📊 Operations Snapshot
💰 Weekly Revenue
$28,400
Lunch: $8,200 · Dinner: $18,400 · Bar: $1,800
▲ 4.8% vs same week prior year
🍖 Food Cost % (Weekly)
36.2%
Target: 32% · Variance: +4.2 pts
▼ $1,194/wk in excess food cost
🔄 Avg Table Turn Rate
58 min
Target: 48 min · Dinner peak: 72 min
▼ 10-min gap = ~$420/night lost
🧮 Real-Time Profit Leak Calculator
⏰ Day-Part Revenue Intelligence
Revenue per Cover + Labor Efficiency by Day-Part
Cost per hour (CPH) includes labor + fixed overhead allocation
Day-PartRevenue ContributionRev/CoverCPHMargin%Signal
Breakfast
$12.40
$68/hr
8.2%
Weak
Lunch
$31.80
$82/hr
18.4%
Average
Happy Hour
$24.20
$54/hr
28.6%
High Margin
Dinner (M-Th)
$48.60
$94/hr
22.1%
Peak
Dinner (F-Sa)
$54.20
$112/hr
19.8%
Turn Rate Issue
💡 F-Sa dinner is your highest-revenue day-part but margin drops to 19.8% because turn rate averages 72 min vs 52 min Mon-Thu. Each 10 min shaved off F-Sa turn time at your cover count = est. +$3,200/month in additional table cycles.
🍖 Food Cost Variance Engine + Server Performance
Food Cost by Category — Actual vs Target
CategoryActualTargetVarianceWeekly $
🍗 Chicken
41%
Target: 33%
+8 pts
-$340/wk
🥩 Beef/Steak
38%
Target: 34%
+4 pts
-$284/wk
🐟 Seafood
35%
Target: 33%
+2 pts
-$120/wk
🌿 Produce/Veg
28%
Target: 30%
-2 pts
+$80/wk
🥃 Bar/Beverage
22%
Target: 24%
-2 pts
+$94/wk
⚠️ Chicken variance is the #1 driver this week. SE_Watch flagged a 18% recipe spec over-pour on the chicken thigh dish — likely portioning issue on the dinner line. Correcting to spec saves $340/week or $17,680/year.
Server Performance — PPA + Upsell Rate
PPA = per-person average. Upsell = apps/desserts/premium drinks attached per table.
ServerPPA ScoreCoversPPAUpsell%Weekly
Jasmine T.
148
$54.20
38%
Top 10%
Marcus W.
134
$49.80
31%
Above Avg
Tanya R.
121
$44.60
22%
Average
Devon K.
118
$38.40
14%
Below Avg
Lisa M.
104
$36.20
9%
Gap: $18/cover
⚠️ Lisa M. runs $18/cover below Jasmine. At 104 covers/week that is $1,872/week in unrealized revenue. SE generates personalized coaching scripts based on each server's specific gap (her miss: zero dessert attachment, 9% app rate).
🔬 SE_Watch — Restaurant Risk Signals
Live Signals — Updated Nightly After Close
Food Cost Variance — Chicken Category +8 pts
Recipe spec over-pour detected on chicken thigh entree. 18% above theoretical usage. Most likely cause: portion drift on dinner line. At current volume, $340/week in excess food cost. Correcting to spec: 2-day fix.
Act This Week
F-Sa Turn Rate 20 Min Over Benchmark
Friday and Saturday dinner averages 72 min/table. Mon-Thu runs 52 min. Bottleneck identified at kitchen ticket timing (avg 28 min fire-to-plate vs 18 min target). 3 tables/night x $48 avg check = $576 in uncaptured covers per weekend night.
Revenue Impact
Late Night (9pm+) Capturing Only $1,800/wk
Bar revenue from 9pm-close runs 22% below comparable Monday Street restaurants in your segment. Your bar seats run at 48% utilization after 9pm F-Sa. No late-night bar menu currently — highest-margin day-part being left empty.
Opportunity
No Prix-Fixe or Table Minimum on Peak Nights
Friday and Saturday seats are fully committed by 7pm yet avg check runs only $54. With a $65 weekend minimum or prix-fixe at $72, same seat count generates 20-25% more revenue with no additional labor or food cost pressure.
