Hours moved from empty mornings to the evening crush
A three-property Singapore group cut average check-in wait 40% while reducing front-office hours 7%, hourly arrival forecasts from Mews staffed the 17:00–20:00 peak for the first time, and a cross-property float pool moved capacity to whichever desk peaked first. Hiring stayed capped throughout.
Measured results, properties anonymized at client's request. Metrics verified against an agreed baseline.
The problem: the roster ignored the arrival curve everyone could see
Arrivals in Singapore business hotels cluster hard after 17:00, late flights, late meetings. The group's desks ran six agents flat from 08:00, so mornings idled while the evening queue passed fifteen minutes again and again at the flagship. Guests wrote reviews about the queue.
What changed
Mews arrival data became an hourly staffing forecast per property; the roster followed the curve, and cross-trained floaters covered whichever property's wave arrived first. The hotel data insights view behind it →
The data behind this chart
| Hour | Staff required | Old roster | Demand-matched roster |
|---|---|---|---|
| 08:00 | 3 | 6 | 3 |
| 10:00 | 3 | 6 | 3 |
| 12:00 | 4 | 6 | 4 |
| 14:00 | 4 | 6 | 4 |
| 16:00 | 6 | 6 | 6 |
| 17:00 | 9 | 6 | 9 |
| 18:00 | 10 | 6 | 10 |
| 19:00 | 9 | 6 | 9 |
| 20:00 | 7 | 6 | 7 |
| 22:00 | 4 | 6 | 4 |
“Reviews stopped mentioning the queue. Same team, same buildings, the hours just moved to where the guests were.”
HotelCadence is workforce software for hotels. It reads the bookings already in your property system, forecasts how busy each department will be hour by hour, builds the roster to match, records worked hours and prepares payroll. Department heads approve every roster. From US$6 per scheduled employee per month.
How can wait time fall 40% while hours fall 7%?
The old roster was both overstaffed and mis-timed: six agents all day meant surplus at 10:00 and a queue at 18:00. Staffing the arrival curve put nine or ten agents on the evening peak and three on quiet mornings, fewer total hours, far more of them in the hours guests arrive.
What is the cross-property float pool?
A cross-property float pool is a small team of cross-trained front desk agents shared by properties within walking distance, assigned each day to whichever desk the hourly arrival forecast says will peak first. Because all three properties run Mews, one hourly arrival forecast covers the cluster, so capacity moves and headcount stays flat.
Why not just hire more agents?
Singapore's labor shortfall is projected to shave up to 1.4 points off sector growth, the hiring cap was a market reality. The group ran 81% occupancy; the only lever left was pointing existing hours at the peaks.