revenue_management_data_science

Hotel Revenue Management: Strategies for the Future

Top industry experts weigh up the role of data science in hotel revenue management, 2020.

Last December, over a 100 industry experts and scholars attended the 3rd Revenue Management & Pricing in Services Conference (2019 RevME Europe), hosted by the Ecole hôtelière de Lausanne in collaboration with The University of Applied Sciences and Arts of Western Switzerland (HES-SO), STR, Hotel Performance and Room Price Genie. The aims of the conference were to create a unique platform for addressing issues related to Revenue Management and Pricing in the services, the role of Artificial Intelligence and Data Analytics, and lastly new approaches in revenue management education and training. What follows is a summary of the key takeaways proposed by the experts in the field.

The importance of data science in Revenue Management

With experienced speakers such as Mr. Nicola Simionato from Google.com/travel, Mr. Jan Krasnodebski from Expedia and Mr. Paul van Meerendonk from IDeaS, everybody agreed on the important potential associated with using big data and artificial intelligence in revenue management, and emphasized the need to adapt the revenue management discipline to new technologies that already exist in order to become competitive on the market and maximize returns. The role of AI, machine learning and data science cannot be underestimated if the savvy traveler is to make speedy decisions and if the smart hotelier wants to forecast market occupancy, send price optimization alerts and gain insights into clientele trends. Admittedly, certain human roles are affected: with tools such as Rev+, the post of a Revenue Manager is now changing into more of a Revenue Strategist, since machines cannot be outperformed but someone is still needed to look at the bigger picture and identify goals. The rise of AI cannot replace the need for human intelligence.

Examples of how Data Science can impact Revenue Management


  • Mr. Kevin Hof, Data Scientist at RoomPriceGenie highlighted the big potential for revenue management practices in the Swiss hospitality industry, especially for small, independent hotels. He shared a case study where nine hotels experienced a 22% increase, on average, in revenue and a 4% jump, on average, in terms of ADR after adopting a pricing optimization tool.
  • Mr. Emanuele Mansueti, Consultant at HotelPerformance, demonstrated how tools such as Smart Pricer and Dynamitick, just two of the many pricing platforms that enable businesses in a wide range of sectors (sports, theatre, cinema and concerts), can help increase revenue by adapting prices to fluctuating demand. He also discussed the emergence of dynamic pricing on secondary markets and its implications.
  • Mr. Daniel Krisch, Senior Director at Oracle Hospitality, focused on how artificial intelligence can help to provide a better hotel guest experience. AI applied to hotel property management system (PMS) can enhance auto-room assignment, which helps to minimize operational costs while meeting guests’ expectations. He also explained how the system can identify a guest’s persona based on profile and transaction data mining, and predict a guest’s interests.
  • Dr. Luciano Viverit, CEO of Hotelnet, showed how cloud machine learning tools such as Microsoft Azure or IBM Watson can be utilized for predictive analytics for hotels. While business intelligence is a ‘descriptive’ diagnostic, advanced analytics using machine learning tools are predictive and prescriptive so that decisions can be automated.

The future of Revenue Management Education and Training

Regarding issue of how to improve revenue management education and training, panelists agreed that there is a growing demand for well-qualified revenue managers but that the skill sets of the job are changing, hence RM education has to evolve accordingly. While good analytical skills are important, good communication skills (for sharing valuable information based on data analysis among colleagues in the organization) are even more critical. To this effect, data visualization tools can be used productively in revenue management education.

 

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Dr Cindy Heo
About the author

Dr Cindy Heo is an Associate Professor of revenue management at Ecole hôtelière de Lausanne (EHL). Prior to joining EHL, She taught revenue management course at the Hong Kong Polytechnic University and has delivered custom executive education programs on revenue management in Asia, Middle East, and Europe.

Dr. Heo is a recipient of numerous research awards including EHL Researcher of the Year Award, Best Paper Award from APAC CHRIE conference and ICOT Young Scientist Award. Her scholarly research and industry consulting focus on the core strategic elements of revenue management, pricing and sharing economy. Prior to joining academia, she had extensive industry experience in the hospitality and tourism fields.

Dr-Isabella-Blengini_EHL
About the author

Dr Isabella Blengini, is an Assistant Professor in Economics at Ecole hôtelière de Lausanne (EHL). Her research interests include exchange rate movements, expectations, international capital flows, financial crises optimal monetary policy and portfolio choices. Isabella teaches in the bachelor program the courses of microeconomics and hospitality economics.

After taking her Ph.D. at Boston College, she did a post-doc at the University of Lausanne. She has been visiting fellow in the economics department at MIT and summer intern at the Boston Fed.

Dr. Meng-Mei Maggie Chen
About the author

Meng-Mei Maggie Chen (Ph.D., University of Surrey) is an Assistant Professor of Marketing at Ecole hotelière de Lausanne (EHL), Switzerland. She has actively engaged in various tourism sectors, ranging from hotels, casinos, travel agencies, and consulting. She has worked in Taiwan, the U.S., Puerto Rico, and Switzerland. She leverages her cross cultural sense and sensitivity in her work and research.

Her research includes hotel channel management, distribution channel marketing, customer decision making process, and consumer behavior. Recently, she completed a Swiss governmental agency research project which focuses on optimizing channel management for SME hotels in Switzerland.