Warehouse Automation Approval Checklist: What Buyers Should Confirm Before Signing

A warehouse automation approval checklist should protect the buyer from signing a project that looks strong in a demo but weakens once it meets real floor conditions.

Most warehouse automation projects do not fail because the technology cannot work. They struggle because the approval process skips practical questions: where the workflow starts and ends, which data must be captured, who owns exceptions, how integration will be tested, what operators do when something fails, and which pilot evidence proves the rollout is ready.

For buyers evaluating a parcel dimensioner, freight dimensioner, inspection workflow, receiving control point, or shipping automation project, the checklist should make hidden assumptions visible before the contract is signed.

Confirm the problem the automation must solve

Start with the operating problem, not the product category.

"We need automation" is not specific enough for approval. A useful buying case states which workflow is failing and how the warehouse will know the project fixed it.

Examples:

• manual measurement slows parcel manifest close and creates carrier billing adjustments
• receiving inspections miss damage evidence before putaway release
• pallet dimensions are missing or inconsistent, weakening storage billing and slotting decisions
• shipping quality control catches problems too late to recover before carrier pickup
• supervisors spend too much time resolving unlabeled, unmatched, or poorly documented exceptions
• finance cannot research disputes because records are spread across photos, spreadsheets, emails, and system notes

The approval should name the primary control point:

"This project will capture dimensions, weight, images, shipment identifiers, and exception status before outbound parcels reach manifest close."

That sentence is more useful than a feature list because it connects the investment to a decision the warehouse must make every day.

Check whether the data record is complete

Automation value often depends on the record, not only the action.

A station that measures quickly may still disappoint if the warehouse cannot retrieve the record later. An inspection workflow may look polished but fail a claim if photos are not tied to the shipment, PO, pallet, operator, timestamp, or reason code. A shipping audit may flag problems but create extra work if the exception status does not reach the system where supervisors make release decisions.

Before approval, define the required record:

• order, shipment, carton, pallet, license plate, PO, ASN, SKU, customer, vendor, or carrier identifiers
• dimensions, weight, unit of measure, and measurement status
• image evidence when damage, overhang, label placement, packaging condition, or claim support matters
• timestamp, station, site, operator, shift, and device
• expected value versus captured value when comparison is part of the control
• exception reason, owner, age, action taken, and final disposition
• override history with user, timestamp, reason, and approval level
• retention and export requirements for operations, finance, customer service, billing, or claims

If a required field is missing, decide whether it is a process gap, integration gap, device limitation, or reporting gap. Do that before signing, not during the first week of go-live.

For a deeper structure, compare the checklist with your dimensioning data requirements.

Assign integration ownership before the quote is approved

"Integrates with our WMS" is not a complete requirement.

Buyers should confirm the integration in operational terms:

• Which system provides the identifier before the automation step?
• Which system receives the completed record?
• Does the data need to move before rating, label print, putaway, manifest close, invoice creation, or claim review?
• What happens if the destination system rejects the update?
• Who monitors failed transactions?
• How are duplicate scans, unmatched records, manual corrections, and retries handled?
• What is the fallback process during downtime?
• Who owns support: vendor, internal IT, operations, system integrator, or a named project owner?

The timing matters. A nightly export may be enough for reporting. It is not enough if the warehouse needs dimensions before rate shopping or exception holds before carrier pickup.

The owner matters too. If operations assumes IT will monitor failed updates, and IT assumes the vendor portal owns them, exceptions will age without accountability. A buyer-ready approval names the owner for each failure mode.

Design exceptions before operators find them

Clean transactions make good demos. Exceptions determine whether the workflow survives.

Every approval checklist should include likely exception scenarios:

• unreadable, missing, duplicated, or wrong barcode
• damaged carton, torn wrap, crushed corner, unstable pallet, or visible overhang
• item outside the measurable range
• weight or dimensions outside expected tolerance
• failed image capture, failed measurement, or failed scale read
• network timeout, API rejection, or system lookup failure
• operator needs to remeasure, relabel, repack, split, hold, or release with approval
• supervisor override is required before the order can move

For each scenario, define the action. Does the item stop? Can it move with a warning? Is evidence still saved? Who owns the review? Is there an aging queue? Can a supervisor see which exceptions threaten the next cutoff?

A practical requirement sounds like this:

"Failed measurements and identifier mismatches must create a searchable exception record with reason code, image evidence when available, owner, aging, and approved release path."

That requirement prevents the automation from becoming a black box that operators bypass when the floor gets busy.

Test the business case against real adoption

Many approval packets include a payback number but skip the adoption assumptions behind it.

Before signing, test whether the financial case still works under realistic conditions:

• What percentage of eligible volume will actually pass through the workflow?
• How long will training take by shift?
• How many transactions are expected during normal, peak, and low-volume periods?
• What capture rate is required for the savings to appear?
• How much exception labor remains after automation?
• Which downstream teams will save time, and how will that time be measured?
• What support load is expected during the first 30, 60, and 90 days?
• What happens to payback if the rollout is delayed one month?

Use conservative assumptions for the approval model. If the project still works with slower ramp, modest exception reduction, and realistic support time, leadership can trust the case more than a perfect-scenario spreadsheet.

For buyer teams building the financial side, compare the approval checklist with your warehouse automation payback period model and warehouse labor standards for automation pilots.

Define pilot evidence before go-live

The pilot should answer the rollout question, not simply prove that the equipment turns on.

Define acceptance criteria before the project starts:

• capture rate for eligible parcels, pallets, cartons, or freight
• transaction time for clean work and exception work
• percentage of records matched to the correct identifier
• exception rate, aging, owner response, and final disposition
• image and data retrieval for audit, billing, claims, or customer service
• integration success rate and retry handling
• operator adoption by shift
• bypass reasons and supervisor overrides
• safety, congestion, station placement, and training issues
• support tickets and unresolved blockers

The buyer should know what happens after the pilot. Expand, adjust, delay, change placement, change rules, improve integration, or stop. A pilot without a decision rule becomes a demo with extra steps.

Use the checklist to reduce rollout surprises

Warehouse automation approval should make the project clearer before money is committed.

The checklist does not need to be complicated. It needs to confirm the workflow problem, the required record, the integration path, the exception design, the adoption assumptions, and the evidence that will prove readiness.

Sizelabs helps warehouse teams connect dimensions, weight, images, identifiers, and exception status at the point where automation needs to create operational and financial proof. If your team is close to signing, use the approval process to test the real workflow before the rollout has to absorb every assumption.