Ultimately, will AI replace the revenue manager or not?
Last week at HITEC in Toronto on ‘Stage A’ Sébastien Leitner, VP Partnerships at Cloudbeds spoke to Sarah Major-Bourgeois, Director of Distribution at Germain Hotels, and Jens Munch, CEO at Pace Revenue, to find out what challenges the revenue manager faces and how AI will impact their work in the future. Ultimately, will AI replace the revenue manager or not?
Sarah started by informing that Germain Hotels does not use a revenue management system at all. “We are a Canadian family-owned business behind Le Germain, Alt and Escad Hotels with over 2,500 rooms across 18 hotels. We are not using a revenue management system, as it’s not part of the DNA – we’re a more guest-centric hotel group, and we determine a specific price by looking at the same data other hotels do. However, we started to put a bit more energy into revenue management recently, so that we could grow more strategically – we recruited a new Revenue Manager, which means that we are headed that way.”
Jens Munch from Pace, a leading innovator focused on decision intelligence in the hotel revenue management space, argues that access to a good RMS is key for optimal pricing and growth: “Revenue management is a diverse set of many different activities – from the very tactical to more strategic areas. A typical thing customers say is ‘I never thought I could sell at this price’ [An RMS infused with AI and ML can help achieve these prices.]”
Sebastien asked whether automation can help hoteliers identify changes and patterns, but also questioned when the AI machine actually starts to do something, rather than just listening to changes.
“All these terms – AI etc. – are just ways of getting data points,” said Jens. “That’s where machine learning comes in – it can run all of these simulations at the same time. At Pace, we update all of our data points every hour. In some cases, we can identify various different times over the space of 24 hours where demand was high, so we may be changing the [room] price up to 12 times per day Machine learning keeps an eye on everything and changes the price accordingly.”
But Sarah didn’t see how AI could capture every single piece of human detail.
Jens responded: “It’s important that you know how AI works. We can’t make AI work until we know the full picture. We therefore need the strategic input [from our customers] and visibility right down to things like email threads for the AI to be able to interpret certain individual scenarios. But strong surges of bookings over one weekend, we can analyse that. This is one thing we are always working on.”
Sebastien finished the session by asking what hoteliers should worry about: “Should we be worried about AI and Chat GPT?” Jens said: “We need to worry about solving the problems we were talking about five years ago, and focus on having all our data in one place where it’s easily accessible. Let’s solve that before we get too carried away with where we’ll be in ten years’ time.”
When asked what she’d like to see in her future RMS, Sarah said: “I want to be able to delete repetitive tasks, I want access to accurate data that’s easily digestible and relevant, and I want to be enabled to do things that are aligned with our goals, that are not necessarily on the books of the Marriotts and Hyatts of this world.”
Theodore is the Co-Founder and Managing Editor of TravelDailyNews Media Network; his responsibilities include business development and planning for TravelDailyNews long-term opportunities.
