Scan the bin
An employee scans every unit physically present. No manual list to work from.
Inventory accuracy case study
From manual cycle counts to real-time reconciliation.
A barcode-driven workflow that compares physical inventory to the ERP on every scan — and reconciles the difference automatically, with no separate cleanup step.
Prior operating experience led by Built-N-AI founder Casey Jackson. Company identity is omitted.
Results at a glance
Real-TimeBin reconciliationReconciled the moment scanning finishes
AutomaticMissing inventoryMoved to non-sellable holding instantly
AutomaticMislocated inventoryERP location corrected on scan
ZeroManual list comparisonsEmployee scans; the system compares
IntegratedPicking overridesConnects directly to FIFO exception handling
FullAudit trailEvery adjustment tied to who, what and when
The challenge
The hard part isn’t counting. It’s reconciling.
Cycle counting sounds simple: count what’s physically in a bin and compare it with what the ERP says should be there. The difficult part is resolving the discrepancies — deciding where missing inventory belongs in the system, whether it should remain sellable, who updates its status, and how to correct items that are physically in one bin but expected in another.
Under the existing process, much of that reconciliation was manual and cumbersome. We wanted the physical count itself to drive the reconciliation, instead of a person reconciling it after the fact.
“The employee captures reality. The system reconciles itself to reality.”
This is grounding in practice — the system’s records don’t drift from what’s physically on the shelf.
The solution
A barcode scan replaces the list.
We built a barcode-driven cycle-counting workflow around each individual unit. Instead of comparing lists by hand, an employee goes to a bin and scans every unit physically present — the system handles the comparison and the reconciliation.
If a unit was expected in the bin but wasn’t scanned, the system marks it missing and moves it to a controlled non-sellable holding status, so it stops being promised to another customer while its location is unknown.
A fully reconciled bin
- Inventory expected and present — confirmed
- Inventory expected but missing — held, non-sellable
- Inventory present but expected elsewhere — location corrected
- Every exception — logged for follow-up
- Bin status — fully reconciled at scan-complete
Scan Bin → Compare to ERP → Identify Exceptions → Reconcile Inventory.
The opposite problem is handled in the same pass: if a unit is physically in the bin even though the ERP believes it belongs somewhere else, the scan catches the mismatch and updates the location automatically.
Connected, not separate
Tied directly to picking, not a standalone system.
The cycle-counting workflow complements the digital picking process. If a picker can’t find the FIFO-recommended unit in its expected bin, they use an approved override and select another. The missing unit is automatically placed in non-sellable holding — and cycle counting is what later finds and reconciles it.
If that unit turns up in another bin during a count, its location is corrected and it’s returned to an appropriate sellable status — closing the loop between picking exceptions and inventory accuracy.
“Don’t make the employee reconcile the system to reality. Let the employee capture reality, and make the system reconcile itself.”
How it works
Five steps, one scan at a time.
System compares
The scan is checked against what the ERP expects to be in that bin.
Missing inventory held
Anything expected but not scanned is marked missing and moved to non-sellable holding — the edge cases the system is built to catch, not its failure mode.
Mislocated inventory corrected
Anything scanned but expected elsewhere has its ERP location updated automatically.
Bin reconciled
Once scanning is done, the bin is fully reconciled — no follow-up cleanup step.
Before & after
The reconciliation model changed.
Before
Manual comparison of a printed or exported list to the bin
After
Employee scans; the system compares automatically
Before
Missing inventory often stayed listed as sellable
After
Automatically moved to non-sellable holding on discovery
Before
Mislocated inventory required a separate correction step
After
Location corrected automatically at time of scan
Before
Picking exceptions and cycle counts were disconnected
After
Integrated — a picking override feeds directly into reconciliation
Before
Limited traceability on inventory adjustments
After
Complete audit trail for every adjustment
Business impact
Better accuracy without a bigger team.
Reconciliation
Bins reconcile themselves at the moment scanning finishes.
Fulfillment problems
Less phantom inventory promised to customers who can’t actually receive it.
Exception handling
Picking and cycle counting share one workflow instead of two disconnected processes.
Traceability
Every adjustment is tied to a person, an action and a timestamp.
Cycle counts
Far less manual reconciliation per bin, per count.
Founding Client Program — 3 spots
Prove it on your data before you commit.
This workflow was built and proven inside real operations, not sold before it was tested. The first three external clients get founding-client pricing in exchange for a case study and testimonial.
Step 1 — Pilot
$1,800
A 2-week pilot reconciling a handful of your bins against your ERP, proving the scan-and-reconcile workflow on your own data. Credited toward the full build if you move forward.
Step 2 — Full build (founding-client rate)
$7,500
The full barcode-driven reconciliation workflow integrated into your ERP, scoped to your warehouse. Founding-client pricing for the first 3 external clients only.
Key takeaway
Better inventory accuracy without a bigger inventory team.
The system does the reconciliation work a person used to do after the count — identifying what’s missing, correcting what’s mislocated, and holding what can’t be trusted until it’s found.
The employee captures reality. The system reconciles itself to reality.