The 3 Biggest Challenges with Hotel Data

4 min read

Last month, we sat down with our New York City hotel GMs to talk about how they currently leverage data at their hotels.

Although there's much to be gained, wrangling hotel data is not without its challenges. Our GMs describe their three biggest pain points when it comes to hotel data.

Too little of it...or too much. That's the data paradox. In certain instances, like trying to understand employee productivity, there's little data to be had. Almost all of the hoteliers we spoke with rely entirely on trusting their management and maintaining strong communication channels as ways of staying informed of what their employees are doing all day. And because too little data exists, many General Managers are forced to make these adjustments in a reactionary way.

One GM says he relies mostly on guest reviews. Another only made workload adjustments when his employees were falling short of their weekly tasks. "Ultimately, it all comes down to trial and error," he says. "The sad truth is that we determine workloads based on when things don't get done. It allows us to readjust our goals."

Conversely, there are instances where it's hard to pare the signal from the noise, particularly when it comes to insights to be gleaned from booking. An excess of data makes it hard to prioritize certain information or see larger patterns or trends. One GM summed up this frustration, saying "Usually it's having too much [data] and not knowing what's valuable information and what's just noise. It would be great if there was a way to figure out why discounts are given to guests and how it affects their bookings."

This issue is exacerbated by the siloed reporting functions of the many disconnected systems run within a hotel. The problem with hotel data is that it's scattered, says another of our GMs. "I wish I had a dashboard, a single place where you can get all of the information that you need, at any time, with real time updates, etc."

There's not enough customization. Many of the GMs we talked with bemoan the lack of customization around the reporting of data from these many tools. Dissatisfied with the reporting choices made by those designing the systems, some GMs cobble together reports manually, using personal anecdotes, PMS data and website analytics. Even with this more personalized set of data, it's hard to draw important insights.

Human error.  Even with perfectly tailored reports and integrated systems, data reporting isn't foolproof. As one GM noted, until everything is automated in its entirety (unlikely in hospitality), there will always be human error. "For example, if an employee is not diligent in their approach with ALICE, and they're not finishing and closing tickets as they come up, we're never going to have perfect data," he said. "It's never going to be entirely accurate because it takes time to manually close tickets etc. Even guest reviews aren't infallible. Someone having a bad day or hoping to get a free room for their "complaint" can throw the review and create an unreliable data point."

About ALICE

ALICE is the leading all-in-one hospitality operations platform that enables hotel staff to do their most impactful work. Task management, real-time communication, and operational analytics reduce the complexity and chaos of hotel operations providing the transparency and flexibility needed to run efficiently. Founded in 2013, ALICE works with more than 2,500 hotels and tens of thousands of hotel staff across many of the world's leading brands, including Hilton Hotels & Resorts, Graduate Hotels, and Grupo Posadas. ALICE won 7 HotelTechAwards in 2022: winner of Best Concierge Software & Best Housekeeping Software; finalist for its Guest Messaging, Maintenance, and Staff Collaboration Tools; Top 10 People's Choice; and Top 10 Best Places to Work in Hotel Technology for the fifth straight year. https://www.aliceplatform.com/.

Reputation Management Big Data

ALICE

104 W 27th St
New York, NY 10001
United States

Phone: 212-579-2861
[email protected]
www.aliceplatform.com

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