XUANMOU BRAIN

Xuanmou Brain

Turning your existing data into business insight and measurable improvement — so every profit leak is found, fixed, verified, and replicated

Three Questions Every CEO Must Answer

Chain restaurants don't lack data — they lack the ability to turn data into business decisions and measurable results

01

Where exactly am I losing money?

02

Which actions will actually improve profit?

03

When we scale from 30 to 300 stores, can I still see clearly and stay in control?

Why Data-Driven Efficiency Is No Longer Optional

The restaurant industry is undergoing structural change in 2025-2026

¥34.7
Average Check Size
Dropped from ¥39.8 to ¥34.7 — dine-in check sizes have fallen back to a decade ago, leaving no room for price increases
25%
Chain Penetration Rate
Up from 15% in 2020 to 25% in 2025, with 11 brands exceeding 10,000 stores — consolidate or be eliminated
8.83%
Industry Profit Margin
Risen from 5% to 8.83% through efficiency gains, not revenue growth — supply chain and digitalization are the key levers
24.1%
Delivery Share
Platform subsidy wars are squeezing margins — stores with high delivery dependency face further profit erosion
Raising prices is no longer realistic — the only path forward is internal efficiency. Cost reduction and productivity gains are the core imperative for restaurant chains in the coming years

12 Profit Black Holes

The 12 most common profit drains in restaurant chains — each one is quietly eating your margins

Revenue · Capture the Money You Should Be Earning
Discount Runaway
Some stores have discount rates above 25%, with promotions executed at store level without ROI evaluation
Are these discounts actually driving incremental traffic?
Ineffective Loyalty Program
Member transactions typically below 15% — industry healthy level is 30-50%, with no outreach records
80,000 members, but only 1 in 7 transactions is from a member?
Bloated Menu
Large numbers of low-volume, low-margin items occupying menu space, traffic-driving items unvalidated, some items lack cost data
Hundreds of items that don't sell — why are they still on the menu?
Delivery Revenue Without Profit
Platform commissions and discounts devour margins, platform cost rates exceed thresholds at many stores, per-order profit unclear
How much delivery revenue did we generate, and how much did the platform take?
Underperforming Stores Dragging Down the Chain
Red-flag stores with expense ratios above 60%, contribution margins of only 1-5%, closure analysis lacks real investment data
Should these stores be closed or rescued?
Site Selection by Gut, Not Data
Missing store areas make sales-per-sqm uncalculable, overlapping stores cannibalize foot traffic, success factors hard to replicate
What exactly drives new store location decisions?
Cost Control · Keep the Profit You Should Be Retaining
Severe Ingredient Overconsumption
The biggest profit black hole — portion overage, missing BOMs, high procurement prices, annual losses can reach tens of millions
A few million a month in overconsumption — tens of millions a year?
Recipe Data Chaos
Code mismatches, zero net quantities, yield loss rates above 50% — theoretical costs are unreliable, leading to pricing errors
If you can't even calculate costs accurately, how can you set prices?
Rough Inventory Management
Negative consumption and zero consumption coexist, no waste records, no transfer tracking, turnover efficiency uncalculable
How are expired ingredients handled? How much was written off?
High Expense Ratios
Many stores with operating expense ratios above 55%, unclear breakdown of wages/rent/utilities/commissions/supplies, no budget tracking
A full month of work, and the contribution margin is only 1%?
Central Kitchen Potential Unreleased
Yield rates below standard, large recipe variances, cost allocation unverified — is it saving money or wasting it?
Is the central kitchen a cost center or a profit center?
Rough Labor Cost Management
Labor cost ratios above threshold, scheduling not aligned with traffic peaks and valleys, turnover rates unknown, no productivity rankings
Which stores are overstaffed?

How Xuanmou Brain Works

Four categories, seventeen domains — translating CEO concerns into measurable, trackable indicators

Revenue
5 domains · 18 indicators
  • Revenue GrowthHow much was sold, achievement rate
  • Discount ControlDid discounts actually drive incremental sales
  • Member OperationsRepeat rate, LTV, churn rate
  • Delivery P&LTrue profit per delivery order
  • Store Grading & Site SelectionWhich stores to close, where to open new ones
Efficiency
4 domains · 12 indicators
  • Spatial EfficiencySales per sqm, seat turnover rate
  • Labor EfficiencyRevenue per head, labor cost ratio, gross profit per head
  • Operational EfficiencyTable turnover, dining duration, kitchen output speed
  • Inventory & CapacityTurnover days, waste rate, capacity utilization
Cost Control
5 domains · 16 indicators
  • Ingredient CostActual vs theoretical variance, BOM coverage
  • Expense ControlExpense ratio, contribution margin, budget execution
  • Waste & LossWaste rate, negative consumption, zero consumption
  • Central KitchenYield rate, recipe variance rate
  • Supply ChainOn-time delivery, quality score, price variance
Risk Control
3 domains · 9 indicators
  • Food Safety & InspectionInspection scores, non-conformance items, IoT temperature
  • Compliance & AuditAbnormal bills, cashier risk, zero-revenue stores
  • Sentiment & ComplaintsComplaint rate, resolution time, turnover rate
55 indicators covering the full operational chain — each with healthy threshold, current value, improvement action, responsible person, and review frequency

The Improvement Loop

From problem discovery to verified improvement — a traceable, replicable management loop

Detect Anomaly
→
Root-Cause Analysis
→
Generate Action
→
Track Execution
→
Verify Improvement
→
Codify & Replicate

Turn effective practices into company best practices and replicate them across every store

Review Cadence

Daily
Store Manager · Daily target card, anomaly review
Weekly
Area Manager · Revenue trends, cost variance, task execution
Monthly
CEO · Full indicators, store grading, loop review
Quarterly
Board · Trend analysis, ROI, strategic adjustment

Implementation Path

Phased delivery — each phase independently verifiable, no all-or-nothing bets

30 Days

Run the First Loop

Audit data landscape → Build indicator system → Launch anomaly monitoring → Generate first improvement tasks → Verify the first profit improvement opportunity

6 Weeks

Indicator System + Dashboard Live

CEO cockpit, area dashboards, store detail views — three-tier visibility with automated alerts and trackable task closure

3 Months

Stable Loop Operation

Review cadence institutionalized, best practices being codified and replicated, data quality continuously improving

Spend 30 days finding the first batch of verifiable profit improvement opportunities, then decide how to scale