Food Cost Control & Inventory

🔄 Quick Recall: In the previous lesson, you classified every menu item by profitability and popularity, optimized pricing, and created compelling descriptions. Now you’ll tackle the cost side — building systems that track every dollar of food expense and catch problems before they eat your margins.

Food cost is the #1 controllable expense in your restaurant. With 84% of operators reporting higher food costs than last year, the operators who track, analyze, and adjust in real time are the ones who survive.

The difference between a 32% and a 28% food cost on $1.5M revenue is $60,000 per year. That’s the difference between a restaurant that’s barely surviving and one that’s thriving.

Recipe Costing: The Foundation

Every dish on your menu should have a documented recipe cost. Without this, you’re pricing blind.

AI prompt for recipe costing:

You are a restaurant cost analyst. I’ll provide a recipe with ingredients and quantities. For each ingredient, I’ll give the purchase unit (case/pound/gallon) and cost. Calculate: (1) cost per usable unit after accounting for yield percentage (e.g., raw chicken has ~75% yield after trimming), (2) total recipe food cost, (3) cost per portion, (4) recommended menu price at [TARGET]% food cost, and (5) contribution margin at the recommended price. Recipe: [DISH NAME] — [LIST INGREDIENTS WITH QUANTITIES AND PURCHASE COSTS].

Yield percentages matter:

✅ Quick Check: Your recipe calls for 8 oz of beef tenderloin. You buy it at $28/lb. What’s the actual ingredient cost per plate? (Answer: At 80% yield, the true cost is $35/lb usable. 8 oz = 0.5 lb × $35 = $17.50 per plate — not the $14 you’d calculate using the purchase price. AI applies yield percentages automatically to every ingredient, revealing the true cost of each dish.)

Food Cost Tracking System

Tracking food cost monthly isn’t enough — by the time you see last month’s numbers, you’ve already lost money. AI enables weekly or even daily tracking.

The weekly food cost formula:

Beginning Inventory + Purchases - Ending Inventory = COGS
COGS ÷ Food Revenue = Actual Food Cost %

AI prompt for food cost analysis:

Analyze my restaurant’s food cost data for this week. Beginning inventory: $[AMOUNT]. Purchases this week: $[AMOUNT]. Ending inventory: $[AMOUNT]. Food revenue: $[AMOUNT]. Calculate: actual food cost percentage, variance from my target of [TARGET]%, dollar amount of the variance, and annualized impact if this variance continues. Then compare to the previous 4 weeks to identify the trend. If the variance exceeds 1 percentage point, suggest three possible causes to investigate.

Setting up variance alerts:

Waste Tracking and Reduction

The average restaurant wastes 4-10% of purchased food — worth $20,000-$50,000 per year for a million-dollar restaurant. AI helps you track, categorize, and reduce waste systematically.

Waste categories and solutions:

AI prompt for waste reduction plan:

I run a [RESTAURANT TYPE] doing $[REVENUE]/week. My current food cost is [X]% and my target is [Y]%. I’ve been tracking waste for the past two weeks: [LIST WASTE LOG ENTRIES — item, amount, reason]. Analyze this waste data, identify the top 3 categories costing me the most money, and create an action plan for each with: specific process changes, measurement methods, and expected savings. Also suggest a daily waste tracking system my kitchen staff can use in under 5 minutes.

✅ Quick Check: Your kitchen consistently overproduces 15 lbs of prep items per day. At an average food cost of $4/lb, what’s the annual cost of this waste? (Answer: 15 lbs × $4 × 365 days = $21,900 per year. And that’s just overproduction — before spoilage, over-portioning, and plate waste. AI demand forecasting reduces overproduction by predicting how much you’ll actually sell based on day of week, weather, events, and historical patterns.)

Inventory Forecasting and Ordering

Over-ordering creates waste. Under-ordering creates 86’d items and frustrated guests. AI forecasting finds the sweet spot.

AI prompt for inventory forecasting:

Based on my restaurant’s sales data for the past 4 weeks, forecast next week’s usage for these key items: [LIST TOP 20 INGREDIENTS WITH LAST 4 WEEKS’ USAGE]. Factor in: day of week patterns, upcoming events or holidays [LIST ANY], weather forecast [EXPECTED CONDITIONS], and any trends in the data. For each item, recommend: order quantity (usage + 10-15% safety stock), order day (based on delivery lead time of [X] days), and par level to maintain.

Supplier price monitoring:

Key Takeaways

• Recipe costing with yield percentages reveals the true cost of each dish — a chicken breast at $2.50/lb purchased actually costs $3.85/lb usable, and AI calculates this for every ingredient
• Track food cost weekly, not monthly — a 2% variance caught in week one costs $400; caught after a month, it costs $1,600+
• The average restaurant wastes 4-10% of purchased food ($20K-$50K/year) — AI waste tracking categorizes and reduces each type: prep, spoilage, plate waste, over-portioning, and overproduction
• AI demand forecasting reduces over-ordering by predicting sales based on day, weather, events, and historical data — eliminating the guesswork that creates waste
• A 3-point food cost reduction on $2M revenue saves $60,000/year — enough to fund equipment upgrades, staff bonuses, or marketing

Up Next

In the next lesson, you’ll tackle the second-biggest expense: labor. You’ll build AI scheduling systems that optimize coverage, reduce overtime, and keep your team happy.