We know we don’t have to convince you that we’re living in a Big Data world, or that there is tremendous opportunity buried in all that data. The hotel industry has been talking about it for a few years now. Hoteliers recognize that there are new insights that can help to improve the guest experience, optimize operations to control costs, increase guest value and drive revenue and profits, locked in the data the business and the market generate every day.
This is the Big Data mantra we repeat back to anyone who will listen. However, in many cases, everything beyond this high-level mantra remains a bit mysterious, and justifiably so. The world of Big Data is full of math, computer science and tiny, geeky details. It’s hard stuff, and most information about it is hard to understand. In this two-part series, we’ll talk about the evolution of technology, Big Data and analytics in hospitality – to help you see how we ended up where we are today (and explain it to your bosses). Then, we’ll follow up with a discussion about data science – the methods, people and technology that will help you unlock the value from your Big Data.
As you read the (highly simplified) history of hospitality technology, data and analytics below, remember that early adopters were ahead of this timeline. We are referring to the eras when the technology, data and analytical applications became relatively mainstream in hospitality.
Technology in Hospitality, A History Lesson
Thinking back to the earlier days in hospitality technology (1980s and earlier – hence the Madonna tribute), the technology footprint at hotels was relatively small. There was enough to hold a reservation, check a guest in, charge them and reconcile the books. Technology was primarily used for financial controls. Since the guest had to contact the hotel or an agent to make a booking, the guest relationship was relatively direct and relatively personal, right from booking on.
When hotels followed the airlines in adopting GDS (global distribution systems) in the 80s, their reach was extended, but the one-to-one relationship between guest and hotel or agent remained the same, as did the amount of data that was generated. Hotels still collected transactional data, and still used it mainly for control purposes.
1990s – Inventory Transparency
In 1990s CRS (central reservation systems) were introduced, providing access to real-time inventory information. Guests could get instant confirmation of reservation requests, but their methods of interaction with the hotel and the data collected didn’t change. This was the era of inventory transparency.
The 1990s also saw the spread of hotel loyalty programs, again adopted from the airline industry. Hotels started gathering guest demographics and stay history, and quickly realized that maintaining guest databases was quite different from maintaining transaction history. It’s easy for profile information to be incomplete or inaccurate. Many hotels are still struggling with this today.
The 1990s also saw the emergence of the first advanced analytical application in hospitality – revenue management. Hotels realized that they could maximize the value of their capacity constrained inventory by varying prices according to demand patterns. By forecasting demand and using an optimization algorithm to pick the rates that maximized revenue, hotels could realize significant revenue gains. These systems and processes focused on inventory optimization – opening and closing rates, or controlling inventory availability.
2000s – Price Transparency
And then everything changed.
In the 2000s came the internet, which fundamentally changed the way hotel rooms were sold, and paved the way for the Big Data era. A big digital wall slammed down between hotels and guests, cutting off the direct and personal relationship.
The 2000s were the era of price transparency. As the OTAs came on the scene and hotels began to transact online, it suddenly became much easier for consumers to compare prices across a market. Hotels, therefore, had to start competing more directly on price. Just when hotels were starting to get comfortable with the revenue management practices of the 1990s, suddenly, with price transparency, the systems needed to consider the impact of price on demand, or price optimization. This is a change that most hotels (and systems) are still adapting to today.
New data sources began to emerge. Competitor prices could be collected and analyzed. As hotels began to move advertising to digital channels like email and web advertisements, new marketing metrics like click-throughs and email open rates became important.
2010-2014 – Value Transparency
Just as hotels were becoming comfortable with the e’s – e-commerce and email – along came the next technology evolution, the social web. This is where Big Data really begins to impact hospitality. A definition of Big Data is “when the volume, variety and velocity of data exceeds an organization’s ability to store and process it at the speed of business” (Gartner, 2001). Although data volumes had started to increase in the 2000s, the social web created volumes of entirely new sources of data in the form of text reviews, ratings, video, audio and images, along with intricate networks of relationships among guests and potential guests. It’s unstructured, meaning it doesn’t fit into the same neat rows and columns as transaction or even guest profiles do.
With service triumphs and mistakes available for the virtual world to see, the early 2010s became the era of value transparency. Guests now have access to the opinions and experiences of previous travelers to balance against room prices. Hotels now need to understand not just their price position, but also their perceived value, as expressed in social commentary.
Interestingly, the advent of the social web broke through the digital wall, creating a new opportunity for a direct and personal relationship with guests.
This period saw the next application of advanced analytics – predictive modeling using guest data. Hotels are now starting to use analytics to predict guest value, likelihood to respond and next best actions.
2015 through Today – It’s Going Faster
The pace of technology development is accelerating, so we can no longer measure it in decades. The post 2015s added the i’s (iPhone®, iPad®) to the e’s (e-commerce, email). As mobile exploded, it’s now possible to know exactly where the guest is, and influence their next action directly. Location data explodes the volume of data once again, and accelerates the importance of responding to velocity as well. You could say even the guests are becoming transparent…whether they like it or not.
Where Do We Go from Here?
Looming on the horizon is the Internet of Things. Devices connected to the internet stream constant status updates. In this volume and variety of fast data, there are presumably even more opportunities to optimize operational efficiency, drive revenue and profits, and improve the guest experience. If only we can access, store and unlock insights from data at the speed of business.
You can see from the history lesson in this article, that each evolution in technology drove evolutions in available data, and the complexity of that data. This also increased the complexity of the solutions required to unlock the value from that data. When you look at this evolution a few things become clear:
1. We can’t handle this amount of data manually. Routine data acquisition, cleansing and analysis tasks must be automated to keep analysts focused on making decisions rather than manipulating data.
2. Routine analysis and decisions also must be automated. Advanced analytics like forecasting, predictive modeling and optimization can replicate the best decisions of your best decision makers, freeing up their time to handle the exceptions.
3. This isn’t going to slow down. Hoteliers must stay educated on technology, data and analytics trends. There is a great deal of technical detail and misleading information out there. We’ll keep helping you decipher it!
Of course, the Big Data itself has no value. The value is in the insights you derive from it. In the next article of this series, we’ll discuss data science, what it is, what it isn’t and how you can (responsibly and realistically) get some of it!
Kelly McGuire is the vice president of advanced analytics for Wyndham Destination Network. NATALIE OSBORN is a principal marketing consultant, hospitality and gaming, with SAS Institute, Inc.