---
title: "Warehouse Measurement Protocol | Fortune AI"
description: "A first-party protocol for measuring dock-to-stock time, forklift utilization, and inventory handoffs with WMS or TMS records and existing camera views"
canonical: https://www.fortuneai.app/resources/warehouse-measurement-protocol/
language: en
---

[Resources](https://www.fortuneai.app/resources/) Warehouse measurement protocol

# Warehouse measurement protocol

Define the event, evidence, sample, acceptance rule, and operating limit before comparing a warehouse result

First-party measurement method

## Benchmark the site against its own accepted baseline

This protocol defines how Fortune AI and an operations team can create a reviewable warehouse baseline from operating records and existing camera views. It is a measurement framework—not a customer case study, industry average, or performance guarantee.

Warehouse operations baseline worksheet

Record the scope, sample, exclusions, baseline, target, and acceptance decision for each metric.

[Download CSV worksheet](https://www.fortuneai.app/assets/resources/warehouse-operations-benchmark-worksheet.csv)

Metric definitions

## Three bounded warehouse measures

| Measure | Start and end event | System record | Camera evidence | Reported result |
| --- | --- | --- | --- | --- |
| Dock-to-stock | Unload begins to accepted putaway or receiving close | TMS arrival, ASN, receipt, location scan | Dock, staging, and agreed putaway handoff views | Median, 90th percentile, and exception clips by shift |
| Forklift utilization | Agreed shift window; classify active handling, loaded travel, empty travel, and waiting | Shift roster; optional telematics or task events | Only the zones covered by approved camera views | Minutes and share of observed time by activity state |
| Inventory handoff verification | Expected shipment or putaway event compared with observed physical handoff | Item, dock, vehicle, location, and event timestamp from WMS | Timestamp-aligned pallet, vehicle, dock, or location evidence | Match, mismatch, or uncertain—with footage and resolution state |

Evaluation sample

## Agree on the test before reviewing the result

- Freeze the definition. Document eligible events, start and end states, zones, shifts, and exclusions.
- Select representative footage. Include normal volume, peak periods, changeovers, occlusion, and at least one known exception when available.
- Build the acceptance set. The worksheet starts with 100 eligible events across at least three representative shifts when volume permits. Lower-volume sites should review all available events and report the count.
- Compare independently. A team reviewer labels the acceptance set before comparing it with the camera-derived measure.
- Decide explicitly. Publish the event count, coverage, disagreements, uncertain cases, and the pre-agreed acceptance threshold.

## Decision rule

There is no universal accuracy claim. Each deployment needs an acceptance threshold appropriate to the operating decision and the cost of a missed or incorrect event.

Results outside camera coverage, with unresolved timestamp drift, or without the required WMS/TMS record remain unmeasured or uncertain—not silently estimated.

WMS / TMS + camera

## Join records only at an agreed operating event

### Minimum system fields

- Stable event or shipment identifier
- Event type and timestamp with timezone
- Dock, lane, vehicle, or location identifier
- Expected state and later resolution state

### Camera-side record

- Camera identifier and covered zone
- Observed start and end timestamp
- Measurement state and uncertainty reason
- Supporting clip reference and retention status

### Operational output

- Matched event and evidence link
- Duration or activity classification
- Exception owner and review status
- API, MCP, report, or WMS/TMS write-back result

Reporting limits

## State what the measure cannot see

- Camera-derived results cover approved views and time windows, not the entire facility by default.
- Occlusion, lighting, camera movement, timestamp drift, and incomplete source records can produce uncertain or excluded events.
- Forklift utilization is an activity measure within covered zones; it is not worker identity, productivity scoring, or continuous equipment telematics.
- Inventory handoff verification checks bounded state changes. It does not replace the WMS or claim continuous item-level tracking.
- Any public case study or performance benchmark must use verified customer permission, sample details, and measured results. None are implied here.

Published by Fortune AI Technologies · Version 1.0 · September 27, 2026