The Situation
How a restaurant group discovered it had built its menu around popularity — not profitability — and what a restructure unlocked.
Food cost was running at 41% against a 32% target. Two locations felt profitable. Two didn't. But the consolidated P&L obscured everything. Decisions were made on instinct and customer feedback — not data.
The Approach
GrowthBridge applied menu engineering methodology — mapping every item on a frequency vs contribution margin matrix. We then built a location-level P&L for all four sites and benchmarked rent-to-revenue, staff cost, and average spend per cover.
Menu Engineering Matrix — Contribution Margin vs Order Frequency
Stars
High frequency · High margin
- Dal Makhani
- Butter Naan
- Beverages
- Tandoori Chicken
Puzzles
Low frequency · High margin
- Chef Specials
- Premium Mains
- Signature Starters
Plough-horses
High frequency · Low margin
Dogs
Low frequency · Low margin
- Most Starters
- Most Desserts
- Niche Mains
Key Finding
The biryani — the most ordered item across all four locations — generated ₹72 contribution margin per cover. Dal Makhani, ordered at half the frequency, generated ₹280. 22 "Dog" items occupied 34% of the menu and generated negligible contribution.
The Recommendations
- 01Remove 22 low-frequency, low-margin items — simplify the menu, reduce kitchen complexity, and free up training capacity.
- 02Promote "Puzzle" items actively — 11 high-margin items ordered infrequently due to poor menu placement and low staff awareness.
- 03Close the Lower Parel location — generating negative EBITDA at ₹1.2Cr revenue with a rent covenant that makes profitability structurally impossible.
The Outcome
The founder had been proud of the biryani. Menu engineering is not about removing what customers love. It is about making sure what they love also works for the business. The restructure identified ₹94L of recoverable EBITDA through menu and location decisions.
Business names, individual identifiers, and certain operational details have been changed to protect confidentiality. The analytical methodology, data patterns, and strategic findings are real. Specific figures are indicative of the patterns identified.