The Housekeeping Productivity Number That Looks Too Good
You supervise housekeeping at a 140-room select-service hotel. The department standard is 16 rooms per 8-hour shift for a room attendant, with a 30-minute lunch and two 15-minute breaks. Last month the team averaged 18.5 rooms per attendant per shift, and the executive housekeeper (your peer, not your report) cited this in a meeting as proof the standard should be raised to 19. You notice three things: the property has been running 78% occupancy, so most attendants are cleaning stayovers rather than checkouts; two of your most experienced attendants left six weeks ago and were replaced by new hires; and the 'rooms cleaned' figure comes from the PMS, which counts a room as cleaned when the status is flipped, not when the attendant finishes. You also have a stack of three guest complaints about bathrooms in the last two weeks.
1. Should you support raising the standard to 19? Defend your answer with the evidence in the setup.
Read the worked answer
No - and the reason is that the 18.5 figure does not measure what the standard measures.
- Mix effect. The standard of 16 assumes a blend of checkouts and stayovers. At 78% occupancy with a stable in-house base, a large share of rooms are stayovers, which take materially less time than a departure clean. A high average under a stayover-heavy mix says nothing about whether an attendant can do 19 checkouts.
- Experience effect. Two experienced attendants left six weeks ago. New hires are typically slower for the first several months, which means the 18.5 was achieved despite a drag, not because the job got easier. Raising the standard now would land hardest on the least experienced staff.
- Measurement effect. PMS status flips are an administrative timestamp, not a labor timestamp. If status is flipped early or in batches, the productivity number is inflated by definition.
- Quality signal. Three bathroom complaints in two weeks is a leading indicator that the current pace may already be too fast. Productivity gains that show up as complaints are not gains; they are deferred cost.
What to propose instead: report rooms by type (checkout vs. stayover), measure actual clock time per room from a sample, and revisit the standard after the new hires clear their ramp-up period. Offer to run the study with the executive housekeeper rather than arguing from opinion.
2. Design the measurement you would bring to the next meeting. What would you collect, over what period, and what would you do with it?
Read the worked answer
Collect a two-week time study, stratified by room type, not a single average.
- Sample: at least 20 checkouts and 20 stayovers across attendants with different tenure, including the new hires.
- Measure: start and stop time per room from the attendant's own log (or a simple paper slip), plus the room number and type. Do not use PMS status.
- Also capture: number of rooms the attendant was assigned that day, and any guest complaint tied to that room within 48 hours.
- Output: minutes per checkout and minutes per stayover, with a range, not just a mean. Then compute what a realistic daily room count looks like at the current mix.
How to use it: bring the distribution to the meeting. If checkouts average, say, 34 minutes including setup and travel, then a 19-room day of checkouts is arithmetically impossible inside an 8-hour shift with breaks - that ends the argument with data instead of seniority. If stayovers average 18 minutes, you can show that the 18.5 figure is explained entirely by mix.
Then commit to something. Offer a target for the new hires (e.g., 13 rooms for their first 60 days, stepping to 16), and agree to re-run the study in 90 days. A supervisor who only says no is a blocker; a supervisor who says 'no, and here is the study and the ramp plan' is a manager.