What is Picking in Logistics?
Picking in logistics is the process of selecting and retrieving the correct items from storage locations in a warehouse or fulfilment centre to satisfy customer or replenishment orders. It is one of the most labour-intensive and time-critical activities in warehousing.
In e-commerce and B2B distribution, picking directly influences order accuracy, same-day and next-day delivery promises, and overall customer satisfaction. A well-designed picking process can dramatically reduce operating costs whilst improving speed and reliability across the supply chain.
Key Picking Methods Explained
1. Single-Order Picking (Discrete Picking)
What it is: One picker handles one order at a time, walking through the warehouse to collect all items for that order before starting the next.
Best suited for: Low-volume operations, simple catalogues, small warehouses, or environments where training needs to be minimal and systems are basic.
Advantages: Simple process, easy to understand and train, minimal sorting required after picking, low system complexity, and suitable as a starting point for growing operations.
Disadvantages: High travel time per order, poor efficiency at scale, limited ability to optimise routes, and difficult to maintain short lead times as order volumes increase.
Real-world application: Small online shops, early-stage e-commerce brands, and spare-parts stores with relatively low daily order volumes.
2. Batch Picking
What it is: A picker collects items for multiple orders in a single tour through the warehouse, grouping picks for the same SKU to reduce repeated travel.
Best suited for: Operations with many small orders, overlapping SKUs across orders, and a need to reduce walking distance whilst keeping the process manageable.
Advantages: Reduces travel time per order, increases lines picked per hour, particularly effective when many orders share popular SKUs, and can be implemented with relatively simple WMS support.
Disadvantages: Requires consolidation and sorting after picking, increases process complexity, higher risk of mis-sorting if controls are weak, and may not work well when orders are very diverse.
Real-world application: E-commerce fulfilment centres picking multiple online orders in one route and later separating them at a packing or sortation area.
3. Zone Picking
What it is: The warehouse is divided into zones, and each picker works only within a specific area. Orders are passed from zone to zone, or picks from different zones are later consolidated.
Best suited for: Medium to large operations, warehouses with clear product groupings, and facilities where travel distance is significant or special handling skills are needed in certain zones.
Advantages: Reduces travel distance for each picker, enables specialisation by product type or handling requirement, can increase throughput, and scales well with larger teams.
Disadvantages: Requires coordination between zones, may create bottlenecks, needs a WMS capable of managing zone logic, and may complicate order tracking and balancing.
Real-world application: Fulfilment centres with separate zones for small items, bulky goods, temperature-controlled products, and high-value items.
4. Wave Picking
What it is: Orders are released to the warehouse in “waves” according to specific criteria (carrier cut-off times, routes, order types), synchronising picking with packing and despatch schedules.
Best suited for: High-volume warehouses with strict despatch times, multiple carriers, and the need to coordinate picking with loading and transport planning.
Advantages: Aligns picking activity with shipping deadlines, supports carrier- or route-based consolidation, helps manage workload, and improves dock and packing area utilisation.
Disadvantages: Less flexible for late orders once a wave is closed, requires capable WMS planning tools, and can cause peaks and troughs of activity if waves are poorly designed.
Real-world application: Retail distribution centres and e-commerce warehouses planning waves by carrier cut-off time or destination region.
5. Cluster Picking
What it is: A picker picks items for multiple orders at once using a multi-compartment trolley or cart, where each compartment represents one order or batch.
Best suited for: Operations with many small orders and overlapping pick paths, especially where automation is limited but efficiency gains are needed.
Advantages: Reduces travel, allows simultaneous picking for many orders, decreases sorting effort at packing if compartments are well controlled, and can significantly raise picks per hour.
Disadvantages: Requires clear labelling and process discipline to avoid mixing orders, carts can become heavy or unwieldy, and layout constraints might limit capacity.
Real-world application: E-commerce fulfilment centres with pick carts configured for 8–40 orders at a time, especially in shelving and bin areas.
6. Goods-to-Person Picking
What it is: Instead of pickers walking to stock locations, automated systems (conveyors, shuttles, robots) bring totes, trays, or shelves to a stationary picker workstation.
Best suited for: High-volume operations, limited floor space, fast order cycles, and environments where labour is expensive or hard to source.
