Stock variances can be frustrating, but they often point to specific issues that can be identified and resolved. Whether it’s missing sales, unrecorded deliveries, miscounts, incorrect recipes, or operational issues understanding the root cause is key to maintaining accurate inventory records.
In this guide, we’ll walk through the most common (and simple to fix) stock variance issues:
Incorrect recipes: When what’s configured doesn’t reflect what’s truly being used.
Waste events: Food or drink loss that isn’t logged or accounted for correctly.
Inventory setup issues: Items being purchased under one name but used in recipes under another.
Operational behaviour: Unapproved ordering, overproduction, or poor portion control.
Core Assumptions & Investigative Process
Before we can meaningfully diagnose a variance, we must ensure that all controllable variables are correct. The theoretical usage (what the system expects to be used) is only as good as the assumptions feeding it.
Getting Ready: Establish Certainty in Known Input Data Points:
Closing Stock Count
This is the most crucial input into your reconciliation.
Ensure stock counts are accurate, consistent, and completed within the same window across all sections.
2. Deliveries Logged Correctly
Double-check that all deliveries have been entered with the correct quantity and matched to the right SKU.
3. Transfers Recorded
Any stock transferred between locations or sections must be logged.
Missing transfers are a common cause of unexplained variances.
4. Waste Logged and Categorised
Waste must be logged with clear reasons—this is essential for separating controllable vs uncontrollable losses.
Now what? Identify the Unknowns
With all the above solidified, the remaining “unknown” becomes theoretical recipe usage. This is where potential discrepancies lie, including:
Shrinkage during batch prep
Over-portioning
Substitutions in production
Prep wastage
Step-by-Step Diagnostic Process
Step 1. Analyse Recipes in Detail
Are portion sizes realistic? For example, is the system configured for 150g but 180g is actually plated?
Are batch yields configured to reflect actual shrinkage (e.g., trim, evaporation, overproduction)?
Use Nory to Validate These Assumptions:
Nory doesn’t just surface variance—it helps pinpoint its origin.
If a specific ingredient is consistently showing negative variance, and that ingredient is used across one or more batches, it may indicate that the batch recipe is missing yield adjustments.
For example, if you regularly sell 20kg of a dish using butter, but your variance shows a consistent 10kg deficit, it suggests a 50% shrinkage is happening during prep or cooking that's not reflected in the batch recipe.
By using Nory’s variance reporting in tandem with batch tracking, you can:
Spot discrepancies that suggest batch yield misconfigurations.
Estimate the level of shrinkage occurring.
Adjust recipes to include this shrinkage—so theoretical usage aligns with actual prep.
This ensures that your theoretical costs reflect reality, which improves margin accuracy.
📌 Why it matters: If a batch yield is wrong, the system underestimates how much product is being used. This not only skews variance but also hides your true cost, making a dish appear more profitable than it is.
→ Action: Update batch recipes with correct yield factors. Validate these against prep data, and ensure they’re reflected in both recipe costing and inventory reconciliation.
→ Action: Reassess menu item viability based on actual performance.
→ Outcome: Improved margin reporting, better menu engineering decisions, and increased confidence in data accuracy.
Step 2: Revisit Recipe Mapping & POS Integration
This is one of the most critical steps in diagnosing variances. Even if your recipes and stock inputs are perfectly configured, incorrect POS mapping can completely throw off your usage data.
Why POS Mapping Matters:
Nory calculates theoretical usage based on what’s sold via POS. If those sales aren’t linked correctly to recipes, usage data becomes unreliable.
There are two key failure modes:
Unmapped POS Items – Sales come through with no recipe assigned.
Incorrectly Mapped Items – A POS button is linked to the wrong recipe, modifier, or portion size.
What to Check:
Pending POS Items: Review regularly to ensure new buttons are being assigned to the correct recipes.
Assigned POS Items: Audit these to confirm that mappings reflect real operational use.
Modifiers and Add-ons: Ensure these are included and not driving unaccounted usage.
Investigate What’s Happening Operationally:
Are teams pressing the correct POS buttons for what’s actually being served?
Are servers and FOH staff trained to follow the right workflows?
Do menu configurations in the POS reflect what’s available and plated?
Sometimes variances aren’t due to system errors, but rather non-compliance on the ground—for example, staff using old or incorrect buttons, or skipping modifier steps.
Keep the POS Clean:
Archive outdated or unused buttons to prevent noise in the system.
Ensure only live, relevant POS data is synced into Nory.
