Why Picking Is Your Biggest Cost Problem
The numbers are brutal. A typical picker in a manual warehouse walks 15–16 kilometers per 8-hour shift. Track a picker with a pedometer for a week and the distances are consistently in that range.
The warehouse order picking software market hit $8.56 billion in 2025 and is growing at 12.74% CAGR, projected to reach $19.7 billion by 2032.↗
That growth tells you something: warehouses are realizing that picking is where the money leaks.
Order picking is also widely treated as the biggest cost center in warehousing.
Here’s a breakdown of where a picker’s shift actually goes:
Only 15–20% of a picker’s time is spent actually picking product.
The rest is walking, searching, confirming, and waiting. That ratio is the opportunity. Every percentage point you can shift from walking to picking is pure labor savings.
Recent research consistently shows travel time can consume over 50% of collection time in manual picking.
The Three Levers of Picking Optimization
Most warehouses try to fix picking by throwing more people at it. That’s the wrong lever. Here are the three that actually work, ranked by impact.
Lever 1: Intelligent Batching (Biggest Impact)
Batch picking means collecting items for multiple orders in a single trip instead of walking the warehouse once per order. The question is which orders to group together.
Naive batching (grouping random orders) gives you some benefit. Intelligent batching, where an algorithm selects orders whose items are physically close together in the warehouse, multiplies the effect.
The ideal batch:
- Contains 8–15 items across 3–6 orders (typical for B2C e-commerce)
- Has items clustered in 2–3 zones rather than scattered across the full warehouse
- Respects the trolley/tote capacity and the picker’s physical reach
- Considers order priority and SLA deadlines
Intelligent batching alone can reduce walk time by 15–25%, and when combined with route optimization, the effects compound.
Optioryx Pulse handles both simultaneously: it builds the batch and the route together, which is mathematically superior to optimizing them separately.
Lever 2: Route Optimization
Route optimization calculates the shortest possible path through the warehouse to collect all items for one or more orders. Think of it as turn-by-turn navigation for your warehouse floor.
Without route optimization, pickers typically follow a serpentine path (up one aisle, down the next) or worse, a paper list sorted by order line, which sends them zigzagging across the warehouse.
A route-optimized pick sequence considers:
- Exact bin locations in 3D space (aisle, bay, level)
- Travel distances between locations
- One-way aisle restrictions
- Equipment constraints (trolley capacity, weight limits)
- Sequence logic (heavy items first for pallet stability)
Optioryx Pulse reduces picking walk distances by 20–55% in manual warehouse environments.↗ The range depends on warehouse layout, order profile, and starting optimization level. A chaotic warehouse with no prior optimization sees the high end. A warehouse that already batches manually sees the lower end, but 20% is still significant when multiplied across 30 pickers over a year.
Lever 3: Slotting Optimization
Slotting determines where products are stored. It’s the structural foundation that makes route optimization effective. If your fastest-moving SKUs are scattered across 15 different aisles, even the best routing algorithm can only do so much.
Good slotting puts:
- High-velocity SKUs closest to the packing station and at ergonomic pick heights
- Frequently co-ordered items near each other
- Heavy items at waist height (ergonomics and speed)
- Slow movers in upper racks or remote zones
The catch: most warehouses slot by supplier or category, not by velocity or co-occurrence. That made sense when the warehouse was set up, but after a year of changing demand patterns, the original slotting is usually 30–50% suboptimal.
Manual vs Software-Optimized Picking: The Real Difference
Here’s what the before and after actually looks like:
These ranges come from warehouse operations running 10–50 pickers in manual environments (no goods-to-person automation).
The improvements are lower for warehouses that already batch manually and higher for warehouses that currently pick order-by-order with paper lists.
How AI Changes Picking Optimization
Traditional picking optimization uses static algorithms. You set the parameters, it calculates routes.
AI-powered optimization adds combined optimization that static algorithms can’t match.
This is the hardest problem and where Optioryx is unique.
Most systems optimize picking, packing, and slotting as separate problems.
Optioryx Pulse optimizes all three simultaneously.
Why does that matter? Because optimizing picking in isolation might create a great pick route that results in terrible pallet stacking. Simultaneous optimization avoids local optimum traps where you win on one metric and lose on another.
