1. Why KPIs Matter in Warehouse Operations
Warehouse KPIs (Key Performance Indicators) help measure how efficiently and accurately a warehouse is operating.
They provide objective visibility into labor performance, stock accuracy, service quality, and process flow.
For small and medium warehouses, KPIs are essential for identifying bottlenecks, improving productivity, controlling costs,
and increasing customer satisfaction.
A strong KPI framework helps warehouse managers answer essential questions:
- How fast are we processing orders?
- How accurate is our inventory?
- Where do delays occur?
- Are we meeting customer expectations?
KPIs turn operational intuition into measurable facts.
2. How to Use KPIs in Daily Operations
- Track KPIs consistently (daily or weekly)
- Compare against internal benchmarks
- Investigate root causes when results fall
- Adjust staffing, layout, or processes
- Communicate results to the team
KPIs only work when they trigger action.
3. FAQ
How many KPIs should a warehouse track?
Usually 8–12, depending on complexity.
Which KPI is the most important?
Inventory accuracy — it affects everything.
How often should KPIs be reviewed?
Daily for operations, monthly for management.
Can small warehouses use KPIs?
Absolutely — they benefit even more from structured tracking.
4. KPIs Warehouse Operations
The most important KPIs for warehouse operations are grouped into three categories:
Operational Performance, Labor Productivity, and Service Level. A practical comparison table for
service quality monitoring is also provided.
4.1 Warehouse Operational Performance Indicators
These KPIs measure the overall throughput and capacity of warehouse operations on a daily basis.
- Total Orders per Day – Number of customer orders processed daily.
- Total Parcels per Day – Number of individual parcels shipped daily.
- Pallets OUT per Day – Pallets dispatched from the warehouse daily.
- Pallets IN per Day – Pallets received and stored daily.
Why it matters:
Monitoring operational KPIs helps identify trends in workload, peak periods, and capacity constraints.
4.2 Warehouse Labor Productivity Indicators
These KPIs focus on the efficiency and accuracy of warehouse staff, especially order pickers.
- Orders per Picker per Day – Average number of orders processed by a picker.
- Cases per Picker per Day – Number of boxes or cases picked by a worker daily.
- Order Lines per Picker – Total number of order lines handled per picker.
- Errors per Picker per Day – Number of picking mistakes per worker.
Why it matters:
Labor productivity indicators help identify top performers and areas for training or process improvement.
4.3 Warehouse Service Level Indicators
These KPIs measure the warehouse’s ability to meet customer expectations in terms of accuracy, completeness, and timeliness.
- Error-Free Orders (%) – Ratio of orders shipped without any errors.
- On Time, In Full (OTIF) – Percentage of orders delivered completely and on time.
- Orders Shipped vs. Planned – Actual shipped orders vs. planned orders for the day.
- Undelivered Orders per Day – Orders not shipped by the end of the day.
Why it matters:
High service level performance directly impacts customer satisfaction, loyalty, and reputation.
Service Quality KPI Comparison Table
The following table shows an example of service quality KPIs with performance thresholds for Blue (Excellent),
Green (Good), Amber (Needs Attention), and Red (Critical) levels.
| KPI | Blue | Green | Amber | Red | Definition / Measurement |
|---|---|---|---|---|---|
| Goods Received & Stocked ≤ 48h | >96% | 94.0%–96.0% | 92.0%–94.0% | <92% | Time to unload, store, and register inbound goods in WMS. |
| On‑Time Deliveries (within 24h of order entry) | >99.0% | 97.0%–99.0% | 95.0%–97.0% | <95% | Orders delivered on the scheduled delivery day. |
| Complete Order Deliveries (In‑Full) | >99.5% | 99.0%–99.5% | 97.5%–99.0% | <97.5% | Orders shipped to customers without missing items. |
| Picking Accuracy | >99.8% | 99.5%–99.8% | 98.5%–99.5% | <98.5% | Correct cases picked ÷ total cases picked. |
| Inventory Counting Accuracy | >99% | 99.85%–99.9% | 99.8%–99.85% | <99.8% | Correctly counted cases during stock counts. |
| Stock Availability | >99.0% | 97.0%–99.0% | 93.0%–97.0% | <93.0% | Time for received goods to become available for sale. |
| Out‑of‑Stock Items (OOS) | ≤10% | 10%–15% | 15%–20% | >20% | Share of SKUs currently unavailable in stock. |
| OOS Duration per Item | ≤24h | 24–48h | 48–72h | >72h | Time a SKU remains out of stock. |
| Overstocked Items | ≤1.2% | 1.2%–1.5% | 1.5%–2% | ≥3% | SKUs with >3 months of stock on hand. |
| On‑Time Delivery (Own Fleet – Same Day) | >99.0% | 97.0%–99.0% | 95.0%–97.0% | <95% | Same‑day deliveries using company fleet. |
Tip: Review daily, trend weekly. Blue is the strategic target; Amber/Red trigger corrective actions.