Inventory
Metrc Inventory Control Statistics 2026
A source-based control model for comparing physical cannabis inventory with tracked records and documenting exceptions.
Key takeaways
- Inventory accuracy is a comparison result, not a universal industry percentage.
- Every exception needs a product identifier, count method, cause status, owner, and approval path.
- Virginia rules and Metrc documentation should be read together for current scope.
Inventory accuracy is the result of a defined comparison. It is not a universal cannabis percentage. Virginia's Cannabis Control Authority laws page is the jurisdiction starting point [S1]. The Virginia Administrative Code processor chapter provides operative text for its scope [S2].
| Exception field | Minimum evidence | Avoid |
|---|---|---|
| Product and package | Identifier and location | Name-only match |
| Count method | Who, when, how | Unstated count |
| Variance | Units and direction | “Inventory issue” |
| Cause status | Known, pending, unknown | Guessing cause |
| Approval | Reviewer and action | Silent adjustment |
Metrc's official resources describe system materials [S3]. The CCA reports page provides public program context [S4]. The NIST CSF supports access and audit thinking [S5]. The NIST Privacy Framework applies when records contain personal data [S6].
Use cycle-count frequency, absolute variance units, variance value, repeat exception rate, and time to closure as local measures. Define denominators and preserve unresolved items. The GAO data reliability guide supports checking completeness and accuracy [S7]. The National Archives records schedules provide retention context [S8]. The FDA recall guidance shows why lot and disposition evidence matter in another regulated domain [S9]. The IRS recordkeeping page adds financial record context [S10].
Pair with inventory accuracy benchmarks and product recall notification research. This article is not regulatory advice.
Frequently asked questions
What is a good inventory accuracy target?
Set it from the defined process and risk, then publish the denominator and exception treatment.
Is a variance automatically a compliance violation?
Not from the statistic alone. Investigate the facts and controlling rules.
Who can approve a correction?
The role named by current policy and applicable rules, with the approval recorded.
Sources
- [S1] Virginia CCA, Laws, accessed August 10, 2026.
- [S2] Virginia Administrative Code, Processors, accessed August 10, 2026.
- [S3] Metrc, Resources, accessed August 10, 2026.
- [S4] Virginia CCA, Reports, accessed August 10, 2026.
- [S5] NIST, Cybersecurity Framework, accessed August 10, 2026.
- [S6] NIST, Privacy Framework, published January 2020.
- [S7] GAO, Data reliability, published December 2019.
- [S8] National Archives, Records schedules, accessed August 10, 2026.
- [S9] FDA, Recalls, accessed August 10, 2026.
- [S10] IRS, Recordkeeping, accessed August 10, 2026.
Conclusion
Inventory research earns trust by showing the comparison method and the exception path. A percentage without those details is not a control.
Reviewed by the DispensaryVA editorial team on 2026-08-10.