5 essential components of Hotel RMS

1. ACCURACY & HIGHER MARGINS

Rather than relying on human error-prone manual methods, a scientific approach uses statistical algorithms to effortlessly perform the computations necessary to develop optimal pricing and revenue management decisions. An advanced RMS incorporates wide-ranging factors, swiftly processing data to improve decision-making and produce more profitable results

2. SUPPLY AND DEMAND

A key function of a science-based RMS is its ability to forecast unconstrained transient demand rooms that could be sold with unlimited inventory available at a highly granular level, i.e. customer segment, arrival date, room category and length of stay. This is crucial for true profit optimization. As an example, a 200-room hotel with demand for 300 rooms would require a very different pricing strategy than if there was a demand for only 100 rooms on a given stay night

3. Precise Forecasting

When it comes to optimizing pricing decisions, research findings from the Q2 2019 survey on Hospitality Revenue Management revealed that 93% of hoteliers consider an accurate forecasting model to be critical. For maximum total profit, in addition to forecasting transient demand, you must forecast unconstrained group demand by day, by segment as well, along with group materialization- considering cancellations, no shows, and group wash.

4. Tailored to your Hotel’s DNA

A Scientific model offers a highly configurable solution that meets the unique needs of your hotel. It draws from multiple historic and real-time, internal and external data points including seasonality, special events and the unique relationship between guest segments and their booking patterns. A scientific model also forecasts special events independently from all other demand and because end users have differing needs, advanced solutions offer the ability to customize reporting and dashboard views based on your hotel’s priorities.

5. Built for the future

A scientific approach utilizes robust analytics, machine learning and dynamic decision models that swiftly adapt to the ever-changing realties of your market and Business. Furthermore, a robust system can predict a customer’s purchase behaviour in advance, allowing hotels to ensure that at any given time there are rooms available for their most profitable guests.

Photo by Robynne Hu on Unsplash

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