Hotel Revenue Analytics: Data Science and Your Day Job
By Paul van Meerendonk Director of Advisory Services, IDeaS Revenue Solutions | July 14, 2019
The 2020s are fast approaching. If there's one thing we can count on in the coming decade, it's that the rate of technological change and disruption will only continue to increase. For the hotel industry, and the field of revenue management in particular, the growing importance of analytics has already taken over our "day jobs," which raises the question: what will it take to be a high-performing hotel revenue manager in the new age of technology-driven data science?
In answering this question, it helps to look back at other times technology has completely upended our lives and how we have since adapted. Consider the invention of the automobile. Before cars, people typically relied on horses to go from point A to point B. It was commonplace to own horses, and horse owners had to know a thing or two about how to take care of their animals. But what did they know about gas-powered engines? Probably not much.
Even today, over a century later, the average car driver tends to know very little about what's really going on under the hood. But does that make them a bad driver? As technology and systems become more sophisticated, the user experience and process should remain simple. After all, technology is meant to enhance our lives, not make things more difficult.
In fact, the rise of automatic transmissions and cruise-control systems in cars have only made us better, more efficient drivers by allowing us to stay focused on our performance and keep our eyes on the road. With a basic comprehension of how our vehicles operate, we can be safe drivers, and let the manufacturers and mechanics take care of the rest.
The same is true for the field of revenue management. With a core understanding around the fundamentals of advanced data analytics, we can be effective and strategic revenue managers while counting on automated revenue technology to do the deep diving as we drive toward more profitable outcomes.
What Revenue Managers Should Know About Analytics
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