What If Your Forecast Was Never the Problem?
By Charlie Liu ·
Picture a Sunday night. A finance analyst pulling exports from the PMS, the POS, and the labor system, all to get one clean number by Monday morning. Now picture that happening at every property, every week.
It's not that hotel finance teams are bad at forecasting. It's that their data is scattered across a dozen systems that were never built to talk to each other.
The information is already there: occupancy, ADR, labor hours, booking pace. Nothing is missing. It just has to be stitched together by hand before anyone can use it, and that's where the real cost shows up: hours lost every week just getting the data to agree with itself.
The 3 lessons
- Finance creates more value influencing operations than reporting on them. Most hotel finance teams still work on a monthly clock. Close the books, report what happened, move on. By the time that report lands, the month is gone, and a GM can't fix staffing that already ran overtime three weeks ago. Finance is most useful when it moves at the speed of the hotel.
- The obstacle isn't forecasting. It's connecting the data. Ask any FP&A lead what's standing between them and a better forecast, and technique rarely comes up. What comes up is the export, the reconciliation, the version of the workbook that's two systems out of date by the time anyone opens it. Fix the plumbing and the forecasting problem mostly solves itself.
- AI rewards a clean foundation, not another tool. AI only becomes valuable once the underlying operational data is connected and trustworthy. Layer AI on top of fragmented systems and all it does is automate the mess faster. The hotels that win with AI won't be the ones with the newest tool. They'll be the ones who connected their data first.
What actually changes when occupancy drops 2 points
A hotel with connected data can trace one number through every lever it touches in minutes. A hotel without it finds out at month end.
- Staffing: trim the schedule so the property isn't overstaffed against lighter demand
- Pricing: check whether a competing event just got cancelled or a market shift is underway
- Marketing spend: adjust if the drop signals a softer month ahead, not just a blip
By the numbers
Otelier's recent hotel operations research found:
- 27% of hotels run more than seven separate technology platforms
- 27% of teams spend over 11 hours a week just reconciling data across them
That's more than a full workday, every week, spent making systems agree with each other before anyone can even start planning.
So before the next planning cycle, a few honest questions are worth sitting with:
- How long does your current forecast actually take, start to finish?
- What data is still getting massaged by hand every month?
- Which process breaks if the one person who understands it leaves tomorrow?
- How many manual exports is your team running right now?
The answers usually point to the same place. Finance can run at the speed of the hotel instead of always looking backwards, but only once the data underneath it is connected enough to trust.
If you want to dig into where that time actually goes, Eugene and Ian Lawless took a live look at fixing it on July 28. See the session.
Sources
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