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Order picking is one of the most important processes in warehouse logistics. It directly influences delivery speed, operational costs and overall customer satisfaction. In many warehouses, picking activities account for the largest share of total operating costs.
For this reason, optimising order picking processes can significantly improve overall warehouse efficiency.
This Jungheinrich guide explains the fundamentals of order picking, introduces common picking methods and technologies, and shows how companies can systematically improve their picking performance.
Order picking is the process of retrieving and compiling specific items from the total inventory based on customer orders or production requirements.
In practical terms, order picking ensures that:
The term is often used interchangeably with order fulfilment, although order picking specifically focuses on the retrieval and consolidation of goods — not packaging or shipping.
Because of its central role, even small improvements in picking performance can have a significant impact on overall warehouse efficiency.
Optimised order picking has a direct influence on key performance indicators across the supply chain.
| Impact Area | Effect of Optimised Order Picking |
|---|---|
| Costs | Lower labour costs, fewer errors and returns |
| Speed | Shorter throughput and delivery times |
| Accuracy | Higher picking accuracy, fewer complaints |
| Productivity | Increased throughput and better resource utilisation |
| Customer satisfaction | Reliable, punctual deliveries |
Inefficient picking processes, by contrast, lead to delays, rising costs and dissatisfied customers.
Regardless of the method used, the order picking process typically follows these steps:
| Process Step | Description |
|---|---|
| Order acceptance | Orders are received and converted into picking tasks |
| Picking planning | Selection of method, route optimisation and resource allocation |
| Picking execution | Items are retrieved from storage locations |
| Control | Verification of completeness and correctness |
| Transfer | Handover of picked goods to packing or shipping |
Order picking methods describe how orders are processed and organised. They define the overall flow of the picking process.
Overview of Common Order Picking Methods
| Method | Description | Typical Use Case |
|---|---|---|
| Order-oriented (serial) picking | Each order is picked individually from start to finish | Low order volumes, high order variability |
| Series-oriented (parallel) picking | Multiple orders are picked simultaneously and sorted afterwards | High order volumes with similar order structures |
| Zone picking | Warehouse divided into zones; each picker works within one zone | Large warehouses with wide product ranges |
| Article-oriented picking | All items of one SKU picked at once for multiple orders | Few SKUs, many similar orders |
Each picking method has advantages and limitations, and many warehouses use hybrid combinations to maximise efficiency.
While picking methods define the organisational structure of the process, picking strategies describe the technologies and tools that support warehouse operatives during the picking process.
Overview of Picking Strategies
| Strategy | Description | Benefits |
|---|---|---|
| Manual picking | Paper-based or handheld-supported picking | Low investment, high flexibility |
| Pick-by-Light | Visual signals guide pickers | High speed and accuracy |
| Pick-by-Voice | Voice commands guide pickers | Hands-free operation, good ergonomics |
| Pick-by-Vision | AR glasses display picking information | Fast onboarding, high precision |
| Automated picking | Robots or AS/RS systems perform picking | Maximum throughput and consistency |
The right strategy must align with the chosen picking method and warehouse conditions.
Selecting the optimal picking method depends on multiple operational factors. The following table by Jungheinrich makes it easier to understand which one might be best for your warehouse:
| Decision Factor | Key Considerations |
|---|---|
| Order structure | Number of items per order, order similarity |
| Product range | Number of SKUs and storage characteristics |
| Order volume | Daily and seasonal fluctuations |
| Warehouse layout | Size, aisle width, storage system |
| Degree of automation | Existing systems and future scalability |
| Budget | Investment and operating cost targets |
In practice, mixed picking concepts often deliver the best balance between flexibility, efficiency and cost control.
Order picking is becoming smarter, more connected and increasingly automated.
| Trend | Impact on Order Picking |
|---|---|
| Artificial Intelligence (AI) | Dynamic route optimisation and demand forecasting |
| Robotics | Use of AMRs and picking robots for repetitive tasks |
| Augmented Reality (AR) | Visual navigation and error reduction |
| Internet of Things (IoT) | Real-time inventory and equipment monitoring |
| Sustainability | Energy-efficient vehicles and reduced travel distances |
| Human–robot collaboration | Robots handle physical tasks, humans focus on quality and decisions |
| Cloud-based systems | Scalable, flexible integration of new technologies |
These developments enable warehouses to respond faster to changing demand while maintaining high accuracy and efficiency.
Jungheinrich is your partner for efficient and future-proof order picking solutions — from manual systems to fully automated warehouses.
With more than 70 years of experience, we can support you throughout the entire process: analysis, planning, implementation and long-term optimisation.
| Solution Area | Benefits |
|---|---|
| Industrial trucks | Order pickers for every picking height |
| Warehouse systems | Customised racking solutions |
| Automation solutions | AGVs, stacker cranes and robotics |
| Software solutions | Jungheinrich WMS for end-to-end control |
| Consulting & service | Expert support and long-term reliability |
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