Advantages: Dramatically reduces walking, enables very high pick rates, improves ergonomics, can integrate with lights or screens for guidance, and fits well with automation and robotics.
Disadvantages: High capital investment, dependency on automation uptime, longer implementation times, and less flexibility for sudden layout changes.
Real-world application: Large e-commerce fulfilment centres using shuttle systems, automated storage and retrieval systems (AS/RS), or AMRs carrying shelves to picking stations.
Key Technologies Supporting Picking
1. RF and Mobile Scanning
What it is: Handheld or wearable devices guiding pickers through tasks and scanning barcodes at pick locations and on items.
Advantages: Increases accuracy, provides real-time inventory updates, supports route guidance, and helps enforce process discipline.
2. Pick-to-Light and Put-to-Light
What it is: Light displays at locations or on racks show pick quantities or destination compartments, guiding the picker visually.
Advantages: Very fast, highly intuitive, reduces training time, and works well in high-density SKU environments.
3. Voice Picking
What it is: Pickers receive instructions via headset and confirm picks verbally, keeping hands and eyes free.
Advantages: Good ergonomics, improved accuracy over paper, robust in chilled or frozen environments, and supports multi-language teams.
4. AMRs and Robotics
What it is: Autonomous mobile robots carrying shelves, totes, or carts to reduce walking and support goods-to-person or person-to-goods hybrids.
Advantages: Cuts travel, supports scalable automation, and can be redeployed more easily than fixed infrastructure.
Comparing Picking Methods
| Picking Method | Productivity Potential | Accuracy | System / Tech Complexity | Implementation Cost |
|---|---|---|---|---|
| Single-Order Picking | Low | High (simple) | Low | Low |
| Batch Picking | Medium-High | Medium-High | Medium | Low-Medium |
| Zone Picking | High | Medium-High | Medium | Medium |
| Wave Picking | High | Medium-High | Medium-High | Medium |
| Cluster Picking | High | Medium-High | Medium | Low-Medium |
| Goods-to-Person | Very High | Very High | High | High |
Picking in E-commerce Fulfilment
E-commerce fulfilment centres handle a large number of small, multi-line orders with high customer expectations. Picking is usually the largest single driver of labour hours and cost per order.
High SKU Counts: Online catalogues often contain thousands of SKUs, so slotting strategy and clear location labelling are crucial for efficient picking.
Fast Order Cycles: Same-day and next-day delivery commitments require short cut-off times and tight coordination between order release, picking, packing, and carrier collection.
Peaks and Promotions: Black Friday, seasonal campaigns, and flash sales can multiply pick volumes. Flexible picking methods and cross-trained teams are essential for peak management.
Returns Handling: Returns must be inspected and, when possible, quickly returned to pickable stock to avoid artificial stock-outs.
Picking in Traditional Warehousing and B2B
In B2B and industrial logistics, picking patterns can be quite different from D2C operations, but precision remains essential.
Case and Pallet Picking: Many B2B operations pick full cases or full pallets rather than individual units, often using forklifts or ride-on equipment.
Project and Kit Picking: Manufacturing and service environments may require picking kits or project sets, combining many components into one logical unit for production or installation.
Store Replenishment: Retail distribution centres often combine full-case picking with split-case picking, balancing speed with planogram and shelf-space requirements.
Implementing a Picking Strategy Successfully
Start with Process and Data: Analyse current orders, lines per order, SKU popularity, travel paths, and error rates. This baseline shows where the biggest opportunities lie.
Choose Methods by Profile: Match picking methods to order and product characteristics. For example, use batch or cluster picking for many small orders, and dedicated flows for bulky items.
Enable with WMS and Simple Tools: Even before full automation, a capable WMS, barcode scanning, and clear location addressing can unlock major gains in accuracy and productivity.
Design for Ergonomics and Flow: Shorter walks, logical pick paths, and ergonomic workstation design reduce fatigue and support consistent performance over a full shift.
Iterate and Kaizen: Picking is never “finished”. Continuous improvement, layout tweaks, and regular re-slotting based on velocity data keep the process aligned with business growth.
