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📝 Seasonality and purchasing · ⏱️ 3 min read

How do I create a simple forecast model for seasonal dish sales without complex software?

📝 KitchenNmbrs · updated 16 Mar 2026

Seasonal dishes can make or break your profit. Buying too much means waste, buying too little means missed revenue. A simple forecast model helps you estimate how much you need without expensive software or complex calculations.

Why seasonal dishes are tricky

Seasonal dishes give you a limited window to sell them. A summer salad with strawberries won't move in December. That makes purchasing risky: buy too much and you're stuck with ingredients you can't use.

But seasonal dishes often bring higher profits since guests pay more for fresh, seasonal ingredients.

The basics of your forecast model

A forecast estimates future sales. For seasonal dishes, you examine:

  • Historical data: How much did you sell last season?
  • Season duration: How many weeks can you sell this dish?
  • Weekly pattern: Which days are busy, which are quiet?
  • Weather influence: Warm days = more cold dishes

💡 Example: Gazpacho forecast

You want gazpacho on the menu from May to September (20 weeks):

  • Last year: 8 portions per week on average
  • Warm weeks: 15 portions
  • Cool weeks: 3 portions
  • Expected growth this year: 10% due to better menu placement

Estimate: 8 × 1.10 × 20 weeks = 176 portions total

Step 1: Gather your basic data

Start with what you know. Have you sold this dish before? Check your POS system or notes. Haven't sold it before? Look at similar dishes.

Write down how much you sold each week. Watch for patterns: did you sell more at the beginning (curiosity) or later (word of mouth)?

⚠️ Watch out:

No historical data? Start cautiously. Count on 5-8% of your total covers for a new seasonal dish.

Step 2: Calculate with scenarios

Create three scenarios: pessimistic, realistic, and optimistic. This gives you a range to work with.

  • Pessimistic: 70% of last year (bad summer, competition)
  • Realistic: 100% of last year (same as always)
  • Optimistic: 130% of last year (better marketing, good summer)

Plan your purchasing on the realistic scenario, but account for the other two for adjustments.

💡 Example: Asparagus soup in April-June

Last year: 120 portions in 8 weeks (15 per week on average)

  • Pessimistic: 120 × 0.70 = 84 portions
  • Realistic: 120 portions
  • Optimistic: 120 × 1.30 = 156 portions

Plan purchasing for 120 portions, but know you can reorder if things go well.

Step 3: Distribute across weeks and days

Seasonal dishes don't sell linearly. The first weeks are often busier (curiosity), then it stabilizes, and at season's end sales drop.

A common pattern we see repeatedly in restaurant financials:

  • Week 1-2: 150% of average (curiosity)
  • Week 3-8: 100% of average (stable)
  • Last 2 weeks: 70% of average (season winding down)

Factor in weather influence

Seasonal dishes are often weather-sensitive. Cold soups sell poorly on rainy days, warm stews don't move well at 30 degrees.

Check the long-range weather forecast and adjust your purchasing. Will it be a cold May? Then you'll sell less gazpacho in the first weeks.

💡 Example: Weather correction

Your gazpacho forecast: 10 portions per week in normal weather

  • Warm week (25°+): 10 × 1.5 = 15 portions
  • Cool week (below 18°): 10 × 0.4 = 4 portions
  • Rainy week: 10 × 0.2 = 2 portions

Adjust your weekly purchasing accordingly.

Adjust during the season

A forecast isn't set in stone. After 2-3 weeks you'll see if your estimate is correct. Selling more than expected? Reorder. Stuck with ingredients? Scale back.

Track weekly: how much sold vs. how much expected. Adjust your forecast for the remaining weeks based on what you learn.

Ingredients that spoil quickly

Pay extra attention to ingredients with short shelf life. Fresh herbs, soft fruits, and fresh fish can't be stored for weeks.

For these ingredients: order weekly based on your weekly forecast, not for the whole season.

⚠️ Watch out:

Keep a 20% buffer for peaks, but not more. Too much buffer means waste.

Digital tools

You don't need expensive software. A simple spreadsheet works, or even a notebook. What matters is that you track it and review it regularly.

Apps like KitchenNmbrs can help by automatically tracking how much of each dish you sell, so you have better data for your forecast next season.

How do you create a seasonal forecast? (step by step)

1

Gather historical sales data

Check how much you sold per week last season of this dish or similar dishes. No data? Estimate 5-8% of your total covers for a new seasonal dish.

2

Create three scenarios

Calculate pessimistic (70% of last year), realistic (100%), and optimistic (130%). Plan your purchasing on the realistic scenario.

3

Distribute across weeks with seasonal pattern

First 2 weeks: 150% of average (curiosity). Middle weeks: 100%. Last weeks: 70% (season winding down).

4

Correct for weather forecast

Check the long-range weather forecast. Warm weeks: +50% for cold dishes. Cold/rainy weeks: -60 to -80%.

5

Adjust weekly based on actual sales

After 2-3 weeks compare your actual sales to your forecast. Adjust your estimate for the remaining weeks based on what you learn.

✨ Pro tip

Track your weekly sales against weather patterns for 3-4 weeks straight. You'll spot temperature thresholds that trigger buying behavior changes faster than any complex model.

Calculate this yourself?

In the KitchenNmbrs app you can do this in just a few clicks. 7 days free, no credit card.

Try KitchenNmbrs free →

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Frequently asked questions

What if I don't have historical data for a new seasonal dish?

Start cautiously with 5-8% of your total covers. Look at similar dishes you have sold. After a few weeks you can adjust based on actual sales.

How often should I adjust my forecast?

Check weekly whether your forecast matches reality. Large deviations (more than 30% difference) are reason to adjust your forecast for the remaining weeks.

Do I need to create a separate forecast for each seasonal dish?

Yes, each dish has its own pattern. A gazpacho sells differently than a pumpkin soup. Create a forecast per dish, but use the same method.

What if the weather turns out completely different than predicted?

Adjust immediately once you notice the weather is affecting your sales. A heat wave can double your cold dish sales, a cold summer can cut it in half.

ℹ️ This article was prepared based on official sources and professional expertise. While we strive for current and accurate information, the content may differ from the most recent regulations. Always consult the official authorities for binding standards.

📚 Sources consulted

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.

JS

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.

🏆 8 years kitchen manager at 1NUL8 Group Rotterdam
Expertise: food cost management HACCP kitchen management restaurant operations food safety compliance

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