Historical sales data is gold for your purchasing. Many restaurant owners buy based on gut feeling, resulting in too much or too little stock. By analyzing your old sales figures you can recognize patterns and purchase more precisely.
Why historical data is so valuable
Your sales data tells stories you'd otherwise miss. Which dishes sell well on Monday? How much more fish do you sell in summer? These patterns repeat year after year.
💡 Example:
Restaurant De Smaak analyzes their salmon sales:
- January 2024: 45 salmon portions per week
- July 2024: 78 salmon portions per week
- January 2025: 48 salmon portions per week
Pattern: 70% more salmon in summer months
What data you need
You don't need all the numbers to get started. Focus on the most important data:
- Number of portions sold per dish per day/week
- Total revenue per day (to see seasonal patterns)
- Number of covers per day (to forecast busy periods)
- Special events (holidays, events, bad weather)
You get this from your POS system or through manual counting. Go back at least 12 months for reliable patterns.
Recognizing seasonal patterns
Most restaurants have clear seasonal patterns. You can use these for better purchasing:
💡 Example patterns:
- Summer: +40% salads, +60% fish, -30% stews
- Winter: +50% game, +30% red wine, -40% rosé
- Holidays: +200% luxury ingredients (lobster, champagne)
Note these percentages and adjust your purchasing accordingly. Don't buy winter ingredients in summer, even if they're cheap.
⚠️ Watch out:
One-off events skew your data. Filter out outliers before looking for patterns. That one wedding with 200 guests isn't a standard Saturday.
Using daily patterns for fresh purchasing
Not just seasons, but weekdays have patterns too. This is crucial for fresh products with short shelf life:
- Monday often 40-60% less than weekends
- Friday/Saturday usually peak evenings
- Sunday depends on your concept (lunch vs. dinner)
Use this for fish, meat, and fresh vegetables. Buy less on Monday, more on Thursday for the weekend.
Forecasting with correction factors
Historical data is a foundation, not a guarantee. Always adjust for:
- Weather: rain = fewer guests, heat = more terrace seating
- Local events: festivals, sports matches, trade shows
- Your own actions: new menu, marketing campaigns
- Economic situation: recession = cheaper dishes more popular
💡 Example correction:
Forecast based on data: 60 covers on Saturday
Adjustments: Football final (-20%), nice weather (+15%)
Adjusted forecast: 57 covers
Tools to organize your data
Excel works, but gets messy quickly. Better options:
- POS system reports: most can export sales per dish
- Hospitality apps: systems like KitchenNmbrs can link sales and purchasing
- Simple spreadsheet: per week, per dish, quantity sold
The most important thing is that you use it. A perfect database you never check doesn't help.
From data to action
Collecting data is step 1. Step 2 is adjusting your purchasing:
- Order 80% of your forecast for perishables (you can reorder)
- Order 100-110% for shelf-stable products (inventory is fine)
- Keep buffer for popular dishes (worse to run out than have too much)
Test your forecasts for a month and adjust. Perfect forecasting doesn't exist, but 80% accuracy is already a huge improvement.
How do you adjust purchasing based on historical data? (step by step)
Collect 12 months of sales data
Export from your POS system: number of portions sold per dish per week. At least a full year for seasonal patterns. Filter out outliers (events, closed days).
Calculate averages per season and weekday
Create overviews: how much you sell on average per dish in winter/summer, per weekday. Note percentage differences between seasons for your top 10 dishes.
Forecast next week and order based on that
Use your averages, adjust for weather/events/promotions. Order 80% of forecast for fresh items, 100% for shelf-stable. Compare after a week: was your forecast accurate?
✨ Pro tip
Start with your 5 best-selling dishes. If you can forecast those well, you have 70% of your purchasing under control. Perfection on everything is less valuable than accuracy on your top sellers.
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
How many months of data do I need at minimum?
At least 12 months for reliable seasonal patterns. You can start with 6 months, but you'll miss seasonal differences. With 24 months you can see if patterns repeat.
What if my POS system can't generate detailed reports?
Start by manually counting your top 5 dishes per day. Note in a simple spreadsheet. After a month you'll already see patterns. Perfect data is less important than consistent tracking.
How do I handle new dishes without sales history?
Compare with similar dishes you already have. A new fish dish probably follows the pattern of other fish dishes. Start cautiously with small quantities and adjust based on sales.
Should I account for trends and changing tastes?
Yes, historical data shows what was, not what's coming. Keep an eye on trends (plant-based, local products) and gradually adjust your purchasing. Use data as a foundation, not as law.
How often should I update my forecasts?
Check weekly how accurate your forecast was. Update your averages monthly with new data. You can update seasonal averages each quarter.
📚 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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