The Hidden Inefficiencies in High-Bay Warehouses—Solved

Most discussions around warehouse picking strategy tend to focus on DTC and e-commerce workflows—fast-moving, small-order environments that dominate online content and industry playbooks. But the reality on the floor of a high-bay, high-throughput B2B warehouse looks nothing like that. Here, orders span 50 to 150 SKU lines, inventory is scattered across multiple pallet positions, reach trucks navigate lifts across seven or more levels, and FEFO or lot-based rules shape every movement.

When these complexities collide, the conventional wisdom around optimizing pick paths or slotting falls apart. Travel time balloons, pallet spread increases, and operations get bogged down by inefficiencies that rarely show up in “best practice” picking guides. This gap between abstract strategy and ground-level reality is exactly where most B2B warehouses lose the most time—and where smarter, coordinated logic can unlock massive efficiency gains.

The Realities of High-Bay B2B Warehousing

High-bay B2B warehouses don’t operate on the same playbook as DTC fulfillment. The environment is bigger, heavier, and far more complex — and the picking logic needs to reflect that.

1. High Line Counts per Order

Most B2B orders contain 50–150 SKU lines.
This immediately changes the nature of route planning, batching, and pick-path optimization. The picker isn’t grabbing a handful of items — they’re navigating a long, multi-node sequence.

2. SKUs Spread Across Multiple Pallet Positions

The same SKU often sits in 3, 4, or even 5 pallet locations due to replenishment timing, partial pallet picks, or open cases.
This creates:

• More travel
• More location checks
• More mid-route detours

A single line suddenly becomes a multi-stop task.

3. Seven-Level Reach-Truck Movement

Unlike low-bay operations, B2B pickers work across 7+ vertical levels using reach trucks.
Vertical lifts introduce:

• Slow cycle times
• Queueing behind equipment
• Increased effort for even small top-ups

Every lift adds minutes — not seconds.

4. FEFO and Lot/Expiry Constraints

FEFO rules and lot traceability further restrict which pallets can be picked.
Even if a low-effort pick exists at ground level, the picker may be forced to:

• Access a higher-level pallet
• Travel to a farther aisle
• Open a pallet that is harder to reach

Compliance adds unavoidable friction.

5. Travel Time Grows Exponentially

When you combine:

• High line counts
• Scattered pallet positions
• Vertical lifts
• FEFO-driven restrictions

…you get exploding travel time.

What seems like a straightforward order on paper becomes a long, unpredictable route with unnecessary backtracking, aisle changes, and mid-path interruptions.

This is the real operational drag inside high-bay B2B warehouses — and it’s why abstract picking advice rarely holds up on the floor.

The Hidden Pain Points Nobody Talks About

Most of the inefficiencies in high-bay B2B picking don’t come from obvious issues. They come from small, repeated patterns that compound across hundreds of orders and thousands of SKU touches. These are the problems rarely covered in conventional picking “best practices,” but they are exactly what slows a warehouse down.

1. Excessive Location Splits for a Single Line

A common pattern: one SKU line gets pulled from 3–5 different locations even though 1–2 would be enough.

Why it happens:

• Partial pallet picks
• Random replenishment
• Old pallets opened prematurely
• No logic to consolidate pickable inventory

Impact:

• Extra travel
• More reach-truck cycles
• Inconsistent route flow

A single unnecessary split multiplies across hundreds of lines per day.

2. Late “New Aisle” Introductions Mid-Route

Pickers often discover new aisles halfway through the route — aisles that should have been hit early or batched together.

This causes:

• Long backtracking
• Broken picking rhythm
• Multi-aisle zig-zagging

Result: pick routes balloon in length even when the order size doesn’t.

3. Upper-Level Picks for Tiny Top-Ups

Operators take a reach truck up to Level 6 or 7… just to grab a few units.

This happens when:

• Lower-level pallets aren’t reserved for small picks
• FEFO pushes picks to less convenient locations
• No prioritization of low-effort pick faces

Every lift adds minutes, equipment congestion, and fatigue.

4. Pallet Fragmentation: Multiple Open Pallets for the Same SKU

When pickers open new pallets before finishing existing ones, the SKU gets scattered across the warehouse.

