Eight data points to collect before deciding between assisted picking, conveyors, routing automation or a wider intralogistics project.
1. Start with order and flow profiles
Automation starts with demand structure: order lines per hour, SKU mix, carton sizes, batch profiles, cut-off times and seasonal peaks. An average daily volume can hide short periods where the real bottleneck appears.
2. Measure travel and waiting
Walking, searching, waiting for labels, checking destinations and moving empty containers are often easier to remove than the picking action itself. A useful study therefore separates value-adding handling from avoidable motion.
3. Separate information flow from material flow
Scan confirmation, routing rules, label generation and WMS data can improve reliability before heavy material automation is installed. In many warehouses the information layer is the lowest-risk first step.
| Data | Why it matters | Example output |
|---|---|---|
| Orders / hour | Sizes transfer and routing capacity | Peak profile |
| Walking distance | Identifies avoidable motion | Spaghetti / travel map |
| Error / return rate | Quantifies quality loss | Baseline KPI |
| SKU / format mix | Determines flexibility required | Format matrix |
| WMS interfaces | Defines data ownership | Interface map |
4. Size peaks, not only averages
Conveyors, buffers and sorters must be sized on realistic peaks and recovery scenarios. A design that only works at average throughput may create queues precisely when the warehouse is under the most pressure.
5. Define recovery before automation
A professional concept defines what happens when a barcode is unreadable, a destination is unavailable, a conveyor stops or a carton is rejected. Recovery flow is part of the automation architecture, not an afterthought.
General technical scoping note. Performance, interfaces and responsibilities must be confirmed project by project.