Historical clutter can lead to missed mappings and misleading reports.
💡 Best Practice: Schedule a weekly audit of both pending and assigned POS items. Cross-check these with your live menu and recipe data to ensure nothing slips through the cracks.
→ Action: Review and clean your POS integration in Nory. Reassign or archive outdated buttons, validate modifier logic, and confirm staff are trained to follow correct input procedures.
→ Outcome: Improved mapping accuracy leads to more reliable variance insights—and prevents wasted time chasing phantom discrepancies.
Step 3: Assess for Hidden Operational Gaps
Once recipes, stock counts, waste logs, and POS mapping are confirmed, yet variances remain, you're likely dealing with untracked operational behavior. These gaps often don’t leave digital footprints but their impact shows up in your data.
This step is about looking beyond the system and into kitchen execution, team habits, and compliance.
Common Operational Drivers of Variance:
Unlogged waste
Staff forget or neglect to log end-of-day or production waste, particularly during busy shifts.
Undocumented substitutions
One ingredient is swapped for another (e.g., margarine instead of butter) without updating batch or recipe data.
Improper portioning
Without standardised tools or adherence to guides, portions vary by server, shift, or prep batch.
Over-prep or over-production
Teams prepare too much in anticipation of demand, leading to expiry or wastage.
Prep or cook errors
Burnt items, dropped plates, or incorrectly cooked food often go unrecorded.
Training and SOP non-compliance
Staff might not follow documented guides, either due to lack of training or time pressure.
How to Investigate These Gaps:
Shadow a service or prep session
Observe firsthand whether SOPs are followed, portioning tools are used, and prep volumes are reasonable.
Interview chefs and shift leads
Ask how closely they follow the guides. Often, they'll reveal shortcuts or habitual workarounds.
Review kitchen guides vs actual behavior
Is what's happening in the kitchen a match for what’s documented in recipes and batch instructions?
Check consistency across shifts
Variances may spike on weekends, late shifts, or when specific team members are working.
Use Nory variance patterns
Look for:
Recurring items with consistent negative variance
High-value ingredients with frequent swings
Gaps where no waste is logged, yet stock is missing
Nory Tools That Help:
Variance reports over time: Zoom out to monthly trends—this helps smooth out short-term anomalies and shows whether corrective actions have long-term impact.
Waste logging review: Cross-reference high-variance items with waste logs. If there’s no recorded loss, investigate further.
Stocktake compliance tools: Ensure teams are completing counts on time and to standard.
Variance by location or shift: Identify if problems are concentrated in specific venues, days, or teams.
What to Do About It:
Coach teams: Focus first on the top 5 variance contributors. Reiterate importance of waste logging, accurate prep, and standard portioning.
Update SOPs if needed: Sometimes the guides are unclear, impractical, or outdated.
Spot-train: Schedule refresher training on portioning tools, logging practices, and prep control.
Introduce accountability: Add variance reviews into weekly management huddles.
→ Action: Identify the top sources of unexplained variance. Use a mix of data (Nory) and field observation to validate theories.
→ Outcome: Reduced variance noise, improved operational compliance, and stronger alignment between systems and reality.
Step 4: Reduce the Stock Window for Sharper Visibility
One of the most effective tactics for identifying root causes is to shorten the window of stock analysis.
Here's why:
A full week’s stocktake can mask fluctuations.
By counting every 2–3 days, or even daily for key items, you get:
Clearer signals on when the issue occurs (early week vs weekend)
A shorter feedback loop to validate if your corrective actions are working
Less “noise” in the data due to cumulative issues compounding
This creates an operational microscope—helping managers and chefs react quicker, rather than waiting 7+ days to see if something worked.
🧠 Use pre-built templates for daily and weekly spot checks to ensure consistent units, locations, and timing.
Waste: The Hidden Driver of Variance
Many issues behind variance are rooted in waste, often unseen but highly damaging to profitability.
This includes:
Shrinkage
Over-production
Poor processing or batch control
Over-ordering
Burnt or mishandled food
Gaps in operational training
While waste might show up in your variance report as a negative number, it doesn’t explain why it happened. That’s where waste logging becomes critical.
Logging Waste with Reasons:
Logging why waste occurred gives you qualitative insight.
Did it happen due to:
Poor ordering?
Overproduction during service?
Product expiry or misrotation?
These reasons help distinguish where processes need fixing.
Why It Matters:
It turns guesswork into action.
