The Cycle Count Intelligence Toolkit reads the count export you already run and turns twelve weeks of history into repeat offenders, drift, dollar impact, and next week's count list. In a spreadsheet, not a BI project.
Works with exports from Solochain, NAV / Business Central, D365, Fishbowl, and any WMS that produces a CSV.
| SKU | Bin | Misses | Net | Pattern | Priority |
|---|
Most teams count, adjust, and move on. The pattern is in the history. The toolkit keeps it, scores it, and turns it into a count plan.
Record accuracy by zone, bin, ABC class, and counter. Tolerance-aware, so a one-unit miss on a $2 fastener isn't scored like a pallet of finished goods.
SKUs and bins that miss count after count get flagged automatically, with a miss rate over the trailing window and the last three results.
Separates a bin that is slowly bleeding units (drift) from one that swings both ways (volatility). Different problems, different fixes.
Tag each miss as receiving, pick, put-away, unit-of-measure, or transfer. Tags roll up so you can see which process is actually generating the variance.
Every variance priced at unit cost. Shrink, overage, and net exposure by zone, so the conversation with ops or the customer is about dollars, not units.
Instead of counting everything on a fixed rotation, the toolkit ranks bins by risk and builds next week's count list around the ones most likely to be wrong.
Any CSV with a SKU, location, system quantity, counted quantity, and date. Unit cost is optional but unlocks the dollar views.
Paste or upload. Columns are mapped once and remembered. Each import appends to the history, so the trends get sharper every week.
Open the offender list, tag root causes, pull the risk-ranked schedule, and hand the count sheet to the floor.
Move the sliders to your numbers. The estimate uses the same logic the toolkit applies to your real history.
Assumes risk-based scheduling trims 30% of low-risk counts, and floor labor at $22/hour for payback. Your real numbers come from your own history once imported.
The toolkit lives in the spreadsheet your inventory lead already has open. No dashboards to learn, no analyst to wait on.
The real analysis engine, running on a synthetic 12-week history for a 48-bin, 4-zone warehouse. Hover the charts, sort the table, tag root causes.
In the demo the sample file is already loaded. The first slice of it is below.
sku item numberzone / bin locationcount_date one row per countsystem_qty book qty at count timecounted_qty physical countunit_cost optional, enables $ viewscounter optional, enables by-person accuracyDrift is the average signed variance per count. A steady negative number is a bin losing units every cycle: usually mis-picks, unrecorded scrap, or a UoM mismatch.
Volatility is the spread. High spread with near-zero drift means counts swing over and under: a shared bin, a put-away discipline problem, or two people counting differently.
Opens your mail app with a pre-filled note. Early-access buyers lock in $149 before public launch. Runs in Google Sheets or Excel you already have; your data never leaves your account.
Small 3PLs and single-site warehouses running cycle counts weekly, with 500 to 20,000 SKUs, and nobody on staff whose job is "inventory analytics."
Multi-site networks with a BI team, or operations that don't cycle count yet. If that's you, start a count program first; the toolkit is what you add once the data exists.
Champ Systems is a one-person software studio in Fort Worth, Texas, and the Toolkit is its first product. It's built by someone who has spent his career on the operations side of enterprise systems: supporting the people who use them, troubleshooting the integrations behind them, and turning ERP and WMS data into answers when the reports didn't exist yet. The toolkit is the tool that should have been on the shelf the whole time.
No, and that's deliberate. It reads the CSV export your WMS already produces, so there's no integration to approve, no credentials to hand over, and nothing to break when your WMS updates.
v1 runs in Google Sheets with an Apps Script analytics layer. An Excel add-in is on the roadmap; early-access buyers get it at no extra cost when it ships.
You set it per ABC class or per SKU: a unit threshold, a percentage, or a dollar threshold. Counts inside tolerance are hits; everything else is a miss that feeds the offender and risk logic.
Everything except the financial impact lens still works. Add a cost column later and the history reprices itself.
No. The analysis runs inside your own spreadsheet account. Nothing is uploaded to Champ Systems; we never see your inventory data.