Case study · Bali · Mews

Labor that breathes with the season

A Bali resort running three F&B outlets on Mews cut low-season F&B labor-to-revenue by 14%, outlet-level demand forecasts consolidated outlets on forecast-quiet monsoon days, while high-season service was left exactly as it was. Guest satisfaction held through both seasons.

−14%F&B labor-to-revenue, low season vs baseline
48%January occupancy, with full rosters in 3 outlets
77.9%of Indonesian reservations arrive via OTA, short-leadIndustry data

Measured results, property anonymized at client's request. Metrics verified against an agreed baseline.

The problem: APAC's lowest F&B revenue per room, staffed like peak week

APAC hotels earn the region's lowest F&B revenue per available room (~US$43.90), which makes idle outlet hours expensive. In monsoon January the resort ran ~48% occupancy, yet the beach grill, lobby café and main restaurant all kept full brigades, because the roster was a copy of December's.

What changed

Mews reservation and covers data became per-outlet demand forecasts. On days two outlets forecast under 30% capacity, the schedule consolidated service into one, staff rotated rather than stood idle, and the change was visible to guests only as a shorter walk. How outlet-level forecasting works →

BeforeAfter
0%20%40%60%JanMarMayJulSepNovBefore 30%After 29%Jan, Before: 41% · After: 35%Feb, Before: 42% · After: 36%Mar, Before: 36% · After: 33%Apr, Before: 33% · After: 31%May, Before: 31% · After: 30%Jun, Before: 29% · After: 29%Jul, Before: 27% · After: 27%Aug, Before: 26% · After: 26%Sep, Before: 29% · After: 28%Oct, Before: 32% · After: 30%Nov, Before: 36% · After: 32%Dec, Before: 30% · After: 29%
F&B labor as % of F&B revenue by month: the after-year (teal) pulls the monsoon hump down 5-6 points while peak months stay unchanged, labor now breathes with the season.

The data behind this chart

MonthBefore (%)After (%)
Jan4135
Feb4236
Mar3633
Apr3331
May3130
Jun2929
Jul2727
Aug2626
Sep2928
Oct3230
Nov3632
Dec3029
“Low season used to mean watching payroll eat the P&L. Now the quiet weeks cost what quiet weeks should cost.”
Resort General Manager
Where does a 14% low-season saving come from?

January-February occupancy dropped to ~48% but all three outlets kept full rosters. Outlet-level covers forecasts showed two outlets running below 30% of capacity on weekdays, consolidating them on forecast-quiet days cut paid hours while total resort covers were still served.

Why did high season stay untouched?

The optimizer schedules to the service standard first. In July-August the forecast demanded full rosters across all outlets, so it rostered them, the labor-to-revenue line barely moves in peak months because it was already close to right.

How do OTA-heavy bookings affect this?

Indonesian resort bookings are OTA-dominated (77.9% of reservations) and short-lead, which makes month-out gut forecasts especially wrong. Pickup-driven forecasts from Mews re-read the book daily, so quiet days are called days ahead, not discovered at service time.

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