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Reliable warehouse reporting

Warehouse data quality: the checks before every KPI

Good formulas cannot repair unclear units, duplicate orders or ambiguous dates.

Beginner-friendly animated guide

Learn Warehouse data quality: the checks before every KPI from the beginning

Practical controls for SKU codes, units, dates, duplicates, partial shipments and KPI reconciliation. Use the controls to study one section at a time. No previous warehouse knowledge is required.

Step-by-step

Read the complete animation transcript

    Seven controls that prevent misleading warehouse reports

    1. Preserve identifiers as text. SKU and location codes can contain leading zeros.
    2. Declare the unit of measure. Do not add eaches, cases and pallets in one quantity column.
    3. Choose the business date. Order, promised, ship and delivery dates answer different questions.
    4. Control partial shipments. Decide whether the KPI uses order, line, unit or shipment level.
    5. Remove duplicate events. Reprints, status history and joins can multiply transactions.
    6. Separate missing from zero. Unknown performance is not zero performance.
    7. Reconcile totals. Compare row counts and control totals back to the source system before publishing.

    Minimum data-quality record

    ControlRecord
    SourceSystem, report name, extraction time and filters
    ScopeSite, customer, channel, status and exclusions
    GrainOne row per order, line, SKU-location, receipt or event
    UnitsCurrency, time zone, UOM and conversion rule
    ExceptionsReturns, cancellations, backorders and missing values
    ReconciliationSource count, quantity and value compared with output

    Download KPI data dictionary Download SKU checklist

    Original field application

    Work the problem from evidence to closure

    Practice situation

    The same SKU has different units and descriptions across purchasing, warehouse and sales files. The useful response is not a generic target or a tick-box answer. Start by defining the exact event, location, item, time period and decision owner so that another reviewer can reproduce what happened.

    Decision path

    Choose an accountable master, define validation rules and quarantine changes that fail required checks. Record assumptions before changing the process. Compare the proposed control with the current condition, test it on a limited scope where appropriate, and define the condition that would require work to stop or management to escalate.

    Evidence pack

    Data owner, field definition, source system, validation result, rejected record, correction and approval. Keep the source record with the action rather than copying only a summary into a presentation. A complete pack should show who reviewed the information, what was excluded, the date of the decision and proof that the action was later checked.

    Supervisor walkthrough

    1. Observe the work at the location and ask the operator to explain the normal sequence.
    2. Compare the observed sequence with the written standard and system record.
    3. Separate an isolated exception from a repeated condition by checking recent history.
    4. Agree one immediate control and one corrective action with a named owner and realistic date.
    5. Return after implementation and verify the result with evidence, not verbal confirmation.

    Common failure to avoid

    Do not close the review with “team advised” or “monitor closely.” Those statements do not identify a changed control, accountable owner or effectiveness check. A useful closure states what changed, where it changed, when it was checked and what result would reopen the issue.

    Method and verification

    This lesson is an operational decision aid. Reconcile definitions to your contracts, system fields and approved local procedure. See the calculation and evidence method.

    Editorial review: Amit Mehta · Reviewed 2026-10-16 · Operational education, not legal or engineering approval. How WarehouseOps checks and corrects content.