Your pickers spend 50–60% of their shift walking. Not picking. Not packing. Walking.
That's the single biggest waste in any warehouse — and your legacy WMS is making it worse. Most warehouse management systems route picks the same way they did in 2010: static zone assignment, FIFO-only sequencing, and zero awareness of where inventory actually sits right now.
Intelligent pick path routing cuts travel distance by 25–40%. Same warehouse. Same staff. Same orders. Fewer steps.
What Is Pick Path Optimization?
Pick path optimization calculates the most efficient route for a picker to collect all items for an order (or batch of orders) in a single trip through the warehouse.
Instead of sending a picker to Aisle 1, then Aisle 14, then back to Aisle 3 — a good routing algorithm sequences those picks to minimize total travel distance.
Key Metrics
- Travel distance per pick: How far a picker walks per item collected
- Picks per hour: Total items picked in 60 minutes
- Lines per trip: How many order lines a picker completes per warehouse pass
- Travel-to-pick ratio: Percentage of time walking vs. actively picking
An optimized warehouse targets a travel-to-pick ratio under 40%. Most unoptimized warehouses sit at 55–65%.
Common Routing Strategies
| Strategy | How It Works | Travel Reduction |
|---|---|---|
| S-shape (serpentine) | Traverse every aisle containing a pick | Baseline — 0% |
| Return | Enter and exit each aisle from the same end | 5–10% worse than S-shape |
| Largest gap | Skip the largest unneeded section of each aisle | 10–20% improvement |
| Midpoint | Only enter aisles to the midpoint from each end | 10–15% improvement |
| Combined | Use best strategy per aisle dynamically | 15–25% improvement |
| AI-optimized | Shortest path with real-time adaptation | 25–40% improvement |
How Legacy WMS Handles Pick Routing
Most warehouse management systems ship with basic routing that hasn't evolved in over a decade.
Static Zone Assignment
Pickers are assigned to fixed zones. Orders spanning multiple zones get split into separate picks, requiring consolidation — an extra step that adds time and error risk.
If Zone A has 3 items and Zone B has 1 item, two pickers handle what one picker could do in a single trip.
FIFO-Only Logic
Legacy systems sequence picks by order time: first order in, first order picked. No consideration for where items are located. Order #1001 might have items on opposite ends of the warehouse, while Order #1003 has items right next to each other — but #1001 gets picked first regardless.
No Real-Time Adaptation
Legacy routing doesn't know:
- Which locations are currently congested (another picker is already there)
- Whether a product was recently moved during a slotting change
- That a location is temporarily blocked by a restocking cart
The route it generates at pick assignment time doesn't change — even when conditions on the floor do.
The Cost of Bad Routing
For a warehouse with 20 pickers processing 2,000 orders/day:
- Wasted travel: 2–3 hours per picker per shift
- Lost picks per hour: 15–25 picks/hour vs 30–45 possible
- Annual labor waste: $80,000–$150,000 in paid walking time
That's not a rounding error. That's a full-time salary spent on steps that software should eliminate.
Intelligent Pick Routing Algorithms Explained
Smart routing treats the warehouse as a graph problem — nodes (storage locations) connected by edges (aisles and cross-aisles) with weights (distance, congestion, time).
Shortest Path Algorithms
The algorithm calculates the minimum-distance route that visits all required pick locations. This is a variant of the Traveling Salesman Problem, and modern solvers handle warehouse-scale instances in milliseconds.
For a typical pick list of 10–15 items, the optimal route is computed in under 100 milliseconds.
Real-Time Inventory Positioning
Intelligent routing knows where every SKU actually is right now — not where it was last night when the batch job ran. If a product was moved during cycle counting or restocking, the route adjusts automatically.
This eliminates "phantom picks" where a worker walks to a location only to find the product isn't there.
Dynamic Rebalancing
When multiple pickers are active, the system avoids sending two pickers to the same aisle at the same time. It rebalances routes in real-time to:
- Reduce aisle congestion
- Minimize picker wait times
- Distribute workload evenly across zones
Multi-Order Batching
Instead of one order per trip, intelligent systems batch compatible orders together. A picker collects items for 5–10 orders in a single pass, sorted into separate totes on their cart.
The algorithm groups orders by:
- Location overlap: Orders with items in the same aisles
- Priority alignment: Orders with similar ship-by times
- Cart capacity: Maximum items that fit in one trip
Smart batching alone improves picks per hour by 30–50%.
