Many owners track sales and covers. Fewer track what happens in the 3 to 10 minutes between parties.
That gap is where table-flow profit leaks.
Quick Summary
- Turnaround time is a workflow metric, not a guest-pressure metric
- Measure by daypart first, then fix the slowest handoff
- Use turnaround time and RevPASH together to avoid false wins
- Run a 14-day test before changing SOP across the whole floor
Why This Matters in 2026
BLS data (January 2026 release) still shows food-away-from-home prices up year over year. NFIB data also shows persistent operating pressure for small owners.
When costs rise, service-window efficiency matters more. If your reset flow is slow, volume growth does not fully convert to margin.
Core Turnaround Formula
turnaroundTime = nextSeatedTimestamp - previousPartyLeftTimestamp
Track median by daypart:
medianTurnaroundTimeByDaypart = median(all turnaroundTime values in that period)
Then pair with:
revpash = sales / (seats x serviceHours)
Worked Example (Dinner Window)
Assumptions:
- Seats: 72
- Dinner service: 5 hours
- Sales: $5,760
- Median turnaround before fixes: 8.5 min
- Median turnaround after fixes: 5.5 min
RevPASH baseline:
revpash = 5,760 / (72 x 5) = $16.00
If shorter reset time allows one extra full table use cycle on key sections, that usually raises effective throughput without changing menu price.
14-Day Turnaround Test
Days 1-3: Baseline
- timestamp party leave and next seat
- capture median by daypart
- note top bottleneck reason (bus delay, host queue, payment lag)
Days 4-10: Two changes only
- reset handoff script (server -> bus -> host)
- payment-close timing rule (check timing + handheld flow)
Days 11-14: Hold and evaluate
- compare median turnaround time
- compare RevPASH
- compare guest complaints and remake rate
Keep only changes that improve dollars and keep guest signal stable.
Common Bottlenecks
- Check-close delay at table end
- No owner of reset handoff
- Host seating queue not synced to floor status
- Inconsistent reset standard by shift
Fix one bottleneck at a time. Multi-change rollouts hide cause and effect.
Mistakes to Avoid
- Measuring averages only (median is more useful for flow)
- Pushing guest departure instead of reducing internal delay
- Improving turns while ignoring service quality signals
- Rolling out floor-wide before one-section validation
Related Guides
- What Is Table Turnover Rate?
- Table Turnover vs Check Average Guide
- Restaurant Table Turnover Calculator (80-Seat Example)
- Break-Even Sales Calculator
- Prime Cost Guide
KitchenCost helps you connect item mix, service windows, and margin impact in one weekly review rhythm.
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