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Warehouse management analytics compares completed orders, labor hours, picking delays and unfinished work. Use operating exports to build a shift and site comparison whose order totals reconcile.
Warehouse management analytics compares order throughput, picking delays and labor hours from physical warehouse operating exports. The useful question is whether each site and shift is clearing its assigned work with the available hours. Read output beside unfinished orders so a strong shipping total does not hide a growing queue.
A warehouse manager needs to know which queue requires attention, which shift needs a workload review and whether a change improved service. Start with a completed order as the output unit, then split bulky, multi-line or special-handling orders before making personnel or capacity decisions.
This guide builds a reconciled comparison from files. The broader warehouse operating KPI scorecard covers accuracy, speed and cost together. Keep that balanced view alongside this narrower throughput investigation.
NIST's supply chain guidance describes improving bottlenecks and coordinating visibility across operations planning and inventory management. The practical implication for this report is to inspect upstream constraints as well as shipping output. If missing supplier deliveries explain a queue, supplier management analytics addresses that adjacent relationship.
Use the same operating week for order releases, final shipments, picking confirmations and time records. Include site and assigned shift on each order. Record actual labor hours in the same time zone and period as the operating work, and explain whether those hours include paid breaks, supervision and temporary workers.
Count an order complete only when its final shipment occurs. A partly shipped order remains in backlog. Count each order once, even when it has several pick confirmations or shipment lines. Keep canceled orders and transfers as separate movements if either occurs.
For picking delays, use the recorded planned pick-completion timestamp as the commitment and compare it with actual completion. Label the measure precisely: late picking is not necessarily late customer delivery. Open picks already past their deadline belong in a separate overdue queue.
Orders per labor hour = Completed orders / Included labor hours
Late-pick rate among completions = Completed orders picked after deadline / Completed orders
Closing backlog = Opening backlog + Released orders − Completed orders
The backlog identity below assumes no cancellations or transfers. Add those movements explicitly when your export contains them.
A US distributor operates Dallas and Reno sites. The table shows one week's activity across three disjoint queues. Orders retain their assigned queue throughout the week; the Dallas day and night figures are separate workloads, rather than successive snapshots of the same backlog.
Columns A through G hold the following fields. Released orders are newly admitted to the queue; completed orders include eligible work already waiting at the opening snapshot.
| Site | Assigned shift | Opening orders | Released orders | Completed orders | Labor hours | Completed orders picked late |
|---|---|---|---|---|---|---|
| Dallas | Day | 60 | 420 | 400 | 100 | 20 |
| Dallas | Night | 80 | 320 | 300 | 90 | 30 |
| Reno | Day | 40 | 300 | 280 | 70 | 14 |
| Total | 180 | 1,040 | 980 | 260 | 64 |
In H2, I2 and J2 respectively, enter these formulas and fill down through row 4:
=C2+D2-E2
=IF(F2=0,"",E2/F2)
=IF(E2=0,"",G2/E2)
| Site and shift | Closing orders | Orders per labor hour | Late-pick rate |
|---|---|---|---|
| Dallas day | 80 | 4.00 | 5.0% |
| Dallas night | 100 | 3.33 | 10.0% |
| Reno day | 60 | 4.00 | 5.0% |
| Total | 240 | 3.77 | 6.5% |
Show throughput to two decimals and rates to one decimal. Calculate totals from unrounded source values:
=SUM(E2:E4)/SUM(F2:F4)
=SUM(G2:G4)/SUM(E2:E4)
The total throughput is 980 / 260 = 3.77 orders per hour. Late picking is 64 / 980 = 6.5%. Do not average the displayed shift percentages or rates; their denominators differ.
For a site summary, place Dallas in L2. Its throughput formula is:
=SUMIFS($E$2:$E$4,$A$2:$A$4,L2)/SUMIFS($F$2:$F$4,$A$2:$A$4,L2)
Microsoft documents SUMIFS as adding values that meet specified criteria. Here it adds the site's orders and hours separately before division. Covirage is not affiliated with Microsoft.
The overall order rollforward is 180 + 1,040 − 980 = 240. The shift closing balances also add to 80 + 100 + 60 = 240. This check must return zero:
=SUM(C2:C4)+SUM(D2:D4)-SUM(E2:E4)-SUM(H2:H4)
Then compare the calculated closing orders with an independently exported closing backlog snapshot. Formula agreement alone proves the arithmetic, not whether the source has omitted an order. Tie included hours to the timekeeping report as a separate check.
The operation admitted 60 more orders than it completed, so backlog grew by 60. Dallas night has the highest late-pick rate and the lowest throughput in this example. That identifies a queue for review; it does not prove the shift is understaffed. Inspect line counts, replenishment waits, release timing and handling requirements before changing labor allocation.
Bring a sample of your own order, picking, backlog and labor-hour exports; Covirage maps the columns, and its tools compute and check comparisons across sites and shifts. The external AI model explains the results with every figure traced to its rows. Create a free Covirage account, which takes about a minute, then set up your business and bring your files.
See Covirage for shipping and logistics teams for the supporting operating context.
Use order releases and final shipment records, picking timestamps, a backlog snapshot and labor-hour records for the same period. Retain order identifiers, site, assigned shift and handling class so the totals can be checked and unlike workloads can be separated.
Use the unit that fits the decision and keep its definition stable. Orders suit final fulfillment throughput; lines can describe picking effort more closely. When order sizes vary substantially, compare handling classes before attributing a productivity difference to staffing or execution.
Yes. Completed orders per hour can rise while uncompleted orders accumulate or picking quality deteriorates. Review throughput alongside backlog, late completions and errors. Investigate the work mix and release timing before treating a higher rate as an improvement.