How to audit inventory shrinkage on Starch
Inventory shrinkage is the gap between what your records say you have and what's actually on the shelf, in the warehouse, or at your co-packer. That gap has real causes — theft, spoilage, receiving errors, mislabeled lots, damaged product written off inconsistently — and finding them requires reconciling physical counts against system records in a way that's repeatable, not just done once a quarter when something looks off. What this workflow looks like in practice depends heavily on your setup: a single-location retailer running cycle counts is doing a different version of this than a CPG brand tracking lot-level shrinkage across three 3PLs and a co-manufacturer. The data sources differ, the tolerances differ, the audit triggers differ. On Starch, the end state is a shrinkage dashboard that shows you your actual loss rate by location, SKU, and cause — updated on whatever cadence matches your operation — plus automatic flags when a discrepancy crosses your threshold, so you're not hunting for problems in a spreadsheet at month-end. Your team sees the number, sees what's driving it, and has the context to act. The two Starch apps most relevant here — Inventory Planner and Lot Tracker — are currently in development; you can request beta access for either. For the financial side of shrinkage (what it's costing you in real dollars, month over month), Transaction Insights pulls directly from your connected bank accounts and flags anomalies automatically.
Why it matters
Shrinkage that goes unmeasured compounds. A 2% loss rate that feels manageable in January becomes a material variance by Q4 — and if you can't attribute it to a cause, you can't fix it. Retailers and distributors increasingly ask for documentation. Insurers want evidence of controls. And internally, misreported inventory distorts your reorder math, your COGS, and your cash position. Getting this right means your numbers are trustworthy, your audits are fast, and you're not discovering a $40,000 variance the week before a fundraise.
Common pitfalls
Counting without a baseline: running a cycle count is useless if your system-of-record quantity was already wrong before you started. Attributing everything to 'shrinkage' instead of categorizing by cause (receiving error vs. spoilage vs. theft vs. admin error) — you can't fix what you haven't separated. Reconciling on a monthly cadence when product moves daily, so by the time you find the discrepancy the trail is cold. And conflating unit loss with dollar loss: a high shrink rate on a low-margin SKU is a different problem than the same rate on your hero product.
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