People Are People: The Human and Data Faces of Hospitality

At its heart, hospitality is all about helping and caring for each other. But when you dig deeper, there's (way) more to it than meets the eye. The word "hospitality" comes from the Latin "hospes/hostis," which (interestingly enough!) means both "guest" and "enemy" (and I am pretty sure that, if you're a hotelier, you felt this dual feeling towards your guests at least once in your career...) That being said, this bit of history shows us that hospitality has many layers and isn't just about the service we see on the surface. Beyond just dealing with people, the hospitality industry is also deeply involved with data, and that is true for the whole travel sector. Hospitality, food, and travel in general are (of course) people-industries, but they're also data-industries. Not convinced? Did you know that a single airplane engine can produce up to 10 GB of data every second? That's the equivalent of 200 music albums, to put things into perspective. However, even with all this data floating around, these information are rarely (if ever) used to their full potential. The bottom line is that hospitality isn't just about humans; it's also very much about numbers, and that's something that's becoming true for every single sector.

Master and Servant: The Reddit Revelation

Reddit is a fascinating example. What started (and still is) as a cool place for sharing news, rating content, and discussing various topics, has become something else entirely. Its value skyrocketed from $0.5 billion in 2014 to $6.4 billion at the time of its recent IPO, showing its significant impact on the digital world. But what, exactly, changed? The key to Reddit's increased value (very likely) lies in its vast collection of posts (over a billion!) and comments (16 billion). This data treasure is perfect for training sophisticated AI models, such as ChatGPT, Gemini, or Claude, highlighting a shift in how the tech industry values data for innovation. Case in point: it's not surprising that the Federal Trade Commission is keeping an eye on Reddit, mainly because of their willingness to use their user-generated content with third-party AI companies. Icing on the cake, the details from Reddit's IPO filing also highlight its financial and ownership structure, revealing that Sam Altman (rings a bell? Yes, he’s the CEO and co-founder of OpenAI) holds an 8.7% stake, making him one of the largest shareholders... Kinda makes sense now, doesn't it?

Policy of Truth: Elon Musk's Twitter Gambit

Let's make another example: Elon Musk's takeover of Twitter in 2022 followed a similar trajectory. Skeptics (including myself) were initially wary because of Twitter's financial struggles, but Musk had bigger plans focused on artificial intelligence (let's not forget Musk served as one of the initial Board of Directors members of OpenAI...). He saw Twitter's enormous collection of public tweets as a goldmine for training his AI models (namely, xAI and Grok). This shift in strategy highlights a change in how Twitter is viewed and perceived: moving from just a place for (kinda toxic, we all agree) tweets to a vital data source for AI training and technological advancements. Not unlike the abovementioned airplane engine, every day, Twitter is flooded with around 500 million tweets. This constant data stream is an invaluable asset for training AI models. Moreover, Twitter's data has value beyond language and sentiment analysis. Because of its vital role in global conversations and political communication (and fights and bans!), the platform's data is extremely useful for political polling, predictive analytics, and forecasting social and political trends. Digging into the massive amount of user-generated content on X/Twitter opens up unique opportunities for Musk to grasp the nuances of public opinion, electoral behavior, and shifts in societal attitudes as they happen. Again, was it a mistake buying Twitter? Maybe the answer is not so obvious…

Behind the Wheel: Tesla's Data-Driven Journey

Talking about Musk, Tesla is another interesting example. Over time, I convinced myself that, at least to a certain extent, Tesla is not a car company, but a data company. They have built their main competitive edge on data. Tesla's vehicles are equipped with sensors and cameras that gather data, allowing the AI systems to detect potential road hazards like other vehicles, pedestrians, and obstacles. Furthermore, Tesla uses big data analytics to refine the driving experience, optimize routes based on traffic patterns, road conditions, and weather, and make journeys more efficient and enjoyable. Recent data supports the effectiveness of their approach, at least in terms of safety, showing that Tesla’s Autopilot is significantly safer than the US average (human) driver and even safer than driving a Tesla without autopilot. This clearly illustrates that Tesla's mission transcends merely manufacturing cars; it's about leveraging data to change mobility and transportation (and maybe more).

