Covers are up, yet prep-time and waste keep slipping
Question
We are busier than last quarter and weekend covers are great. But tickets bunch at peaks, a few dishes are 86’d early, comps rise when expo jams, and waste logs are up after close. Reviews mention slow mains despite a full floor. How can service feel brittle when the top-line looks strong?
Answer ✅
Totals can be up while cadence slips. If prep-time variance widens, stations run hot, or purchasing/par levels drift, you can seat more guests yet deliver slower, 86 more items, and dump more food. SSM-Audit adds a stability band beside the KPIs you already track so you see whether service is calm and repeatable or spiky and luck-dependent—before reviews and margins suffer.
What the bands would have shown 📊
• Table turn-time stability sliding A+ -> A0 (larger variance at peak hours)
• Kitchen prep-time stability degrading to A- (grill/saute tickets queue unevenly)
• Ticket cadence weakening A0 -> A- (orders bunch; expo becomes a choke point)
• 86 incidence stability tilting A0 -> A- (stockouts cluster before peak ends)
• Waste per cover stability softening A+ -> A0 (prep overages, more end-of-night dump)
• Staff schedule stability dipping A0 -> A- (skill mix thin in key slots)
What to do now 🛠️
- Band the service loop: seat -> order -> prep -> expo -> serve -> close. Track bands by 30-min buckets.
- Peak menu mode: when prep-time band < A0, switch to a slimmer line-up and pre-portion high-variance items.
- Rebalance stations: if ticket cadence band < A0, shift dishes across stations and add a floater during banks.
- Par levels by band: when 86 band < A0, raise pars on fast movers and split deliveries earlier in the week.
- Waste control: if waste band slips, tighten prep windows and use cross-utilization for end-of-night items.
- Roster discipline: when schedule band < A0, adjust skill mix and lock a second expo or lead line at peak.
How SSM-Audit helps (practicalities) 🌟
• No additional infrastructure: runs beside POS, kitchen display, purchasing, and waste logs.
• Numbers unchanged: covers, prep times, and costs stay the same; stability is a read-only overlay.
• Easy to use: spreadsheet/BI friendly; one lightweight weekly review with FOH and BOH leads.
• Universal language: A++ / A+ / A0 / A- / A– aligns owners, chefs, and managers fast.
CLI 💻 — try our mini Calculator to identify the drift
(Mini CLI Download Page)
Feed your CSVs and see bands and drift at a glance (numbers unchanged).
# Table turn-time stability (seat -> pay)
ssm_audit_mini_calc restaurant.csv --kpi "Table Turn-Time Stability" \
--out bands_turn.csv --plot_kpi "Table Turn-Time Stability" --build_id r
# Kitchen prep-time stability (per station)
ssm_audit_mini_calc restaurant.csv --kpi "Prep-Time Stability" \
--out bands_prep.csv --plot_kpi "Prep-Time Stability" --build_id r
# Ticket cadence (orders per 5-10 min; bunching)
ssm_audit_mini_calc restaurant.csv --kpi "Ticket Cadence" \
--out bands_tickets.csv --plot_kpi "Ticket Cadence" --build_id r
# 86 incidence stability (stockouts per service window)
ssm_audit_mini_calc restaurant.csv --kpi "86 Incidence Stability" \
--out bands_86.csv --plot_kpi "86 Incidence Stability" --build_id r
# Waste per cover stability (prep overage/dump)
ssm_audit_mini_calc restaurant.csv --kpi "Waste per Cover Stability" \
--out bands_waste.csv --plot_kpi "Waste per Cover Stability" --build_id r
# Staff schedule stability (skill mix by slot)
ssm_audit_mini_calc restaurant.csv --kpi "Staff Schedule Stability" \
--out bands_staff.csv --plot_kpi "Staff Schedule Stability" --build_id r
Outputs you will get:
• CSVs with stability bands for each timestamp (e.g., bands_prep.csv).
• Drift charts per KPI (--plot_kpi) showing exactly where service cadence breaks.
• Optional alerts if you enable thresholds in your setup.
Technical notes
Representation: x = (m, a) with a in (-1, +1)
Collapse parity: phi((m,a)) = m
Order-invariant pooling:
U = sum(w_i * atanh(a_i))
W = sum(w_i)
a_out = tanh( U / max(W, eps_w) )
Typical bands (example):
A++: a >= 0.75
A+: 0.50 - 0.75
A0: 0.25 - 0.50
A-: 0.10 - 0.25
A--: a < 0.10
Navigation
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Page disclaimer
Illustrative scenario for research and education. Observation-only; do not use for critical decisions without independent validation.
SHUNYAYA 