Science-infused Infor EzRMS provides new forecasting capabilities and real-time optimization for hoteliers large and small
NEW YORK – October 12, 2020 – Infor today announced significant updates to Infor EzRMS, a leading revenue management application built specifically for the hospitality industry. Part of the Infor Hospitality suite of cloud-based solutions, Infor EzRMS is designed to help hoteliers better optimize revenue by automatically calculating demand forecasts and recommending appropriate selling strategies based on data such as day-of-week patterns, booking lead-time and the number of guests per room. Through a combination of state-of-the-art technology, sophisticated deep learning algorithms, and innovative business process design, Infor provides the opportunity for its customers to experience increased turnover, higher profit margins, and rapid return on investment.
Learn more about Infor EzRMS.
“Forecasting is an art, and right now it has been more challenging to predict how the business will evolve. Since Asia has been one of the first few regions to experience a recovery and uptick in travel, we decided to pilot the new algorithm from the beginning,” said Andrew Hodges, Accor director of revenue management and systems for Asia-Pacific. “So far, we’ve seen great results. The system is more realistic and quickly adapts to changes in trends, which is key to helping our properties plan and strategize.”
The newest release of Infor EzRMS was designed based on feedback from Infor customers and in response to current trends in travel and leisure. A responsive new forecast algorithm helps hotels use their data to identify and optimize revenue opportunities. With recent business trends being so atypical, looking to the past isn’t as helpful as it once was. As such, Infor developed a next-gen forecasting algorithm designed to automatically detect and respond to new trends—fast. Unlike competing products that still require manual actions to do this, Infor’s unique and hands-free solution delivers demand forecasting in line with current market conditions. In addition, with market-influenced pricing, Infor EzRMS smartly incorporates competitor information, on top of hotel system data, to calculate the optimal price decisions. Using innovative techniques, the system automates the process a revenue manager would normally follow to set prices.
“The hospitality industry is in the middle of significant change. Historical data and trends that were once relied upon to predict the future are no longer helpful as we continue to experience daily and drastic fluctuations. Even though times have changed, many of our competitors are still providing the same solutions, but this isn’t the same industry,” said Jason Floyd, Infor Hospitality general manager. “Our customers need to be able to get more from the data they are collecting – and fast. We took it upon ourselves to overhaul our forecasting methodology to match the current needs of our customers right now.”
This release includes unique, smart, real-time optimization, ensuring a hotel pricing and selling strategy is always up to date, 24 hours a day, seven days a week. This allows hotel teams to focus on other key tasks, trusting that Infor EzRMS will automatically detect and control new revenue opportunities as they happen. It is important to note that these new features don’t operate rule-based, but instead are smart because they function like a revenue manager’s brain, and take action when it makes sense to do so, and with better, more precise real-time data.
“Infor is committed to providing our hospitality customers with sustainable operational advantages that improve the bottom line and maximize occupancy and revenue. Our leading revenue management solution is critical in an industry where pricing sets one hotel apart from another, and there are many options for consumers,” continued Floyd. “Modern technology can help improve the bottom line and maximize occupancy and revenue, and Infor is committed to delivering a scalable system that can quickly navigate through rapid changes in market conditions and demand trends.”
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