The S.A.L.T. Framework: Four Measures That Determine Fulfillment-Center Performance

Warehouse space utilization: value the cube, not only the floor

An analysis based only on floor area ignores the vertical volume between the top of product and the usable clear height. Leading operators track warehouse utilization, pallet-footprint efficiency and cost per cubic foot, not just occupied square footage. The paper separates the product cube (volume physically occupied by inventory and its container) from the facility cube (usable 3D volume after structure, fire protection, access and clearances). The gap between the two is the opportunity.

Illustrative only. Sources: Cushman & Wakefield 2025 construction cost guide; CBRE Chicago Q2 2026; WARE Commercial Real Estate NYC Q2 2026. Full citations are in the white paper.

The paper also covers the active-pick-face problem (a "full" slot may hold only 60 to 80% of its theoretical cube) and how cubic ASRS designs like Attabotics reclaim horizontal and vertical void through tote binning and storage that extends into 35 to 45 foot clear heights while preserving direct robotic access.

Order accuracy: protect truth from receipt to customer

A correct pick cannot rescue incorrect receiving data, and a correct order can still fail when it gets the wrong shipping label. The paper maps where errors are created, inherited, detected, corrected or allowed to escape across five zones: master data, transactions, human picking, work in process, and consolidation and packing.

It also makes error economics visible. Cost per error adds detection, investigation, rework, replacement, reshipping, returns, customer service, lost margin and customer impact. A discrepancy corrected at induction takes seconds. One found after delivery can require a return authorization, replacement inventory and premium freight. That is why order accuracy contributes directly to labor and throughput.

Warehouse labor productivity: convert walking into productive work

Picking labor is easier to improve when the hour is decomposed into three activities: setup and discharge, travel, and bin-face time. The same logic applies to receiving, putaway, replenishment and inventory control.

Eliminating travel does not automatically create a 50% productivity gain, but it creates the capacity for one. The paper explains how goods-to-person automation attacks the nonproductive portion of the hour, and which labor metrics to track: lines per paid hour, productive-time percentage, touches per unit, training time and ergonomic exposure rather than peak picks per hour alone.

Fulfillment throughput: combine bandwidth and velocity

Bandwidth is the quantity of resources available: people, robots, ports, workstations and downstream capacity. Velocity is how quickly each resource completes useful work. A wide fire hose at low flow fills a pail at about the same rate as a narrow garden hose at high velocity. Warehouse capacity behaves the same way.

The paper follows a three-line e-commerce order through a conventional warehouse (items hundreds of yards apart, arriving at packing at different times) and through a goods-to-person flow where bins are sequenced to a stationary operator. It closes with the throughput discipline every buyer should apply: compare sustained peak-hour output and end-to-end order cycle time, never a robot's maximum speed or a workstation's short-duration demo rate.