Pricing Opportunity
Review Response Rate: 34% This Month
You responded to 34% of new Google reviews. Restaurants responding to 80%+ of reviews average 0.3 stars higher and 11% more new guest conversions from search. 28 reviews this month went unanswered.
Brand Signal
0 Birthday/Anniversary Reactivation Sequences Active
Your reservation data contains 284 guests with birthdays or anniversaries on file. Zero outreach sequences running. Restaurants with birthday programs drive 2.4x repeat visits in the 30-day window around the occasion.
Retention Gap
💸 Revenue Leakage Engine
$76,200
Estimated Annual Revenue Leakage Identified
🍖
Food Cost Running 4.2 pts Above Target
At $28K weekly revenue, each 1% food cost point = $280/week. 4.2 pts variance = $1,176/week in pure margin destruction. Primary driver: protein portioning drift on dinner line. Recipe spec enforcement closes this in one week.
$61,152
🔄
Table Turn Rate: 10 Min Over Target on Peak Nights
F-Sa dinner: 72 min avg vs 52 min target. At 24 tables x 3 turn cycles, you miss ~1 full turn cycle per night on peak nights (Fri + Sat). At $54 avg check and 24 tables: 2 nights × $1,296 = $2,592/month in uncaptured seats.
$31,104
🛠️ Restaurant Intelligence Toolkit
Theoretical vs Actual Food Cost Engine
Calculates theoretical food cost from your recipe specs and actual sales mix, then compares to actual usage. Identifies exactly which item is drifting, by how much, and what it costs per week — before it destroys your month.
⚡ Live Variance
Day-Part Revenue Optimizer
Maps revenue per cover, labor cost per hour, and margin by day-part. Identifies your highest-margin time windows and surfaces operational changes (late-night menu, prix-fixe, bar-only seating) to capture that margin.
📊 Margin Mapping
Server Performance Intelligence
Scores every server on PPA, upsell attach rate, table turn contribution, and guest return rate. Generates coaching scripts specific to each server gap — not generic training, but exactly which item they are not suggesting and when.
👥 Team Revenue
Table Turn Rate Analyzer
Breaks down turn time by day-part, day of week, server, and table size. Identifies the exact bottleneck (kitchen timing, payment delay, server pacing) and calculates the revenue impact of each 5-minute improvement.
⏱️ Seat Revenue
Guest Occasion Reactivation
Mines your reservation and POS data for birthdays, anniversaries, and first-visit anniversaries. Fires personalized offers timed to a 2-week window before each occasion — when guests are actively choosing where to celebrate.
🔁 Return Visits
Menu Engineering Matrix
Plots every menu item on a 2×2 matrix of popularity vs margin (Stars, Plowhorses, Puzzles, Dogs). Identifies which items to promote, reprice, reposition, or eliminate — with projected margin impact for each change.
🍽️ Menu Profit
Why this cannot be replicated with ChatGPT
Generic AI can explain what food cost percentage means. Signal Engine calculates your theoretical food cost from your actual recipe specs and sales mix, compares it to your actual usage, and tells you that your chicken thigh portion is 18% over spec and it is costing you $340 this week. That requires your data. That is the moat.
✦
Theoretical vs Actual Food Cost — By Item
Not a category average — per-item variance calculated from your recipes and your sales mix. The system knows chicken thigh is over-poured, not just that protein cost is high.
✦
Server PPA Coaching Scripts
The performance engine doesn't just show who is underperforming — it generates coaching for the specific gap. Lisa is missing dessert attachment. Devon is not suggesting premium drinks. Different script, same training session.
✦
Day-Part Margin vs Revenue
Happy Hour has the highest margin in your restaurant. Friday dinner has the highest revenue but margin drops 2.4 pts vs Mon-Thu because turn rate slows. These two facts drive completely different decisions — and neither is obvious without the model.
✦
Turn Rate Bottleneck Identification
The analyzer doesn't say "turn faster" — it tells you the bottleneck is kitchen ticket timing at 28 minutes fire-to-plate on F-Sa and that fixing it to 18 minutes is worth $576 per weekend night.
Your food cost is drifting right now.
Connect your POS and Signal Engine identifies every food cost variance, server gap, and turn rate leak within 24 hours.