Your POS system tracks every order, yet most restaurant owners never dig deeper than daily sales totals. Meanwhile, your pasta carbonara might be selling 200 times monthly while your expensive salmon special moves just 15 portions. Pairing this popularity data with actual food costs reveals exactly which dishes drive profit and which ones drain it.
What is menu engineering with POS data?
Menu engineering combines two critical metrics: popularity (frequency of orders) and profitability (food cost percentage). Your POS tracks which dishes customers actually order. Match that against your recipe costs and you'll spot exactly which items deserve prime menu real estate and which need immediate fixes.
💡 Example:
Data from POS system (last month):
- Steak: 120x sold, €32 per portion
- Pasta carbonara: 180x sold, €18 per portion
- Salmon fillet: 45x sold, €28 per portion
- Risotto: 25x sold, €22 per portion
Add food costs to this data and the real winners emerge.
The four quadrants of menu engineering
Popularity and profitability create four distinct categories:
- Stars: Popular + profitable → Feature these prominently!
- Plowhorses: Popular + unprofitable → Increase price or cut ingredient costs
- Puzzles: Unpopular + profitable → Boost marketing and placement
- Dogs: Unpopular + unprofitable → Cut from menu immediately
Calculate popularity from POS data
Your POS displays individual dish sales. Convert these numbers into percentages of total covers:
Popularity % = (Individual dish sales / Total covers) × 100
💡 Example calculation:
Last month: 800 covers total
- Steak: 120 / 800 = 15%
- Pasta: 180 / 800 = 22.5%
- Salmon: 45 / 800 = 5.6%
- Risotto: 25 / 800 = 3.1%
Pasta dominates customer preferences.
Calculate profitability
Each dish needs its food cost calculated. Lower percentages mean higher profits.
Food cost % = (Raw ingredient costs / Net selling price) × 100
⚠️ Note:
Use prices excluding VAT for accurate calculations. Food items carry 9% VAT in most regions.
Combine data into action plan
Plot dishes on a grid using popularity (high/low) and profitability (high/low). Most restaurants use 10% popularity and 30% food cost as dividing lines. But one of the most common blind spots in kitchen management is applying these thresholds without considering your restaurant's unique customer base and price point.
💡 Example classification:
Using 30% food cost threshold and 10% popularity:
- Steak (15% pop, 28% food cost): STAR → Push aggressively!
- Pasta (22.5% pop, 35% food cost): PLOWHORSE → Price adjustment needed
- Salmon (5.6% pop, 25% food cost): PUZZLE → Marketing opportunity
- Risotto (3.1% pop, 38% food cost): DOG → Menu elimination candidate
Actions per category
Stars (popular + profitable):
- Position prominently on menu layout
- Train servers to suggest these items
- Maintain consistent ingredient availability
Plowhorses (popular + unprofitable):
- Increase prices by €2-4
- Source cheaper ingredient alternatives
- Reduce portion sizes strategically
Puzzles (unpopular + profitable):
- Rewrite descriptions to sound more appealing
- Move to prominent menu positions
- Include in server recommendations
Dogs (unpopular + unprofitable):
- Remove from menu entirely
- Replace with tested alternatives
- Redirect kitchen focus to profitable items
Frequency of analysis
Review POS data monthly at minimum. Customer preferences shift rapidly, particularly with seasonal offerings. Update food costs quarterly since supplier prices fluctuate regularly.
How do you use POS data for menu engineering? (step by step)
Export sales figures from POS system
Get the sales numbers per dish from your POS for the last month. Also note the total number of covers. Most systems have a report called 'sales per item' or 'item sales'.
Calculate popularity percentage per dish
Divide the number of portions sold by the total number of covers and multiply by 100. Dishes above 10% popularity are popular, below that are not popular.
Calculate food cost percentage per dish
Add up all ingredient costs and divide by the selling price excluding VAT. Multiply by 100 for the percentage. Below 30% is profitable, above that is not profitable.
Place dishes in the four quadrants
Create a chart with popularity and profitability. Place each dish in the right quadrant: Stars, Plowhorses, Puzzles or Dogs.
Create an action plan per category
Promote Stars, make Plowhorses more expensive, sell Puzzles better and remove Dogs from the menu. Focus first on your Stars - they generate the most revenue.
✨ Pro tip
Pull your top 8 dishes from the past 60 days and calculate their exact food cost percentages. If 6 out of 8 show profitable margins, you've addressed the majority of your menu's financial impact.
Calculate this yourself?
In the KitchenNmbrs app you can do this in just a few clicks. 7 days free, no credit card.
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Frequently asked questions
Which POS systems provide detailed sales analytics?
Most modern POS systems include item-level reporting. Search for 'product performance', 'item sales analysis', or 'dish reports' in your system. Export data as CSV or Excel files for deeper analysis.
How often should I refresh my menu engineering analysis?
Review sales data monthly and recalculate food costs quarterly. Seasonal items need more frequent monitoring since demand patterns change rapidly. Major menu changes warrant weekly tracking initially.
What about dishes that only sell during specific seasons?
Compare seasonal items against the same period from previous years rather than month-to-month. Winter soups naturally outsell summer versions. Focus on year-over-year trends within each season for accurate insights.
Should labor costs factor into menu engineering decisions?
Focus primarily on food costs since labor remains relatively consistent across most dishes. Only factor in labor when specific items require significantly more prep time or specialized cooking techniques.
How many underperforming dishes can I remove safely?
Eliminate maximum 1-2 Dogs per menu revision to avoid shocking regular customers. Test replacement dishes as daily specials before permanent menu additions. Maintain menu variety while improving profitability.
What if my POS data shows conflicting trends between weekdays and weekends?
Analyze weekday versus weekend performance separately since customer behavior differs significantly. Business lunch crowds prefer quick, lighter options while weekend diners often choose premium dishes. Create separate analyses for each period.
How do I handle dishes with multiple size options or customizations?
Treat each size variation as a separate menu item for analysis purposes. A small pizza versus large pizza have different food cost percentages and appeal to different customer segments. Track and optimize each variation independently.
📚 Sources consulted
- EU Verordening 852/2004 — Levensmiddelenhygiëne (2004) — Official source
- EU Verordening 853/2004 — Hygiënevoorschriften voor levensmiddelen van dierlijke oorsprong (2004) — Official source
- EU Verordening 1169/2011 — Voedselinformatie aan consumenten (2011) — Official source
- NVWA — Hygiënecode voor de horeca (2024) — Official source
- NVWA — Allergenen in voedsel (2024) — Official source
- Codex Alimentarius — International Food Standards (2024) — Official source
- FSA — Safer food, better business (HACCP) (2024) — Official source
- BVL — Lebensmittelhygiene (HACCP) (2024) — Official source
- Warenwetbesluit Bereiding en behandeling van levensmiddelen (2024) — Official source
- WHO — Foodborne diseases estimates (2024) — Official source
Food Standards Agency (FSA) — https://www.food.gov.uk
The HACCP standards shown in this application are for informational purposes only. KitchenNmbrs does not guarantee that displayed values are current or complete. Always consult the FSA or your local authority for the latest regulations.
Written by
Jeffrey Smit
Founder & CEO of KitchenNmbrs
Jeffrey Smit built KitchenNmbrs from 8 years of hands-on experience as kitchen manager at 1NUL8 Group in Rotterdam. His mission: give every restaurant owner control over food cost.
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