It was a sunny day in The Hague in 2010 when I, somewhere in between reading the Wall Street Journal and playing Mahjong to train my eye for patterns (all of Ms. Lin’s students will remember), decided I would become a Revenue Manager. I loved strategy, I loved acting on trends, and I loved taking decisions based on data…or so I thought.
NB: This is an article from Lighthouse (formerly OTA Insight)
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What I never anticipated (and what I didn’t sign up for) was that 70% of my time would be consumed by non-revenue-generating tasks: building, updating, and debugging spreadsheets, combing through endless printed reports with a highlighter in hand, and searching for insights. All of this took place before I could make a single strategic decision for my hotel.
Back then, the idea that AI – or any machine – could fundamentally transform my former dream job seemed far-fetched. We were just beginning to implement rule-based pricing engines, which felt revolutionary at the time.
Fast forward to 2024. Today, I have the privilege to be at the center of product innovation at Lighthouse. I’m excited to witness the emergence of an automated, strategy-centred future unfolding for new professionals entering the space who might, at last, be able to live the long lost dream of the strategic revenue manager. Here’s to finally outsourcing low-value-add tasks to AI! And now without further ado, I’d like to share my “favorite” low-value-add tasks that I believe AI can and will soon handle on behalf of progressive RMs.
1. Summarizing and sharing data
You can give everyone at your hotel access to the tool, the tech vendors would tell me back then. I’d just smile. Realistically the operations and sales managers would be too hard pressed for time to reliably access the tool, leaving us revenue managers as the gatekeepers of information to summarize complex data.
And don’t even get me started on ad hoc requests that come via phone or email when a colleague wants to know next Saturday’s forecasted occupancy. AI can and will reinvent how we summarize, translate and share data with all hotel stakeholders in a completely hands-off manner.
From smart email summaries to chat-based interfaces that answer high-level questions quickly, AI will drive data democratization at the hotel level.
2. Finding the needle in the haystack
Spotting patterns helps identify shifts and detect anomalies in data. Unfortunately, when done manually, these skills are often limited to the surface layer of data like pick-up and occupancy rates—the usual metrics found in everyday reports. Assessing whether a specific room type is selling more than usual on a certain day, is something discovered by chance, if at all.
This is where AI really shines. While outlier detection can already be handled effectively through statistical models, AI adds a human touch, revealing not only unusual trends, but also providing insights into what might be driving those changes.
3. Going down the rabbit hole
Every revenue manager has been there: All it takes is an unusual amount of pick-up on a given day and you take the plunge, diving deep into which segment, which rate plan, and which room type has caused the spike.
If you are lucky enough to have a BI tool, it might be a matter of expanding a column. If you do not, it will most likely result in having to pull a number of reports first before even being able to draw conclusions.
AI can surface the driving force behind any occurrence within the data directly and with ease, sparing us painfully manual research to understand root causes.
4. Manually cleaning and mapping your data
Nobody likes to talk about data cleanliness and mapping, but it’s the cornerstone of any analysis, especially if you want AI to work properly.
But, setting up a BI tool for your hotel can be a journey into the unknown, involving: merging, mapping, and sorting through countless profiles, segments and rate codes before being able to leverage the full potential of what the system promises.
AI can play a key role in surfacing and auto mapping relevant combinations for the user, slashing the time it takes to get everything properly set up.
5. Building reports
While we’re not there yet, I truly believe it is just a matter of time before we can stop compiling reports from scratch. Soon, we’ll be able to use natural language interfaces to describe the tables or analysis we want, and the system will generate them in mere seconds.
Long gone are the days when you needed a masters degree in Excel wizardry or Tableau to be able to stand out at your job!
Conclusion
To sum up, there’s plenty to look forward to! AI could be the assistant you’ve always dreamed of, freeing up your time by handling low-value tasks and elevating the role of revenue management. While we’re just getting started on this journey, it’s time to hold your tech vendors accountable for adopting emerging technology and ensuring their systems serve their users well.
