Efficient order picking - it’s about managing all the small steps that add up: walking, stopping, setting up carts, and working with your warehouse management system (WMS), order management system (OMS), or enterprise resource planning (ERP) system. By focusing on which orders you pick and when, you can double your pick rate without investing hundreds of thousands of dollars into robotics or warehouse overhauls.
Defining Order-Picking Productivity in Warehouses
Think of picking productivity as a combination of all the steps involved when you pick an order from the warehouse shelves. It includes:
- Walking Time: The time you spend moving from one spot to another.
- Trip Setup Time: The time spent getting your cart or picking tools ready before you start.
- Location Visit Time: The time it takes to stop, check you’re in the right place, and get ready to pick items there.
- WMS Input Time: The time needed to enter or confirm information in your Warehouse Management System.
- Product Grab & Put Time: The actual time it takes to pick up the products and place them in your cart.
When we talk about “picking productivity” we’re basically adding up all these different types of time. The goal is to reduce the ones you have control over (like walking time and the number of stops you make) to make the whole process faster and more efficient.
By focusing on the core variables that your operations team can influence, we can simplify what picking productivity consists of:
- Walking Time: The time spent traveling from one product location to another.
- Location Visit Time: The time it takes to stop, check you’re in the right place, and get ready to pick items there.
Why Order Batching Matters
Order batching is one of the most effective ways to improve warehouse picking efficiency. Instead of picking one order at a time (which leads to excessive walking and wasted effort), batching groups multiple orders together so pickers can retrieve several orders at once.
So, how you decide which products from which orders are going to be picked together during a single round of picking tour can dramatically affect how much time you spend walking and stopping.
How Batching Works
- Instead of walking back and forth for individual orders, pickers collect multiple orders in one trip.
- Orders can be grouped based on their location, order size, weight, shipping priority, cut-off times, or handling requirements
- This reduces the number of stops, cutting down on walking time and location visits—the biggest contributors to inefficiency.
That means less walking, fewer stops, and a faster, more efficient picking process.
Different Batching Scenarios
Yes, there are different batching strategies that warehouses use to optimize order picking. The best choice depends on factors such as warehouse size, order volume, and product variety.
- Batch Picking
Groups multiple orders together so that a picker collects items for several orders in one go. Pickers will place the products in the same bin and later separate them into separate orders.
- Cluster Picking
A single picker uses a cart with multiple bins to collect items for several orders at the same time. Items are sorted into separate bins directly on the cart.
- Wave Picking
Orders are released in batches at scheduled times rather than continuously. This helps sync picking operations with shipping schedules and balances workload during peak periods.
- Zone Picking
The warehouse is divided into zones, and each picker is responsible for one specific zone. Orders are batched by zones and later consolidated at a central location before shipping.
The Impact of Reduced Location Visits
Reducing the number of location visits yields two major benefits:
- Shorter Walking Times: With fewer stops, pickers spend less time traveling between locations.
- Less Overhead at Each Stop: Each visit to a location involves stopping your cart, confirming the pick, and resuming movement. Fewer stops mean less cumulative downtime.
Even if your warehouse layout (slotting) is not ideal, the benefit of halving your location visits often outweighs any gains from perfect product placement.
Overcoming the Combinatorial Challenge
Creating the most efficient batches isn’t as simple as just grouping nearby orders. There are many possible combinations, and factors like cart capacity, item weight, and shipping priority make it even more complicated. Trying to figure this out manually or using basic WMS picking rules often leads to wasted time and extra walking.
Beyond Standard WMS Logic
Most WMS providers are built to handle a wide range of warehouse operations but often struggle with specific tasks like order picking – using basic picking rules, leaving a lot of optimization potential on the table.
One of the main challenges? Stop conditions vary widely—from simple constraints like the number of orders a cart can carry to more complex ones, such as ensuring different-sized shipping boxes fit efficiently on a pallet.
Standard WMS logic is static, following fixed rules that don’t adapt to real-time warehouse conditions, leading to wasted steps and inefficiencies.
By implementing smarter algorithms, warehouses can 2x their pick rates. This does not require a change in WMS provider or even major layout changes. An optimization layer that sits next to your WMS, OMS or ERP platforms dynamically adjusts picking routes and batch orders more effectively, leading to 50% reductions in walking distances - something that standard WMS logic alone simply can’t achieve.
Optimize Before You Automate
Same efficiency without the robotics
Many warehouses look to automation — such as goods-to-person robotics or Automated Mobile Robots (AMRs)—as a way to improve efficiency. Often, companies invest in automation for the sake of innovation, responding to industry pressure to cut costs, manage labor shortages, and keep up with an increasingly fast-paced logistics landscape.
While these technologies offer benefits, they also come with high costs, complex integration, and long deployment timelines. Before committing to robotics, it’s essential to evaluate the entire order-picking process — because in many cases, optimization alone can achieve the same results at a fraction of the cost.
In fact, 90% of the efficiency gains from automation can be achieved simply by improving existing WMS logic. The biggest inefficiencies in warehouse picking come from excess walking and unnecessary location visits—problems that can be solved with smarter order-picking algorithms rather than expensive automation. By implementing dynamic batching and sequencing on top of an existing WMS, warehouses can significantly reduce walking time and streamline operations without major infrastructure changes.
Quantify Productivity Gains in Your Warehouse Digital Twin
Optioryx’s digital twin, OptiPick, creates a virtual replica of your warehouse—mirroring your physical layout, workflows, and constraints. It lets you test and visualize smarter order batching strategies in a risk-free environment.
You can simulate real-world picking scenarios, measure the impact of batching, and see exactly how much time, distance, and cost you could save—before making any changes.
Start improving day one, with data to back every decision. Learn more.