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KPI Definitions and Data Quality

On-time Delivery Metric Reconciliation

A row-level reconciliation explaining why the SQL reporting mart, Power BI model, Excel management pack, operational extract and manually maintained report show different on-time delivery percentages.

Verified reconciliation workbookOpen image

Five reports disagree

Excel shows 62.86%. Power BI shows 38.38%.

A distributor's reporting analyst, Power BI developer, finance business partner and operations analyst all publish on-time delivery. Their results differ because they count different records and stop the delivery clock at different events.

The metric owner must decide which percentage can be released for the period, why the reports disagree and what must change in each calculation.

The same orders, calculated five ways

Grain, event date and extract timing explain the disagreement.

The build reads the same retained order, line and delivery-event records for every route. It recalculates each published percentage before applying the approved order-level final-receipt rule.

Five delivery report results converging through explicit correctionsThe SQL mart, Power BI model, Excel management pack, operational extract and manually maintained report start with different percentages. Formula, grain, date, source, filter and timing changes bring each route to the same approved order-level result.CURRENT REPORTSSQL reporting mart38.81%Power BI38.38%Excel management pack62.86%Operational extract38.83%Manually maintained report39.37%RECALCULATEONE ORDERfinal customer receiptapproved populationBRIDGECALCULATIONevent daterecord grainPOPULATIONcut-off and exclusionsSIGN OFF38.81%approved29,935 delivered orders reviewed · 10,045 eligible orders · zero unexplained residual
  1. 01
    Recalculate five published results

    Retain each formula, grain, date field, source population, filter, refresh time, numerator and denominator.

  2. 02
    Compare one approved rule

    Count one delivered order and use its final customer receipt against the original promise date.

  3. 03
    Bridge every difference

    Separate calculation changes from population and cut-off changes.

  4. 04
    Correct and sign off

    All five implementations finish at 3,898 of 10,045 eligible orders.

Independent recalculation

Each percentage keeps the records and rule that produced it.

SQL reporting mart38.81%

3,898 / 10,045

Counts each eligible delivered order once and waits for the final customer receipt.

Difference
Approved reference
Owner
SQL developer
Refresh
2026-01-03T06:00:00Z
Power BI38.38%

15,900 / 41,433

Counts order lines and tests warehouse dispatch rather than completed delivery.

Difference
Grain and event date
Owner
Power BI developer
Refresh
2026-01-03T06:30:00Z
Excel management pack62.86%

6,314 / 10,045

Counts an order as on time when its first customer receipt meets the promise date.

Difference
Formula and event date
Owner
Finance business partner
Refresh
2026-01-02T17:00:00Z
Operational extract38.83%

7,723 / 19,890

Uses warehouse dispatch and does not require a confirmed customer receipt.

Difference
Source population and event date
Owner
Operations performance manager
Refresh
2026-01-03T05:45:00Z
Manually maintained report39.37%

3,881 / 9,858

Uses an early cut-off and removes cancellation-after-dispatch records.

Difference
Timing, filter and staleness
Owner
Management-reporting analyst
Refresh
2025-12-24T17:00:00Z

Native Excel workpaper

The numerator, denominator and required correction remain visible.

The workbook contains the comparison, percentage bridge, retained order trace, implementation rules, material record differences, corrected results, validation and source register.

Retained output from the executable build

All displayed values come from the generated delivery records, SQL reconciliation and workbook outputs. They are not typed into the page as illustrative results.

A numerical bridge, not a verbal explanation

Every route reaches 38.81% with no unexplained remainder.

Power BI changes from line-level dispatch to order-level final receipt. Excel changes from first receipt to final receipt. The operational extract adds customer receipt and narrows its population. The manual report restores filtered and late-arriving records. SQL already applies the approved definition.

The agreed change in each report

Every correction has an owner, affected report and retained sign-off.

The tolerance is 0.0000 percentage points. A report is not aligned while any difference remains.

SQL reporting martApproved reference

Retain the approved order-level final-receipt rule.

Owner
SQL developer
Affected report
Monthly service report
Decision
Approved for this generated sample model
Approved
Director of Operations, 2026-01-05
Power BIGrain and event date

Replace the line-grain dispatch measure with the approved order-grain final-receipt measure.

Owner
Power BI developer
Affected report
Power BI delivery report
Decision
Approved for this generated sample model
Approved
Director of Operations, 2026-01-05
Excel management packFormula and event date

Replace first receipt with final receipt when testing whether the order completed on time.

Owner
Finance business partner
Affected report
Monthly management pack
Decision
Approved for this generated sample model
Approved
Director of Operations, 2026-01-05
Operational extractSource population and event date

Add final customer receipt and apply the eligible delivered-order population before publishing the metric.

Owner
Operations performance manager
Affected report
Operational delivery extract
Decision
Approved for this generated sample model
Approved
Director of Operations, 2026-01-05
Manually maintained reportTiming, filter and staleness

Refresh after the period closes and remove the manual cancellation filter so the complete approved population is used.

Owner
Management-reporting analyst
Affected report
Manually maintained service report
Decision
Approved for this generated sample model
Approved
Director of Operations, 2026-01-05

One split order explains the rule

ORD-0000001 is on time in Excel and late under the approved definition.

The order has 3 product lines. Its promise date is 2024-01-04. Excel uses the first customer receipt on 2024-01-02, while the approved rule waits for the final receipt on 2024-10-08.

  1. 01Order promised

    2024-01-04

  2. 02First receipt

    2024-01-02 · Excel adds 1 to its numerator.

  3. 03Final receipt

    2024-10-08 · the order is complete after the promise date.

  4. 04Approved treatment

    Denominator 1 · numerator 0 · late.

What was checked

19 of 19 checks passed for the result and the page values.

  • All 120,000 orders, 250,000 order lines and 180,000 delivery events agree with the shared generated-data manifest.
  • The SQL mart, Power BI model, Excel management pack, operational extract and manually maintained report are independently recalculated from retained rows.
  • Each route has one numerator, one denominator and three explicit bridge steps to the approved result.
  • The maximum unexplained bridge residual is 0.0000 percentage points.
  • All 5 corrected implementations use 3,898 on-time orders from 10,045 eligible delivered orders.
  • The split-order trace reproduces both the Excel on-time decision and the approved late decision.

Data and limits

A reproducible sample reconciliation, not a service-performance claim.

The build uses deterministic non-client order and delivery data generated with seed 240605. It covers 120,000 orders from 2024-01-01 to 2025-12-21.

Technical documentationOpen the retained data, rebuild command and detailed limitations

The data does not describe a real distributor. The DAX definition is retained and independently re-performed, but it has not been executed in Power BI Desktop. This project reconciles one metric and does not certify every measure in the five reports.

More work in KPIs and Data Quality

Promotional artwork for Order-to-Delivery Metric Dictionary; inspect the project page for native evidence.

Wholesale distribution

Order-to-Delivery Metric Dictionary

Finance reports on-time delivery at customer receipt. Operations uses dispatch date, while one report counts delivered lines. The project agrees how partial and cancelled orders should be counted.

Decision: Which on-time delivery definition belongs in the monthly service report, and how should split, partial and cancelled orders be treated?

Platform
SQL, Excel and Power BI measure definitions
Data scale
120,000 orders, 250,000 lines and 180,000 delivery events, verified
Maturity
Native Excel catalogue and executed SQL verified. Equivalent DAX and TMDL retained; Power BI Desktop execution not claimed.
Inspect this example

Next step

Reconcile a disputed metric before the next report is issued.

Start with the measures people dispute or the failed checks that need clearer ownership before reporting.