Most companies don’t struggle with inventory because they lack software. They struggle because they don’t know where to look.
On paper, the system is “working.” Stock levels exist. Orders ship. Reports run.
But beneath that surface, small signals quietly pile up—signals that explain why teams stop trusting their numbers, why stockouts keep happening, and why inventory always feels harder than it should.
The good news? You don’t need more dashboards.
You need to pay attention to a small set of overlooked inventory data points that reveal where things are breaking before the damage spreads.
This article walks through the inventory data most teams ignore—and exactly how to use it to fix real problems.
Look for Signals, Not Perfect Reports
Before diving in, one important rule:
You are not looking for perfection.
You are looking for patterns.
Every warehouse has errors. Every system has edge cases. What matters is:
- Which SKUs show up again and again
- Which workflows create the most “fixes”
- Which problems quietly repeat every week
The data below works best when reviewed on a simple cadence:
- Weekly: fast signals, quick corrections
- Monthly: trends, policy changes, training needs
1. Inventory Adjustments by Reason Code (and by User)
Inventory adjustments are one of the clearest signals that reality and the system disagree.
WHY IT MATTERS:
Adjustments don’t just fix numbers—they tell a story about why inventory went wrong in the first place.
What “bad” looks like
- The same SKUs adjusted repeatedly
- Vague reasons like “correction” or “unknown”
- Large adjustments tied to the same user, shift, or process
Common causes
- Receiving shortcuts
- Unit-of-measure confusion
- Pickers bypassing scans
- Manual overrides in urgency moments
What helps
- Require meaningful reason codes
- Review adjustments weekly, not quarterly
- Pair adjustments with short retraining, not punishment
This is one of the fastest ways to regain trust in systems like (Fishbowl) or (Katana).
2. Cycle Count Results (Variance %, Not Just Pass/Fail)
Most teams cycle count—but very few use the results.
WHY IT MATTERS:
Cycle counts don’t just confirm accuracy. They expose where accuracy breaks down.
What to watch
- Variance percentage over time
- SKUs or bins that are “always wrong”
- High-dollar items with small but consistent errors
Common causes
- Poor bin labeling
- Shared locations
- Counting while picks are still happening
What helps
- Lock bins during counts
- Track accuracy trends, not just outcomes
- Focus on the worst 10% of items, not all of them
Cycle counting is most effective when it feeds back into process—not when it’s treated like a checkbox.
3. Negative Inventory and Backdated Transactions
Negative inventory is a silent killer.
WHY IT MATTERS:
Once inventory goes negative, availability becomes fictional. Reorder points fail. Sales overpromise. Planning collapses.
What “bad” looks like
- Frequent negatives on the same SKUs
- Transactions posted out of order
- Inventory “fixed later” instead of prevented
Common causes
- Shipping before receiving is finalized
- Integration timing gaps
- Too many users with override permissions
What helps
- Enforce transaction order
- Tighten permissions
- Monitor integration sync timing, especially with ecommerce
Negative inventory is less about mistakes—and more about missing guardrails.
4. Stockouts and the “Missed Sales” Proxy
If you don’t track missed sales directly, you still have signals.
WHY IT MATTERS:
Stockouts don’t just lose revenue—they erode trust with customers and sales teams.
Proxy signals to watch
- Backorders
- Partial shipments
- Expedited replenishment orders
- Emergency transfers
Patterns that matter
- Same category stockouts
- Seasonal repeats
- One supplier always involved
What helps
- Revisit lead times quarterly
- Adjust reorder points based on reality, not history
- Use real demand, not averages
Inventory visibility isn’t knowing what you had—it’s knowing what you can sell today.
5. Aged Inventory (Dead Stock and Slow Movers)
Dead stock rarely announces itself. It just sits there.
WHY IT MATTERS:
Old inventory ties up cash, space, and attention—often without anyone noticing.
What to track
- 0–30 days
- 31–90 days
- 91–180 days
- 180+ days
What “bad” looks like
- SKUs untouched for months
- “We might need that someday” logic
- Overstocked safety buffers that never shrink
What helps
- Discounting or bundling strategies
- Supplier return conversations
- MOQ renegotiations
- Clear write-off policies
Aged inventory is a planning problem, not a warehouse one.
6. Shrinkage Signals (Expected vs. Actual Usage)
Especially critical for manufacturing and kitting environments.
WHY IT MATTERS:
When expected usage and actual usage drift apart, something is leaking—time, material, or accuracy.
What to watch
- BOM usage vs. picks
- Consistent over-consumption
- Scrap that never gets logged
Common causes
- Untracked scrap
- Rework without adjustments
- Loose material controls
What helps
- Clear scrap workflows
- Kitting discipline
- Periodic BOM audits
Systems like Katana or Cin7 shine when usage data is honest.
7. Location Accuracy and “Temporary” Bins
If the system doesn’t know where something is, it might as well not exist.
WHY IT MATTERS:
Inventory without a reliable location slows picking and increases errors.
Red flags
- “TEMP,” “FLOOR,” or “RECEIVING” bins that never clear
- Items floating without assignments
- Frequent “found it later” moments
What helps
- Enforced put-away steps
- Scanning at movement points
- Regular bin audits
Location discipline pays off faster than most teams expect.
8. Supplier Lead Time Variance
Your reorder points are only as good as your lead times.
WHY IT MATTERS:
If suppliers slip, your system still believes the promise—not the reality.
What to track
- Promised vs. actual receipt dates
- Seasonal variability
- Partial shipment patterns
What helps
- Update lead times based on averages, not contracts
- Add buffers where volatility exists
- Identify alternate suppliers early
This data quietly improves every other inventory decision.
9. Returns and Disposition Accuracy
Returns don’t just affect sales—they distort inventory.
WHY IT MATTERS:
Returned items often skip proper inspection, causing overstated availability.
Watch for
- Returns auto-restocked without review
- No clear disposition rules
- Items sold twice after a return
What helps
- Quarantine locations
- Clear workflows: restock, refurbish, scrap
- Accountability at intake
Returns are a workflow—not an exception.
A 20-Minute Weekly Inventory Health Check
You don’t need hours. You need consistency.
Each week:
- Pull the key reports above
- Circle the top three anomalies
- Identify the workflow step involved
- Apply one small fix
- Recheck next week
This routine works whether you’re using spreadsheets or a full WMS like LilyPad Warehouse Management System.
Final Thought: Inventory Accuracy Is a Habit
Inventory doesn’t fall apart overnight.
It drifts—slowly—when no one is watching the right signals.
The teams that win aren’t perfect. They’re curious, consistent, and willing to look where others don’t.
If you want help turning these signals into a repeatable process—or building a weekly inventory health check into your system—this is exactly where the right tools and training make the biggest difference.