Common Picking Mistakes to Avoid
Many warehouses carry legacy picking processes that quietly erode performance. Typical pitfalls include:
- Mistake: Relying on paper pick lists with no scanning
Impact: High error rates, slow updates, and limited visibility into real-time progress. - Mistake: Ignoring travel distance
Impact: Pickers spend most of their time walking instead of picking, pushing up labour costs. - Mistake: No clear slotting rules
Impact: Fast movers end up in poor locations, creating congestion and slow picks. - Mistake: Overcomplicating methods before basics are stable
Impact: Complex waves or zoning on top of weak processes leads to confusion and poor adoption. - Mistake: Insufficient training and change management
Impact: New methods fail because staff do not fully understand or trust the process and systems. - Mistake: Ignoring quality and rework costs
Impact: Mis-picks generate returns, reships, and customer service contacts that silently drain profit.
Measuring Picking Performance
To understand whether picking improvements are working, operations should track a balanced set of KPIs.
- Lines picked per hour or units picked per hour (by picker and method)
- Average order cycle time from release to completion
- Pick accuracy (% of orders shipped without picking errors)
- Rework and correction rate due to mis-picks
- Average travel distance or time per pick tour
- Labour cost per order or per line picked
- Utilisation of pickers by shift and area
- Congestion hotspots or bottlenecks in specific aisles or zones
- Impact of peak events on productivity and accuracy
Future Trends in Picking
Picking is evolving rapidly as technology and customer expectations change.
AI-Driven Slotting and Tasking: Machine learning models can continuously optimise SKU locations and assignment of tasks to pickers or robots based on real-time demand, congestion, and performance data.
Human–Robot Collaboration: AMRs and cobots increasingly work alongside people, taking over heavy travel or lifting whilst humans handle fine motor tasks and exception management.
Wearables and Vision Systems: Smart glasses, wearables, and computer vision can guide pickers visually and verify picks in real time, further reducing errors.
Micro-Fulfilment and Urban Logistics: Smaller, highly automated nodes closer to the customer are changing picking patterns, emphasising dense storage and ultra-fast pick cycles.
Sustainability and Wellbeing: Ergonomic design, reduced walking, and better working conditions are becoming strategic priorities alongside pure productivity metrics.
Conclusion
Picking is the heartbeat of warehouse operations. It links inventory storage to the customer promise and consumes a large share of labour and time. Small improvements in picking methods, layout, and technology can produce outsized gains in cost, speed, and accuracy.
Whether you run a fast-growing e-commerce brand, a traditional wholesale network, or a highly specialised parts operation, understanding picking methods and their trade-offs enables smarter decisions. When combined with good data, robust systems, and a culture of continuous improvement, picking becomes a strategic advantage rather than a constant bottleneck.
FAQ about Picking in Logistics
What does picking mean in a warehouse?
Picking is the process of locating and retrieving items from storage locations to satisfy customer or internal orders. It is one of the core activities in any warehouse or fulfilment centre.
Why is picking so important in e-commerce fulfilment?
Picking directly affects order speed and accuracy. Slow or inaccurate picking leads to late shipments, wrong items, returns, and extra customer service work – all of which hurt both margins and customer satisfaction.
What is the difference between picking and packing?
Picking is about collecting the right items from storage. Packing is the subsequent step where picked items are checked, packed into boxes or bags, labelled, and prepared for shipment.
Which picking method is best?
No single method is best for everyone. The optimal approach depends on order volume, SKU count, product characteristics, layout, and service requirements. Many warehouses use a hybrid model combining batch, cluster, zone, and goods-to-person picking.
How can I increase picking productivity?
Common levers include improving slotting, reducing travel distance, introducing batch or cluster picking, using scanning and basic WMS support, optimising pick paths, and investing in guidance technologies like pick-to-light or voice picking.
What systems are needed to manage picking?
A warehouse management system (WMS) is the core tool for managing locations, inventory, and tasks. Additional systems such as a transport management system (TMS), automation controllers, or AI planning tools can further optimise task assignment and flow.
How does automation change the picking process?
Automation shifts the focus from walking and searching to confirmation and exception handling. Robots and automated systems bring items to the picker or move picked goods onward, allowing people to handle more lines per hour with less physical strain.
How do I know if my picking process is performing well?
Track key metrics such as pick accuracy, lines per hour, average order cycle time, labour cost per order, and error-related rework. Compare trends over time and against industry benchmarks to identify improvement potential.
