conceptsix-degrees last reviewed 2026-06-11

Six Degrees β€” Labour vs Sales (weekly snapshot)

Context

First cross of Tanda rostered labour against PowerEPOS sales for the same week (2026-06-01 β†’ 2026-06-07). Hours are rostered (net of breaks), aggregate only β€” no individual data, no wage values. Revenue-per-rostered-hour is the efficiency proxy until wage-cost data is in scope.

Detail

DayRostered hShiftsRevenueTxnsAvg ticketRev / rostered h
Mon 06-01124.721$12,105262$46.20$97.07
Tue 06-02259.240$7,521174$43.23$29.02
Wed 06-03243.739$4,13796$43.09$16.98
Thu 06-04261.740$4,772118$40.44$18.24
Fri 06-05303.247$4,256155$27.46$14.04
Sat 06-06250.038$9,201305$30.17$36.81
Sun 06-07140.521$4,701110$42.74$33.46
Week1,583.0246$46,6941,220β€”$29.50
xychart-beta title "Rostered hours vs revenue by day" x-axis [Mon, Tue, Wed, Thu, Fri, Sat, Sun] y-axis "Hours / Revenue ($00s)" 0 --> 320 bar [124.7, 259.2, 243.7, 261.7, 303.2, 250.0, 140.5] line [121.0, 75.2, 41.4, 47.7, 42.6, 92.0, 47.0]

Bars = rostered hours; line = revenue in $hundreds.

What stands out

Control week: 2026-05-25 β†’ 31 (no holiday, actual worked hours)

To test the Friday finding, the prior week was pulled using worked timesheet shifts (not roster) against the same sales source:

DayWorked hShiftsRevenueTxnsRev / worked h
Mon 05-25130.421$2,01058$15.41
Tue 05-26255.140$6,710178$26.30
Wed 05-27254.141$5,258146$20.69
Thu 05-28234.138$3,91697$16.73
Fri 05-29286.943$10,986274$38.29
Sat 05-30255.539$14,839485$58.08
Sun 05-31155.424$13,453297$86.57
Week1,571.5246$57,1721,535$36.38

What the two weeks together actually show:

6-week trend (2026-04-27 β†’ 06-07) β€” conclusive

Extended with four more worked weeks (1,057 timesheet shifts aggregated). Same method, same sources.

Weekly totals β€” the template roster is confirmed:

Week (Mon-start)HoursShiftsRevenueRev/h
Apr 271,594.3262$39,833$24.98
May 041,596.9254$45,939$28.77
May 111,616.5256$39,817$24.63
May 181,582.8255$43,389$27.41
May 251,571.5246$57,172$36.38
Jun 011,583.0246$46,694$29.50

Labour sits in a Β±1.4% band (1,571–1,617 h) for six straight weeks while revenue swings 44% ($39.8k β†’ $57.2k). The roster does not respond to demand.

Weekday averages (6 weeks):

DayAvg hoursAvg revenueAvg rev/hRange ($/h)Verdict
Mon136.7$5,415$41.2215.41–97.07Light roster β€” fine (holiday-skewed avg)
Tue268.6$6,627$24.8914.88–30.232nd-most-staffed day β€” watch
Wed257.8$4,035$15.7211.28–20.69Confirmed over-rostered β€” never beat $21/h
Thu258.9$3,912$15.0910.01–18.24Confirmed over-rostered β€” never beat $19/h
Fri292.5$7,828$26.9814.04–38.29Most-staffed; volatile, roughly earns it
Sat238.1$11,633$48.8236.81–58.08Benchmark β€” best day, fewer hours than Wed/Thu
Sun138.3$6,024$42.2228.35–86.57Light-but-mighty

The killer stat: Saturday is rostered ~20 h/day LESS than Wednesday or Thursday while earning ~2.9Γ— their revenue. Wed+Thu together consume ~517 h/week at ~$15/h β€” if they merely matched Tuesday's efficiency (~$25/h) at current revenue, that's an indicative ceiling of ~190 h/week of trim potential (~12% of total hours). Treat as a ceiling, not a target, until the per-team split and manager context are in.

Caveats

Actions

Provenance

Computed 2026-06-10 (extended 2026-06-11) from Tanda GET /rosters/current (week 2026-06-01..07, rostered hours net of breaks) and GET /shifts (weeks 2026-04-27..05-31, 1,303 worked shifts net of breaks), each aggregated per day with no individual records retained, joined against Aspire Smart Dashboard get_daily_sales (PowerEPOS) for six-degrees.

Related

πŸ”— Relationships

graph LR labour_vs_sales["labour-vs-sales"]:::self labour_vs_sales --> staffing_pattern["staffing-pattern"] labour_vs_sales --> staff_directory["staff-directory"] labour_vs_sales --> venue_profile["venue-profile"] classDef self fill:#715EE3,color:#fff,stroke:#291F50;