Everything Counts: The Paradigm Shift in Hospitality

Back to hospitality: considering the abundance of data floating around in a hotel—like check-in/out dates, names, booking sources, booking pace, guest preferences, and market trends—wouldn't it make sense, not unlike Reddit, Twitter, and Tesla, to actually use these data, for once? Perhaps, like these companies, it's time we re-evaluate our industry and recognize that all these pieces of information are, in fact, a significant asset, maybe our MOST significant asset. So the next logical question we should ask is: How valuable are these data? I'd say very much. So the following piece of the puzzle should be: how can we access them? Well, here's where things become a little more complicated, and it's (mainly) our fault. Yes, because property management systems are probably the primary guardians of data, often by (commercial) choice. In my view, the conversation around PMS should probably focus less on "enhancing the guest experience" (a phrase that often feels more like a marketing stunt, as -let’s face it!- no guest will ever get in touch with the PMS) and more on making all this valuable data actionable. In a nutshell, we should start viewing data as a form of currency. Not because it's cool or because we're geeks (and we are), but just because every other industry in the world is already doing it, and we should not be left behind.

Strangelove: The New Era of Property Management Systems

Just like industry giants such as Reddit, Twitter/X, and Tesla, it's crucial for us to recognize data as the cornerstone of our business. Treating data as currency should be a hospitality guiding principle from now on. Especially because we don't even know why and how we'll be able to use these data in the future. Traditionally, data's role in our industry has been mainly confined to refining ad targeting or making revenue management decisions. However, their potential stretches far beyond that—into shaping actionable insights, training AI models, and crafting precise predictions. I've often joked about the lack of glamour in owning a PMS company. Sure, it's an exaggeration (but is it?), but it underscores a reality: PMS are not seen as the most thrilling part of our industry. Some tried to change (and sell) this narrative, but -look, this comes from an insider-: there's nothing less "sexy" than a PMS (maybe accounting software, but I am not even sure about that!).

World in My Eyes: Rethinking Our Approach to Technology

Yet, the tide is turning. We're now poised to inject some much-needed allure back into the space. Historically, hotels viewed PMS more as a burdensome necessity than a valuable tool, regarding them as inconvenient costs rather than valuable assets. To a certain extent, this perspective began to shift when "new blood" entered the market with a promise: PMS could smooth out the guest experience, making these systems suddenly captivating. Maybe, yet I feel that the actual value lies in harnessing actionable data for meaningful purposes—automating mundane tasks, predicting guest behavior more accurately, and easing friction across departments. Particularly in revenue management, the wealth of data at our disposal, coupled with the newfound affordability of processing technologies (everyone can use ChatGPT’s APIs relatively easily), empowers us (probably for the first time) to not just anticipate demand but actively generate it. This paradigm shift marks a pivotal moment for our industry, where data doesn't just inform our strategies—it DEFINES them.

Stripped: Unveiling the Data Revolution in Hospitality

I've always been captivated by the varied approaches to technology across our field. Most Property Management Systems vendors, particularly those emerging from the innovative wave of cloud-native, open-API platforms, seem to deliberately distance themselves from the traditional image of a PMS. Some go as far as to altogether reject the PMS acronym. I believe they're correct in challenging the status quo, though perhaps not always for the right reasons. Our goal isn't merely to produce flashy PMSs to dazzle the market. Instead, we possess a rich vein of data that allows us to rethink the essence of our roles for the first time in travel history. Sure, we're tasked with dismantling silos, enhancing our API quality, and broadening our mindset to include integrations beyond just channel managers and RMSs, extending to LLMs, pre-training transformers, and beyond. Yet, achieving this could democratize an industry long dominated by gatekeepers. The future, after all, is really just one prompt away. 

It might not be as sexy as some vendors make it out to be.

But, I promise, it will be fun.