Forecasting Models


Forecasting is a valuable way to help a company prepare and plan for the upcoming years. Forecasting however is not a fortune teller, it is designed as an educated guess of how much will be needed and utilized. It is a tool used to help budget and allocate money as accurately as possible.

Types of Forecasting Methods

Since there is not one right way of forecasting, there are many different types of forecasting. Each one is designed to help different organization and it is up to the company to choose the model which is best for them.


Some of the different types of forecasting methods include, Qualitative, “Subjective judgment based on estimates and opinions” (Chase, Jacobs, Aquilano, 2005, p. 514). These methods include talking with the people who are directly involved with sales to find out how a particular item or set of items are moving. A good example of Qualitative forecasting is Delphi. The Delphi model is similar to the panel consensus method. Both forecasting types require that a group of individuals are required to answer a questionnaire and/or share their ideas and opinions on a variety of topics. The argument against panel consensus is that everyone participating is aware of everyone else participating and knows how everyone else answers. This means that if the president of the company is in the group an entry-level person will know and that can cause the entry-level person to become shy and not fully express his or her opinions for fear of losing their job or being seen as not a team player. Delphi seeks to correct this apprehension. Delphi also utilizes a group of team members from the highest level to the lowest level. The difference is that the team members are handed questionnaires and asked to fill them out. They are then turned in and the mediator reads the answers. No one in the panel knows who voiced a certain opinion. This helps to get a more well rounded viewpoint without scaring those members who might worry about how their opinions will be perceived.

Time Series

Another method used in forecasting is called the Time series analysis. This method is “based on the idea that the history of occurrences over time can be used to predict the future” (Chase, et al., 2005, p. 514). Among the time series analysis, models included are Simple moving averages, which deals with averaging a number of points. This method utilizes the view that all points carry equal weight. The more numbers that are included usually smoothes out the randomness in figures. However, if there is a trend this model can have a negative affect and show a lagging. What this means is that the shorter trend will more closely follow trends but the longer trends will look smoother.


Causal forecasting methods include regression analysis, econometric models, input/output models and leading indicators. What causal implies is that this model “tries to understand the system underlying and surrounding the item being forecast. For example, sales may be affected by advertising, quality and competitors’ (Chase, et al., 2005, p. 514). This model tends to be fairly limited in scope since there has to be an independent variable which is used as the leading indicator. That means that one variable directly affects the sales and/outcome of a second variable. Another example of this might be that snow fall causes the sale of mittens.


Simulations models use computers to generate the upcoming forecasts. This type of model is handy since it allows the user to change figures and calculate what might happen if prices should increase or decrease.

The Hotel Industry

The hotel industry tends to be more fluid than other organizations and companies. It has many of the same variables, for instance sales will increase or decrease depending on how many guest are in-house, are staying at the hotel. For this fluid movement of people it can be difficult for management to plan an accurate forecast in advance. They must rely on past data as well as the data which they have on hand, including business conventions and vacation packages which have been booked in advance.

Zero-Based Budgeting

The Hilton El Conquistador uses a form of forecasting called Zero-based budget. This type of forecasting is good because it “requires that you start from scratch each year and take a fresh look at every expenditure without any preconceived notions” (McCarthy, Aug1998, p. 16). This take on forecasting works well since the new groups in-house may have nothing to do with the groups that were there last year at the same time. The budget and forecast is based on drivers, such as the number of covers (guests), the number of rooms booked, the number of group rooms versus the number of transient rooms. The trends are established by the total of rooms/guests which have been ‘captured’. In order to establish what each outlet should budget for the upcoming year, management sits down and looks over the number from last year to see what they did in the previous year and if they have a repeat group what that group did. Then the total number of guests for the month are then further divided by how many of those guests are with a group or on their own, how much their room night costs, whether the groups are using the banquet facilities to cater their meals or if they are on their own. The cost of the banquet rooms for general use. Once the total of guests using banquets has been determined the breakfast, lunch and dinner outlets can plan accordingly. They take the remainder of guests and calculate the total amount needed for their budget, depending on the cost of feeding x number of people and having the correct staff. (McGowan, personal communication, Jan. 27, 2006). Since their forecast depends on the guests in-house and there is no way to accurately forecast whether they will want a banquet meal or a restaurant meal the forecasts are continually changing. Zero-Based budgeting is “comprehensive and realistic. It…forms the basis for a well structured budget submission with far greater chance of being approved… [it can] provide you with a bigger budget and the tools to do the job properly” (Corbett, June2005, p. 9).

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