Enterprise Intelligence Group
Retail master data readiness: can your planning decisions trust the inputs?
Test retail master data and planning inputs across products, locations, units, history and ownership. Use a practical checklist before implementation or improvement.
A product record can be complete and still be unsuitable for a planning decision. A pack conversion may be populated but interpreted differently by two systems. A category hierarchy may support reporting but not the assortment comparison a merchant needs. A store record may no longer reflect the fixture in use.
Retail master data management needs clear definitions and ownership. Planning readiness also requires testing how those records combine with sales, inventory, promotions and other inputs in the workflow that uses them.
Start with a decision, not an entire data estate
Choose a defined use case: a replenishment recommendation, a range change, a price comparison or a space allocation. Identify the inputs, their meaning and the action that follows. This gives the review a testable boundary and helps prioritize defects by their operational consequences.
Separate four kinds of information in the review: source facts, derived calculations, expert judgments and model inferences. Record where each came from, who owns it and what validation is required. An inferred attribute should not quietly become an approved business fact.
Derived calculation
Expert judgment
Model inference
Keep the source, owner and validation visible.
This is an EIG review convention, not a universal data standard.
Follow one item through the workflow
Consider an illustrative item purchased by the case and sold by the unit. Follow its identifier, pack size, cost and quantity through the supplier record, merchandising system and planning input. Ask whether a change in pack size has an effective date and whether each downstream process interprets it consistently.
The test is not simply whether the interface accepted the record. It is whether the resulting calculation and operational instruction mean what the business intended.
Reconcile meaning before combining sources
Market data and internal sales may use different product groupings, coverage, calendars or measures. Customer orders, supplier shipments and point-of-sale records describe different events. Document those differences before interpreting disagreement as a defect in one source.
For assortment decisions, check whether attributes support the intended comparisons. For forecasting, examine history, availability and event timing. For space planning, check item and fixture dimensions. A common technical format does not establish a common business meaning.
Follow a mapping exception into the business decision
Consider an illustrative supplier feed in which a quantity is expressed in cases while the receiving planning process expects individual units. The file can arrive successfully and still create an incorrect planning input if the conversion or effective date is wrong.
Do not resolve this by changing a number without retaining its meaning. Identify the source definition, target requirement, transformation rule and accountable approver. The same discipline applies to product hierarchies, location codes, status changes and supplier identifiers.
A source-to-target exception record
| Field | What to record |
|---|---|
| Business use | The planning, ordering or reporting decision affected |
| Source | System, object, field, unit and effective date |
| Target | Required field, meaning, unit and permitted values |
| Rule | Conversion, lookup or transformation and its approved source |
| Evidence | Permitted sample records and the observed discrepancy |
| Impact | Known affected records/workflows, with unknown extent labelled |
| Ownership | Business data owner, technical implementer and acceptance owner |
| Validation | Expected result, reconciliation check and exception treatment |
| Disposition | Approve, correct, quarantine or investigate, with rationale |
Supplier registration, product-data onboarding and EDI exchange are related but distinct. A registered supplier may still lack usable item data. An acknowledged message may still fail a downstream business rule. Agree which acknowledgement or reconciliation demonstrates each stage rather than treating transmission as end-to-end acceptance.
Market data introduces another reconciliation question. External category definitions, periods, coverage or measures may differ from internal sales records. Preserve those differences and any permitted-use restrictions. Do not force two measures to agree by silently changing their definitions.
AI can propose mappings or identify suspicious patterns. Proposed rules remain proposals until the responsible owner validates them. Keep the source fact, the transformation and any inferred value distinguishable so later users can understand what changed.
EIG’s systems and data integration analysis produces the agreed mapping requirements, harmonization rules and business acceptance scenarios. Connector development, production operation and managed EDI support require separately agreed responsibilities; they are not implied by this worksheet.
Discuss systems and data integration analysis
Use the supplier onboarding checklist
Planning-data readiness checklist
For each row record the decision affected, source, accountable owner, test result, exception and corrective action. “Unknown” is an open issue, not a pass.
| Area | Practical acceptance question |
|---|---|
| Product identity | Can the same item be traced across the relevant systems without ambiguous matching? |
| Hierarchies and attributes | Do definitions support the actual category, planning or customer decision? |
| Units and packs | Are quantities, costs and conversions interpreted consistently, including changes over time? |
| Locations and clusters | Are store, distribution and customer records appropriate for the required planning level? |
| Calendars and history | Are dates, aggregation periods and significant changes understood? |
| Availability and events | Can users identify missing availability, promotions or other relevant context? |
| Market-data mapping | Are coverage, product matching and measure differences documented? |
| Ownership and changes | Who approves definitions, corrections and effective dates? |
| Exceptions | Is a failed or uncertain record identified, routed and resolved before use where required? |
| End-to-end use | Does an agreed sample produce an operationally meaningful result downstream? |
Do not declare the whole dataset ready from one successful example. Define representative cases and important exceptions with the business owner, and record the limits of the sample reviewed.
Use AI-assisted cleansing with validation
AI may help propose mappings, classify exceptions or suggest product attributes. Those suggestions need provenance and checks appropriate to the consequence of an error. Preserve original values, distinguish suggestions from approvals and define how a person can reject or correct a proposed change.
Automation should operate within agreed permissions and controls. A plausible-looking value is not evidence that a commercial rule or source record is correct.
Make readiness an implementation deliverable
Turn findings into a prioritized register rather than a general statement that the data is poor. For each issue identify the affected decision, the responsible team, the proposed correction and the acceptance test. Separate defects that block the next release from improvements that can be scheduled later.
For supplier-specific handoffs, use the supplier onboarding checklist. For a new planning platform, review demand planning software requirements.
Define a focused data-readiness review
EIG helps teams clarify definitions, harmonize inputs and establish decision-level acceptance criteria. A scoped review can examine one planning workflow and produce a source-to-decision map, an exception register and a prioritized readiness plan with owners.
Discuss retail data and integration support
Where data readiness is part of a wider delivery programme, explore implementation and programme support. Access, confidentiality, scope and commercial terms are agreed before detailed work begins.
Send one consequential retail or CPG planning decision, list the inputs it relies on and say whether the agent will retrieve, recommend or act. Bring one live planning decision
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