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Role of Machine Learning in Transforming the Hospitality Business

04 June 2018

The hospitality industry has always been primarily dependent on its personnel and relies largely on human interaction. Starting from reservations to client handling and of course other administrative tasks, the hospitality industry has always preferred humans over machines. However, this often becomes a difficult task to undertake when the business is very large. Among other tasks, revenue management becomes especially difficult. This is the part where the revenue managers have to decide which rate is to be quoted for which season, so as to maximize the revenue.

But things have become rosier with the advent of cluster and cloud computing. With scale-out methodology, hotels can now easily access programs like the Revenue Management System or RMS using Machine Learning and AI. By using this technology, the big data involved in the process can be converted easily into a sizeable content with simpler format for further processing. To be precise, revenue managers no longer have to manually implement revenue management tasks.

Machine Learning in Hospitality – The History

It has been almost thirty long years that Machine Learning has made its way into the hospitality industry through its Revenue Management System. This system could automatically set their rates and make inventory decisions within the various systems of bookings that the industry had. Needless to say that there were trepidations in the minds of the administrative authority to let machines take over the jobs of human beings, that too in an industry where personal touches played such an important role. However, the efficiency with which the systems worked and the benefits they provided in terms of consistency and reliability, soon changed the scenario. Using Machine Learn for optimization, decision making as well as analysis of big data gave the industry a new boost.

As a result, the hoteliers found more time to devote in improving services, guest experiences and of course, their marketing campaigns for a better footfall in their hotels.

How Machine Learning Functions in this Industry

The technology of Machine Learningmakes use of algorithms to learn and extract insights from the data already available. As far as the hospitality industry is concerned, it has invaded primarily the revenue management domain, working in unison with statistical methods for better decision making and more effective optimization of decisions. The Machine Learningsystems has found all the more use and importance in the age of big data where the Revenue Managers often stumble over the sheer volume and complexity of the data they have to handle.

This new technology has become capable of making progressive predictions and analyses embedded in the cutting-edge RMSs. As a result, the hoteliers have found new ways to get hints of the perpetually emerging market trends and find more opportunities to increase revenue, at the same time keeping the market fluctuations under control. Machine Learningis thus, that one technology that has helped the hospitality industry makes use of the big datathey already kept in store and use it for their own benefit. Hotels using high-performance technology can implement machine learning process to understand the relationship between price and demand.

Conclusion

To sum it up, although hoteliers were initially apprehensive of allowing Machine Learn into the functioning of their industry, they have finally recognized its vast range of benefits. This technology is just another proof of the power of analytics, coupled with the precision of big data. All brought together they have helped the industry get rid of the tedious manual or spreadsheet based environments and venture into the more efficient world ofanalytics.

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Lakhwinder Singh Lead Developer - Mobility

Lead Mobile App Developer, covers wide range of technologies applied to the development of websites and business applications too. Enjoys doing creative things in Mobile and is passionate about developing unique Mobile Products.

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