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Sina Niedermaier
Aug 1, 2022

Forecasting in volatile times

What forecasting means

Forecasting is the use of statistical methods to calculate certain predictions or forecasts. These forecasts help to better assess the course of business and support personnel and cost planning, thus leading to optimised profits.

Factors to be considered

But what factors should be taken into account when historical data can no longer be used as a basis to the same extent as before? New competitors, seasonal trends, events, trade fairs, holidays, exchange rates, inflation and even weather can have a major impact on business development in the hotel industry. Flexibility in forecasting is more important now than it has been for a long time, perhaps ever.

In times like these, the following measures are recommended:

  • Regularly (depending on the market, but about once a week) check future bookings. Are the bookings above or below the trend (and this is the trend of the last weeks, NOT above the trend of the previous year). Is there an identifiable reason for one or the other trend?
  • Detailed competitor observation: Are there new hotels in the market, do hotels have to close or are they being renovated? Which room categories do they offer and is there a change in the offer? What discounts and promotions do the competitors advertise?
  • Closely monitor the weather - a rainy weekend needs different pricing treatment than a sunny weekend and can thus have an impact on occupancy.
  • Regular control of the forecasts with adjustment of the strategy. This is more important than ever in the volatile environment in which the hotel industry is currently operating.
  • Quarantine regulations, travel restrictions and new visa regulations caused by the Covid19 pandemic: what are they, how do they change and do they influence the length of stay or the advance booking window?
  • Analyse cancellations constantly and adapt cancellation conditions flexibly and quickly if necessary.
  • Are the main markets constant? Or do tourists from certain countries stay away and what influence does this have on the average rate and even on ancillary sales?
  • Business travel: how is the booking behaviour of companies changing? What influence does this have on the booking curve and sales? Here, revenue management and the sales department have to work hand in hand to quickly identify changes and derive the right actions from them.
  • Do guests want to stay longer, book larger rooms and spend more because they have not been able to travel for a long time? Or are guests cautious because of inflation and don't want to spend a lot of money?
  • Website traffic: has it changed? Did the hotel get more visits or less? Does one nationality stand out in particular? And what could be deduced from this?
  • Quality of reviews: Positive reviews help to push through a higher price. What can be done here to keep the reviews at a high level? If the hotel has consistently bad reviews, it will be difficult to charge higher prices than the competitors.
  • Which countries are the most important for the hotel. Is there a change in the travel behaviour of tourists? Is the exchange rate expensive or favourable? Are these tourists cautious due to inflation and stay in their own country or do they want to reward themselves for the times of doing without in the pandemic and travel abroad?

Now more than ever, revenue management needs to efficiently use myriad data from a wide variety of sources and translate it into a forecast and the right pricing strategy.

Digitalisation as an opportunity

Fortunately, digitalisation enables hoteliers to opt for a revenue management system (RMS), which helps to create forecasts in a supportive or completely autonomous way. Many of the RMS available on the market use historical data for forecasts. In view of the rapidly changing times, as mentioned at the beginning of the article, the question arises whether this is still up to date. To process large amounts of data easily must be the demand on the RMS. The more current trends and changing markets can be included in the forecasts the better. Algorithms and artificial intelligence should support the revenue manager in making the best possible predictions about the business development in order to optimise the hotel result in the long term.

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