Picking Optimization Without a WMS
A common misconception: you need a sophisticated WMS before you can optimize picking. Not true.
What you actually need is:
- A product location map (which SKUs are in which bins)
- Order data (what needs to be picked)
- A layout model (aisle structure, distances)
If you have those three things, even in a spreadsheet, optimization software can work with them.
Pulse can connect to any data source (WMS, ERP, spreadsheet, CSV) because the algorithm doesn’t care where the data comes from. It cares about locations, quantities, and constraints.
Many of our customers started by exporting orders from their WMS, running them through Pulse, and sending optimized pick lists back. No deep integration needed for the first pilot.
The Picking Optimization Software Landscape
Not all solutions approach picking the same way. Here’s how the market breaks down:
Picking Optimization Pilot
You don’t need to commit to a full rollout to see results. Here’s how to run a pilot.
- Baseline measurement. Track your current metrics for one week: orders per picker per hour, average walk distance (use a pedometer app), pick errors per 1,000 lines, and time spent per pick wave. You need these numbers to prove ROI later.
- Data setup. Export your warehouse layout (aisle structure, bin locations) and one week of order data. Feed these into the optimization software. For Pulse, this takes 1–2 days. The layout builder lets you draw your warehouse or import a CAD file.
- Parallel testing. Run one shift optimized, one shift with your current process. Same pickers, same order volume, same SKU mix. Compare the metrics side by side.
- Measure and decide. Calculate the improvement. If you see a 15%+ reduction in walk distance or a 20%+ increase in orders per hour, the business case writes itself. Scale to the full operation or refine and test again.
Questions?
Order picking optimization is the process of improving the efficiency, speed, and accuracy of retrieving items from warehouse storage locations to fulfill customer orders. Order picking typically accounts for 55% of total warehouse operating costs and can consume up to 60% of the entire fulfillment process time. By optimizing picking operations, warehouses can reduce travel distances by 15-40% and increase throughput by 25% or more.
Batch picking is a warehouse picking method where a picker collects items for multiple orders in a single warehouse trip, rather than completing one order at a time. By grouping orders whose items are physically close together, batch picking reduces the total distance traveled per order. Intelligent batch picking software can group 3–6 orders per trip and reduce picker walk time by 15–25%, with even greater results when combined with route optimization.
Industry data shows that 30–40% of a picker's shift is spent walking between pick locations (Honeywell Intelligrated, 2024). In poorly optimized warehouses this can reach 50%. Only 15–20% of a picker's shift is spent actually picking product — the rest is travel, searching, and admin. This makes travel the single largest non-productive activity and the primary target for picking optimization.
Pick path optimization calculates the best route through the warehouse for a specific pick list, based on the actual layout and movement rules.
Batch picking sends one picker to collect items for multiple orders across the warehouse in a single trip. Zone picking assigns each picker to a fixed area, with orders passed between zones as they are built. Batch picking reduces total walk distance per order. Zone picking reduces congestion in busy warehouses. The best approach depends on your warehouse size, order profile, and SKU count. Many high-volume operations combine both (zone-batch picking), routing each zone's picker with an optimized path for maximum efficiency.
Order picking efficiency is affected by factors such as warehouse layout, your order and item profile, your order cluster or grouping restrictions (the more orders you can group together, the more efficient you will be) and lastly the current way of order picking.
Reducing walking and driving means pickers spend less time moving and more time picking. That lets you ship the same volume with fewer labor hours, cut overtime, or handle peak demand without adding extra staff.
Most operations see measurable improvement within 2–4 weeks of going live. A 20% reduction in walk distance across 20 pickers at $30/hour fully loaded cost saves roughly $50,000 per year in labor alone. Add in fewer pick errors, faster fulfillment, and reduced staff turnover from less physical strain, and payback periods of 2–4 months are common for manual warehouse operations.
Optioryx Pulse uses AI-powered algorithms to simultaneously optimize pick route sequence, order batch composition, and product slotting. Unlike systems that optimize these separately, Pulse calculates the route and batch together — producing shorter paths than sequential optimization. In manual warehouse environments, Pulse reduces pick walk distances by 20–55% depending on warehouse layout, order profile, and starting optimization level. Integration requires only product locations, order data, and a layout model. No WMS replacement is needed.
Yes, we offer free trials with guided setup and a walkthrough to help you get started.