Performance Comparison: Legacy vs AI Routing
We've compiled data from warehouse operations before and after implementing intelligent pick routing:
Travel Distance
| Metric | Legacy WMS | Intelligent Routing | Improvement |
|---|---|---|---|
| Avg. distance per pick | 45–65 feet | 25–40 feet | 30–40% reduction |
| Avg. distance per order | 280–400 feet | 160–250 feet | 35–40% reduction |
| Daily travel per picker | 8–12 miles | 5–7 miles | 35–42% reduction |
Throughput
| Metric | Legacy WMS | Intelligent Routing | Improvement |
|---|---|---|---|
| Picks per hour | 60–90 | 100–140 | 40–55% increase |
| Orders per hour (single) | 12–18 | 18–28 | 50–55% increase |
| Orders per hour (batch) | 20–30 | 40–60 | 80–100% increase |
Labor Cost Impact
For a 20-picker warehouse at $18/hour:
| Legacy | Optimized | Savings | |
|---|---|---|---|
| Picks per hour (team) | 1,500 | 2,400 | +900 picks/hour |
| Orders per day | 2,000 | 2,000 | Same throughput... |
| Pickers needed | 20 | 13 | ...with 7 fewer pickers |
| Annual labor cost | $748,800 | $486,720 | $262,080/year |
Or flip it: same 20 pickers, but now processing 3,000+ orders/day instead of 2,000. That's 50% more capacity without hiring.
Either way, the savings are significant — and they compound with slotting optimization that places high-velocity SKUs in the most accessible locations.
Want to see what optimized pick paths look like for your warehouse?
We build custom pick routing modules that bolt onto your existing WMS. $10K–$20K, live in 4–6 weeks.
How to Upgrade Your Pick Path Logic
You don't need to replace your entire WMS to get intelligent routing. There are two paths:
Option 1: Bolt-On Routing Module
Add an intelligent routing layer on top of your existing WMS:
- How it works: The module reads pick lists from your WMS via API, calculates optimized routes, and sends sequenced pick instructions back
- Integration time: 2–4 weeks
- Cost: $10,000–$20,000
- Disruption: Zero — your WMS stays exactly as-is
This is the right choice if your WMS handles everything else well and you just need better routing.
Option 2: Custom WMS with Built-In Optimization
If your WMS is the bottleneck across multiple areas — not just routing — it may be time for a full replacement:
- What you get: Pick routing + inventory management + integrations + reporting, all purpose-built
- Timeline: 6–10 weeks
- Cost: $20,000–$40,000
- Advantage: Routing, slotting, and batching all share the same data model for maximum optimization
Implementation Timeline (Bolt-On)
- Week 1: Map warehouse layout, measure current pick metrics, export aisle/location data
- Week 2–3: Build routing engine, integrate with WMS API, configure batching rules
- Week 3–4: Parallel test — run optimized routes alongside current routing to measure improvement
- Week 4–5: Go live, monitor, tune parameters
- Week 6+: Add features (congestion avoidance, dynamic rebalancing) based on real data
Hardware Requirements
Intelligent routing is software-only. No new hardware needed unless you're also upgrading scanner devices or adding pick-to-light.
The routing engine runs on your existing server or a small cloud instance ($50–$100/month).
What to Measure Before and After
Track these metrics for 2 weeks before implementation to establish your baseline:
- Average picks per hour per picker
- Average distance per order (use pedometer or warehouse layout math)
- Orders completed per shift
- Pick error rate (intelligent routing also reduces picking errors by sequencing picks more logically)
- Aisle congestion incidents (pickers waiting for each other)
Then compare the same metrics 2 weeks after go-live. Most warehouses see measurable improvement within the first week.
Frequently Asked Questions
Pick path optimization is the process of calculating the most efficient route for warehouse pickers to collect items for orders. Intelligent algorithms consider item locations, order priority, and physical constraints to minimize travel distance and maximize picks per hour.
Pick routing algorithms analyze order data, warehouse layout, and inventory locations to calculate optimal walking paths. Advanced algorithms use shortest-path calculations, dynamic batching, and zone optimization to reduce travel distance by 25-40% compared to sequential picking.
The best pick path strategy depends on warehouse layout and order profiles. S-shape routing works for simple warehouses. Largest gap and midpoint strategies reduce travel by 15-20%. AI-optimized routing combining multiple strategies reduces travel by 30-40% on average.
Pick path optimization software costs $10,000-$20,000 for a custom bolt-on module that integrates with your existing WMS. SaaS options run $500-$1,500/month. Custom solutions deliver better results because they are tuned to your specific warehouse layout and order patterns.
Pick path optimization saves 25-40% in travel distance and can reduce picker labor costs by $100,000-$260,000 annually for a 20-picker warehouse. Alternatively, the same team handles 50% more orders per day without additional headcount.
Your pickers are walking in circles. Let's fix that.
20-minute call. We'll map your warehouse layout and estimate the travel reduction. No commitment.