Consequences:

• 3–5 pickable positions for the same SKU
• More splits
• More touches
• More manual checks

Once fragmentation begins, inefficiency accelerates.

5. No Coordination Between Putaway and Picking

One of the biggest hidden drivers of chaos is poor synchronization between putaway logic and picking demand.

Without feedback loops:

• Pallets get stored in low-velocity zones
• High-velocity SKUs end up far from pick paths
• Replenishments create new, unnecessary pallet positions
• Future pick routes become unpredictable

This is the root cause of most pallet spread issues.

How Hopstack Tackled the Problem

Fixing high-bay B2B picking isn’t about speeding up workers — it’s about removing the structural inefficiencies that force them into long routes, unnecessary lifts, and fragmented pallet picks. Hopstack approached the problem by redesigning the logic behind where inventory lives and how orders are executed, not just how fast people move.

1. Cutting Splits: Fewer Locations per Line

Hopstack’s first focus was consolidating pickable inventory.
Instead of allowing a SKU to be pulled from 3–5 different pallet positions, the system:

• Identifies optimal pallet locations
• Directs picks toward consolidated stock
• Avoids creating new partial pallets
• Reduces pallet spread at the source

This immediately cuts down on mid-route detours and reach-truck cycles.

2. Preferring Closer, Low-Effort Picks

The system automatically prioritizes:

• Ground-level and low-level pick faces
• Locations nearest to the picker’s current path
• High-velocity zones

By pushing small or partial picks to the most accessible pallet face, Hopstack eliminates unnecessary vertical lifts and reduces travel time significantly.

3. Co-Locating the Order: No Late Aisle Surprises

One major inefficiency was late introductions of new aisles mid-route.
Hopstack addresses this by:

• Mapping the entire order before execution
• Grouping picks tightly by aisle and zone
• Ensuring all required aisles appear early and predictably

This creates smooth, linear routes instead of long, irregular zig-zags.

4. Intelligent Putaway Based on Pick Velocity

The biggest shift came from linking putaway decisions to future pick patterns.
Hopstack uses velocity and historical pick behavior to suggest the ideal pallet locations, ensuring:

• High-velocity SKUs are stored in accessible positions
• Slow movers go deeper or higher in the warehouse
• Future picks don’t require avoidable lifts
• Pallet spread is prevented before it begins

This coordination between putaway and picking stabilizes location patterns and keeps the warehouse predictable.

The Result: Higher Throughput Without Hiring More Labor

By optimizing splits, travel, vertical effort, aisle sequencing, and putaway logic, Hopstack helped the 3PL:

• Ship 1M+ pieces in the first month
• Prepare to scale to 3M pieces/month
• Maintain the same labor force

The improvement didn’t come from working faster — it came from eliminating the system-level inefficiencies that made work harder.

The Broader Impact: Scalable Picking Without Scaling Labor

Traditional B2B warehousing operates on a linear model: as volume grows, labor must grow with it. More orders mean more travel, more lifts, more pallet touches, and more time spent navigating scattered locations. Even incremental increases in throughput typically require new headcount just to maintain service levels. This is why most 3PLs and B2B distributors see labor as their largest—and least flexible—cost center.

Hopstack’s approach breaks this linear relationship by attacking the structural inefficiencies that force labor expansion in the first place. When slotting, putaway, and picking are coordinated through intelligent logic, the system reduces the two biggest drivers of labor consumption: travel time and vertical effort.
Fewer splits, fewer aisles, fewer lifts, and more predictable routes mean that each picker can handle significantly more volume without working faster or longer.

This shift has a direct operational and financial upside:

• Higher throughput with the same workforce
• More consistent pick-paths and cycle times
• Reduced overtime and temporary labor dependency
• Lower cost-per-pick and cost-per-order
• Greater ability to absorb peak seasons without disruption

For 3PLs, distributors, and high-bay B2B fulfillment centers, the payoff is substantial. Instead of scaling labor to chase volume, operations can scale throughput through better coordination and smarter inventory placement. The result is a warehouse that grows efficiently, predictably, and profitably—without the constant need to add people to keep up.

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