Blog · Board and management reporting
Build a daily operating review from exports with a shared cutoff, matched targets, and visible completeness checks. Work through shipment performance and separate late data from a real operating exception.
A daily KPI dashboard compares operating actuals with targets for the same day, reporting window, and cutoff. Show data completeness beside performance so a missing export does not become a false operating alarm. The first decision is whether the numbers are ready to compare; the second is what needs action.
Start with an export your operations team already uses. For a distributor, that could be the shipment register and the day's committed order schedule. Keep the promised shipment deadline and the actual shipment timestamp so that "shipped" and "shipped on time" remain different measures.
Write down the reporting time zone, operating-day boundary, and treatment of weekends. If locations work in different time zones, agree whether the review compares the same local operating stage or one common instant. Both can be useful, but they answer different questions.
The review needs an explicit source coverage field: the last operating interval the source owner confirms is complete. A file generated after the cutoff might still omit a delayed shipment posting. Do not infer coverage from the filename or upload timestamp.
Choose measures from the team's KPI examples, then keep the daily list small enough that each exception has an owner. The general KPI dashboard template covers reusable targets and status rules; this daily version adds the cutoff and completeness gate.
The fictional US distributor Cedar Route Supply reviews on-time shipments through 2:00 p.m. local operating time on October 22, 2026. Each shipment belongs to one warehouse and one reporting block. The schedule supplies due shipments independently of the shipment-status export.
The company expects four block records. Here is the initial combined export, with columns A through F. "Complete" means all status postings through that block's cutoff have been checked, including shipments that were not on time.
| Report date (A) | Warehouse (B) | Block (C) | Shipments due (D) | Shipped on time (E) | Complete (F) |
|---|---|---|---|---|---|
| October 22, 2026 | East | Morning | 125 | 120 | Yes |
| October 22, 2026 | East | Midday | 75 | 60 | Yes |
| October 22, 2026 | West | Morning | 80 | 80 | Yes |
| October 22, 2026 | West | Midday | 45 | 30 | No |
| Total | 325 | 290 | 3 complete |
These are illustrative business records, not a benchmark. The approved on-time target is 95.0%, and the separate full-day shipment volume target is 500. Store both in a target register with the effective date, owner, unit, and comparison window.
Do not remove the incomplete block from both numerator and denominator and call the remaining business the company result. That would change the population precisely where data is missing. Show the preliminary count and identify the missing coverage.
Enter the report date as a real date in H2 and the expected block count, 4, in H3. Keep the source date cells as dates rather than text. The due shipment count is:
=SUMIFS(D2:D5,A2:A5,$H$2)
The corresponding preliminary on-time rate is:
=IFERROR(SUMIFS(E2:E5,A2:A5,$H$2)/SUMIFS(D2:D5,A2:A5,$H$2),"No due orders")
Google's SUMIFS documentation specifies that it sums a range using multiple criteria. Add warehouse or reporting-block criteria when the source contains more than the one review window shown here. Always apply the same filters to the numerator and denominator.
Calculate block coverage separately:
=COUNTIFS(A2:A5,$H$2,F2:F5,"Yes")/$H$3
Google documents COUNTIFS as counting entries that meet multiple criteria. Here, it counts complete blocks for the selected date. Coverage is 3 / 4 = 75.0%; it measures the reporting check, not the share of shipments processed.
A gated rate cell can use:
=IF(COUNTIFS(A2:A5,$H$2,F2:F5,"Yes")<>$H$3,"Incomplete",IFERROR(SUMIFS(E2:E5,A2:A5,$H$2)/SUMIFS(D2:D5,A2:A5,$H$2),"No due orders"))
Validate unique date-warehouse-block keys first. Otherwise a duplicate complete record could conceal a missing block. Covirage is not affiliated with Google.
The initial count gives 290 / 325 = 89.2%, rounded to one decimal place. Because West's midday block is incomplete, label that rate preliminary and withhold the final target verdict.
West then supplies its completed block: 40 on-time shipments instead of 30, with the same 45 due. Replace the old block rather than appending another copy. The completed comparison becomes:
| Warehouse | Shipments due | On-time shipments | Rate | Target | Gap (percentage points) |
|---|---|---|---|---|---|
| East | 200 | 180 | 90.0% | 95.0% | -5.0 |
| West | 125 | 120 | 96.0% | 95.0% | 1.0 |
| Total | 325 | 300 | 92.3% | 95.0% | -2.7 |
Rates and gaps are rounded to one decimal place after calculation. The company rate is 300 / 325, not the average of the two warehouse percentages. East is the confirmed exception; West's earlier apparent miss came from incomplete reporting.
The proof is straightforward: 200 + 125 = 325 due, and 180 + 120 = 300 on time. Match the due total to the order schedule and the on-time total to the completed shipment register. Every on-time shipment must appear in the due population, and every shipment ID must appear only once.
The 300 on-time shipments also equal 60.0% of the full-day volume target of 500. That is contextual progress, not the on-time rate or a reliable end-of-day prediction. The remaining workload has not yet reached its deadline.
Keep the review table beside a short action log: warehouse, exception, source confirmation, investigation owner, response, and next checkpoint. East's owner should inspect the due shipments that missed their deadlines before assigning a cause. A ratio establishes the shortfall; it does not establish whether staffing, picking, inventory, or carrier timing caused it.
Use dashboard software evaluation when selecting how to present these checks. For work organized around a longer approved baseline, the project KPI dashboard uses a different progress comparison.
Bring a sample of your own shipment export, due-order schedule, and targets, including reporting dates and coverage fields. Covirage maps the columns; its tools compute and check the supplied counts and comparisons, and the external AI model explains the result with every figure traced to its rows. Create a free Covirage account, then set up your business and bring your files.
See self-service analytics for the supporting workflow.
Refresh at the operating checkpoints where someone can act on the result. Label each export's coverage time and the dashboard's comparison cutoff separately. A newly uploaded file can still contain old records, so upload time alone does not establish freshness.
Use a target for the same elapsed operating window when judging performance. A full-day target can provide context, but label progress against it separately. Workload can vary through the day, so elapsed clock time is not automatically a reliable allocation rule.
Choose measures with daily decisions attached, such as due orders shipped on time, open exceptions, or completed units. Record the owner and response for each measure. Financial measures that depend on an unfinished close may be more useful in another reporting cadence.