Any hotelier operating today without the support of an automated revenue management system is working at a competitive disadvantage. Advanced revenue management solutions allow hotels to better predict demand, price their product offerings competitively and achieve the optimal business mix for their property as a result. Simply put, revenue management systems allow a hotel to attract the ideal guest, at the ideal price and via the ideal channel.
In addition to driving revenue and profit growth within a hotel, when applied to its fullest potential, revenue management technology can positively impact efficiency and improve operational performance across an entire organisation. Sophisticated forecasting tools provide powerful insights into business demand, which can assist with wider hotel operational planning and efficiencies.
Have the right number of staff work the right shift
Managing staffing levels is a constant juggle for hotel managers. On the one hand, no one wants to be caught short-staffed and face disgruntled guests who are dissatisfied due to long wait times. Conversely, it is a waste of money for staff to be sitting around underutilised as a result of not having enough work to do. Hoteliers need to balance maximising the guest’s experience whilst keeping labour costs at efficient and profit-oriented levels.
Accurate demand forecasting should be at the foundation of optimal labour scheduling. Through integrating forecasts across a hotel’s operations, hoteliers can use the forecast data provided to inform their staffing decisions and account for periods of higher or lower demand.
Once this data is made available, staffing managers can determine which areas are most affected by the number of guests staying in the hotel. For example, looking at how the number of occupants will affect the housekeeping needs, the number of staff needed at the front desk to check guests in and out, the number of servers who will be required in restaurants and valets to park cars etc.
It is not just the hotel level demand that should be reviewed, but also the granular segmentation that the demand is forecast to be coming from. For example, higher paying guests may be more likely to stay in a suite, which will take longer to clean than a standard room. The suite or club room guests’ in-house spend is different to that of a standard room guest and flows into a hotel’s forecasted fine dining residential uptake, spa, room service etc.