You’ll know whether to coach teams on portioning, adjust prep quantities, or rethink par levels.
Nory enables this culture of accountability with intuitive, fast waste logging, ensuring operators don't just record loss—they learn from it.
Conclusion: Build a Culture of Visibility and Discipline
The core of Nory’s value is turning ambiguity into accountability. Variances highlight what’s slipping through the cracks. But with a methodical approach—starting from validating knowns, then testing recipes, and finally tightening your operational lens—you create the ability to act fast and accurately.
Think of variances as a feedback loop. With the right processes in place, they can become your best tool for continuous improvement.
Quick Reference: Full Diagnostic Checklist
Use this checklist when reviewing variances to ensure a complete, step-by-step investigation.
Step 1: Validate Core Inputs
Closing stock counts are completed and accurate
Counts are done in consistent units and timeframes
All deliveries are entered with correct quantities and items
Transfers between locations/sections are fully recorded
Waste is logged daily with clear reasons (e.g., End of Day, Expired, Damaged)
No gaps in any operational data sources
Step 2: Review Recipe Accuracy
Recipes are correctly mapped to POS buttons
Portion sizes reflect actual usage
Batch yields are tested and realistic (e.g., accounting for trim or evaporation)
Modifiers and sub-recipes are included and linked correctly
Duplicate SKUs or product versions are merged
POS integrations are functional and recipe mapping is complete
Recipe costings are reviewed: is the actual GP close to theoretical GP?
Menu items are assessed for profitability after recipe corrections
Step 3: Investigate Operational Gaps
Are the same variances occurring week after week?
Are high-variance items lacking corresponding waste logs?
Are teams using standard portioning tools?
Are undocumented substitutions or swaps happening in prep?
Is there compliance with prep guides, par levels, and batch processes?
Are behaviours and gaps observable across specific shifts or days?
Step 4: Narrow the Stocktake Window
High-variance items are being line counted every 2–3 days
Mid-week or daily counts trialed for sharper visibility
Trend patterns identified by day or shift (e.g., variance spikes on weekends)
Corrective actions tested mid-week, not just after a full cycle
Feedback loop shortened to respond faster and validate fixes
Step 5: Implement Weekly Variance Review
Weekly variance review meeting is scheduled (30–45 min)
Top 5 high-impact variances reviewed and prioritized
Root causes discussed and documented
Assigned actions (e.g., recipe updates, staff coaching, system clean-up)
Progress reviewed in next week's meeting
Examples
Missing Sales Example
In the screenshot below there is a variance of -2.95 on Parmesan 1/8 Block. The stock was counted correctly but there were not sale of the item connected to a recipe in Nory, this is shown in the column POS sales.
If you see a 0 Sales Qty but you know you sold menu items using that ingredient, it probably means you haven't assigned that Recipe to the POS ID.
Missing Deliveries Example
In the screenshot below Red Chilies is up 1 kg. The closing count is correct, but there are no deliveries of this product.
2 Kg were delivered but the received on date was not within the stock period.
💡The same process could be followed for missing waste entries and transfers that have not been completed.
Miscounts Example
If the math doesn’t add up, double-check how items were counted.
In this example, there’s a variance on Brined Chicken Fillets, showing as -5.25 units (£8.00). After reviewing the count, it was discovered that a storage area was missed during the stocktake.
How to fix it:
You can reopen the stock count and update the quantity for the item based on what’s in the missed storage area. Once updated, the variance will recalculate to reflect the correct closing quantity.
Incorrect Recipe Setup: Positive Variance Example
You’re seeing a positive variance of 16 loaves of gluten-free bread. The delivery records and closing count are both accurate. However, in the POS sales column, it shows 18 loaves sold that week - which the team knows isn’t right, as gluten-free options sell in very low volume.
What caused the variance?
After checking the item setup, it was found that the recipe or POS mapping had the loaves set up as 1 each instead of reflecting how they’re actually used or portioned in the system. This incorrect setup caused the system to deduct more from stock than it should.
How to fix it:
Check the recipe or POS mapping for the item and ensure the correct unit of measure and portion size are being used. Updating this will prevent over-deducting and help keep your variances accurate.
❗ Permission to edit inventory items is needed to access the inventory set up.
📖 Learn more about Permissions in Nory
The recipe for gluten-free bread was for 2 each, assuming 2 slices of bread would be deleted. Instead two loaves were being deducted per order.
To rectify this problem the item was updated to 10 each (10 slices of bread per loaf).