s Reference Data Management service?
Scope can include reference-data inventory, ownership analysis, code-set and hierarchy design, source-of-authority rules, stewardship workflows, crosswalks, versioning, effective dating, change control, validation, metadata, lineage, distribution patterns, platform requirements, implementation support, testing, operating procedures and knowledge transfer. Final scope is confirmed during discovery.
When does an organisation need a formal reference data management capability?
Common triggers include inconsistent codes across ERP, CRM, finance, risk or analytics systems; manual mapping spreadsheets; repeated integration defects; regulatory or management reporting changes; mergers; platform migration; unclear ownership of shared lists; uncontrolled hierarchy changes; and downstream reconciliation caused by mismatched reference values.
What deliverables can we expect?
Typical deliverables can include a reference-data inventory, ownership and RACI model, authoritative-source register, code-set and hierarchy standards, mapping and crosswalk specifications, change-workflow design, versioning and effective-dating rules, data-quality controls, integration and publishing design, governance procedures, test evidence, migration plan, runbook and implementation roadmap.
Can you manage external standards such as country and currency codes?
Yes, where relevant. The service can design controls for externally maintained code sets such as ISO country or currency codes as well as industry or regulator-issued lists. The authoritative source, update mechanism, effective dates, local extensions, approval rules and downstream propagation should be explicitly governed rather than assumed.
Which platforms can support reference data management?
Reference data can be managed through dedicated RDM or MDM platforms, ERP or finance applications, metadata and governance platforms, controlled databases, workflow tools, APIs and integration services. Platform selection should follow data volume, hierarchy complexity, stewardship needs, auditability, integration patterns, security, licensing, existing architecture and operating capability.
Can DataConsultant work with Informatica Reference 360 or SAP Master Data Governance?
The service can consider enterprise platforms such as Informatica Reference 360 and SAP Master Data Governance when they are relevant to the client environment. Exact feature fit, current product capabilities, licensing, integration constraints and implementation responsibilities should be verified during platform assessment rather than assumed in advance.
How are governance, security and privacy handled?
The service can define ownership, segregation of duties, approval paths, change evidence, access controls, audit trails, retention, masking or minimisation where needed, and escalation for exceptions. Reference data itself may be non-personal, but supporting workflows, labels, mappings or source records can still create privacy, security or regulatory considerations that require client-specific review.
How long does a reference data management engagement take?
A reliable duration is confirmed after scoping. Timing depends on the number of code sets and hierarchies, source systems, mappings, stakeholder groups, jurisdictions, platform complexity, data quality, integration requirements, approval cycles, migration scope, testing depth and whether implementation or ongoing operations are included.
How is Reference Data Management pricing calculated?
DataConsultant uses scope-led pricing for this service rather than publishing a fixed fee. Commercial terms depend on the number and complexity of reference domains, source and target systems, hierarchy and crosswalk requirements, workflow design, migration and remediation effort, platform work, testing, governance controls, documentation, stakeholder workshops and implementation support.
Can the service support a migration or ERP transformation?
Yes. Reference data management is often a critical workstream in ERP, finance, CRM, data-platform and MDM transformations because source codes, target values, hierarchies and mappings must be reconciled before cutover. The engagement can support inventory, mapping, approval, cleansing, migration rules, validation and post-cutover controls.
What information should we prepare before the engagement?
Useful inputs include code lists, hierarchy extracts, mapping spreadsheets, data dictionaries, source and target system inventories, integration diagrams, issue logs, reporting requirements, ownership information, change procedures, audit findings, external standard dependencies, platform documentation and access to business and technical decision-makers.
Reference Data Management Enquiry
Request a Reference Data Scope Review
Share your contact details and requirement. DataConsultant can review the likely scope, evidence needed, stakeholder involvement and appropriate next step.