Optimizing Pack Size To Reduce Fulfillment Cost And Improve Picking Efficiency

Pack Size The number of units grouped together within a defined packaging level or orderable pack.

Optimizing pack size is a lever warehouses and shippers use to reduce unit handling costs, lower shipping spend, and improve picking speed. The goal is to choose pack configurations that align with order profiles, storage constraints, and carrier pricing. Small changes in pack size (for example changing from 10-unit inner packs to 12-unit inner packs) can change pallet cubes, pallet layers, and thereby the freight class or zone pricing for LTL shipments.

Decisions about pack size should be data-driven. Analyze order history to understand single-item order rates, average order quantities per SKU, and frequency of mixed-SKU orders. Pack-size optimization is not purely about maximizing case count — it balances customer convenience (e.g., multipacks for retail), pick efficiency (minimizing broken cases), and transportation efficiency (maximizing cube utilization).

Practical Steps For Pack-Size Optimization

Start with an audit of current packaging and order data. Use these inputs to model scenarios and run small pilots. Optimization typically follows these steps:

• Data Review: Identify top-moving SKUs, average picks per order, and percentage of orders fulfilled by eaches versus cases.
• Simulation: Use cartonization and palletization software or WMS modules to simulate how alternate pack sizes affect packing efficiency and freight cube usage.
• Pilot Test: Implement pack-size changes on a subset of SKUs and measure picking time, packing time, and shipping cost changes.
• Scale: Roll out successful configurations to similar SKUs or categories.

Key Tradeoffs To Consider

When you change pack sizes you trade off assembly cost and storage for downstream efficiency. Larger pack sizes reduce per-unit shipping and handling cost but increase the chance of overstocks and require more upfront storage space. Smaller pack sizes reduce storage burden and are more consumer-friendly but increase pick density and per-unit handling costs.

• Storage Density vs Flexibility: Bigger packs improve density but reduce flexibility for mixed orders.
• Handling Cost vs Packaging Cost: More complex packaging (e.g., inner packs, trays) adds packaging cost but can lower labor at pick-and-pack.
• Transport Cube Efficiency: Adjust pack sizes to maximize pallet layers while keeping within carrier weight and dimension limits.

Integration With Systems And Suppliers

Optimization requires coordination. Suppliers must be willing to change carton or inner pack counts; your item master must accept multiple GTINs if new packaging levels are introduced. Update EDI/ASN standards with trading partners so inbound notifications reflect the new pack sizes and carriers can bill accurately.

Example Initiative

A medium-sized CPG company analyzed its order profile and found that 70% of online orders contained multiples of 6 units. The company adjusted its inner pack from 8 units to 6 units and created a new case size that stacks optimally on a standard pallet layer. As a result, they reduced break-pack labor by 18%, lowered dimensional weight charges on average by 6%, and reduced returns caused by damaged goods because fewer units were rehandled.

Implementation Checklist

• Measure Baseline: Record current labor minutes per pick, freight spend per pallet, and damage rates before any change.
• Standardize Naming: Update item master fields and vendor specs so new pack-size values are unambiguous.
• Engage Carriers: Confirm how changes affect freight classification and dimensional weight billing.
• Monitor KPIs: Track pick rates, order accuracy, freight costs and inventory turns post-change.

In short, the Pack Size is a tactical lever in fulfillment that, when optimized, reduces handling and transport costs while improving throughput. Treat pack-size changes as cross-functional projects that include purchasing, vendor management, operations, and systems to realize measurable benefits.