What are the best forecasting strategies to stay ahead in hospitality?

1 Historical data

One of the most common and simple forecasting methods is to use historical data as a baseline. This means analyzing your past performance, such as occupancy, average daily rate, and revenue per available room, and applying a growth rate or a percentage change to project your future results. For example, if you know that your occupancy was 80% in January last year, and you expect a 5% increase this year, you can forecast your occupancy for January this year as 84%. However, this method has some limitations, as it does not account for external factors, such as demand fluctuations, new competitors, or unexpected events, that may affect your business. Therefore, you should always compare your historical data with current market conditions and adjust your forecasts accordingly.

2 Moving average

Another forecasting method that uses historical data is the moving average. This means calculating the average of a certain number of past periods and using it as a forecast for the next period. For example, if you use a 3-month moving average, you can take the average of the last 3 months and use it as a forecast for the next month. The advantage of this method is that it smooths out the seasonal variations and random fluctuations in your data, and gives you a more stable and consistent forecast. However, the disadvantage is that it does not capture the trends or patterns in your data, and it may lag behind the actual changes in your market.

3 Regression analysis

A more advanced and sophisticated forecasting method is regression analysis. This means using statistical techniques to identify the relationship between your dependent variable, such as revenue, and one or more independent variables, such as demand, price, or seasonality. For example, you can use regression analysis to estimate how much your revenue will increase or decrease based on the changes in your price or demand. The advantage of this method is that it allows you to quantify the impact of different factors on your performance, and it can account for multiple variables at once. However, the disadvantage is that it requires more data and expertise to conduct, and it may not capture the non-linear or complex relationships in your market.

4 Scenario planning

A more flexible and creative forecasting method is scenario planning. This means creating different scenarios or stories based on possible future events or outcomes, and estimating their implications for your business. For example, you can create a best-case scenario, a worst-case scenario, and a most-likely scenario, and forecast your revenue, costs, and profitability for each scenario. The advantage of this method is that it helps you prepare for different situations and uncertainties, and it can stimulate your strategic thinking and innovation. However, the disadvantage is that it can be subjective and biased, and it may not reflect the actual probabilities or likelihoods of the scenarios.

5 Machine learning

A more modern and innovative forecasting method is machine learning. This means using artificial intelligence and algorithms to learn from your data and generate forecasts based on patterns, trends, and correlations. For example, you can use machine learning to analyze your customer data, such as booking behavior, preferences, and feedback, and forecast their future demand, satisfaction, and loyalty. The advantage of this method is that it can handle large and complex data sets, and it can improve its accuracy and reliability over time. However, the disadvantage is that it can be costly and complex to implement, and it may not explain the logic or reasoning behind its forecasts.