Forecasting is a method of analyzing current and historical data to make a determination on future trends. Organizations will have determined with methods serve them best and which will provide the information that is crucial to their organizational structure. Several methods are available for organizational use. Some of them include the Delphi method, seasonal methods, time-series forecasting and many others that require various degrees of data gathering and validation.
The Illinois Institute of Technology has done much research in regards to the Delphi method, and the wide scope of its uses. “The objective of most Delphi applications is the reliable and creative exploration of ideas or the production of suitable information for decision making. The Delphi Method is based on a structured process for collecting and distilling knowledge from a group of experts by means of a series of questionnaires interspersed with controlled opinion feedback. Delphi represents a useful communication device among a group of experts and thus facilitates the formation of a group judgment. Lacking full scientific knowledge, decision-makers have to rely on their own intuition or on expert opinion. The Delphi method has been widely used to generate forecasts in technology, education, and other fields.” (www.iit.edu, 2005)
Delphi is an involved process and only after answering a few questions can the organization evaluate if the Delphi method would be successful for their company. IIT asks the questions and warns that only when these are answered would it be appropriate to use this particular method, those questions include “What kind of group communications process is desirable in order to explore the problem at hand? Who are the people with expertise on the problem and where are they located? and What are the alternative techniques available and what results can reasonably be expected from their application?”
Critics have questioned the usefulness of the Delphi method, including that it is not scientific enough and programs that have failed with Delphi have failed miserably. IIT explains that Delphi is a good method when seeking an answer for one single-dimension question.
Seasonal forecasting methods are very useful for specific types of organizations, specifically those who operate on a seasonal basis. Some organizations that take seasons greatly into consideration are retail companies and schools. In regards to the retail organizations, the change in seasons and the holidays that pass through each season contribute to the revenues that are generated by the company.
Christmas is an incredibly profitable time for retail companies, and changes in temperature can be a factor into how many shoppers are coming into the stores. Increased heat or increased cold can push consumers into stores to escape the weather. Companies will devise their plans based on the factors like this that will bring customers in to the store.
In the realm of schools that educate beyond high school, the seasons contribute greatly to the enrollment they will have. Late summer and early autumn are the traditional times when students go back to school. At the University of Phoenix a focus on this time of year and also the beginning of the year when the holidays have passed and people make those resolutions is also a prosperous time for enrollment in classes.
This seasonal information is taken into consideration in efforts to put resources where they can be most useful. They can push or lay back from their efforts in marketing and the processes.
Time-series forecasting, according to Decisioneering.com, is “a forecasting method that uses a set of historical values to predict an outcome. These historic values, often referred to as a “time series”, are spaced equally over time and can represent anything from monthly sales data to daily electricity consumption to hourly call volumes. Time-series forecasting assumes that a time series is a combination of a pattern and some random error. The goal is to separate the pattern from the error by understanding the pattern’s trend, its long-term increase or decrease, and its seasonality, the change caused by seasonal factors such as fluctuations in use and demand.” (decisioneering.com, 2005)
The University of Baltimore has also done research into forecasting methods and they warn that, “The selection and implementation of the proper forecast methodology has always been an important planning and control issue for most firms and agencies. Often, the financial well-being of the entire operation rely on the accuracy of the forecast since such information will likely be used to make interrelated budgetary and operative decisions in areas of personnel management, purchasing, marketing and advertising, capital financing, etc. For example, any significant over-or-under sales forecast error may cause the firm to be overly burdened with excess inventory carrying costs or else create lost sales revenue through unanticipated item shortages. When demand is fairly stable, e.g., unchanging or else growing or declining at a known constant rate, making an accurate forecast is less difficult. If, on the other hand, the firm has historically experienced an up-and-down sales pattern, then the complexity of the forecasting task is compounded.” (www.ubalt.edu, 2005)
“There are two main approaches to forecasting. Either the estimate of future value is based on an analysis of factors which are believed to influence future values, i.e., the explanatory method, or else the prediction is based on an inferred study of past general data behavior over time, i.e., the extrapolation method. For example, the belief that the sale of doll clothing will increase from current levels because of a recent advertising blitz rather than proximity to Christmas illustrates the difference between the two philosophies. It is possible that both approaches will lead to the creation of accurate and useful forecasts, but it must be remembered that, even for a modest degree of desired accuracy, the former method is often more difficult to implement and validate than the latter approach.” (www.ubalt.edu, 2005)
For the University of Phoenix, and countless other private universities, the seasonal method provides the easiest way to look at how the business cycles. The traditional school schedule reflects into how potential consumers view going back to school. Traditionally, classes start in late summer, again in the New Year and to a lesser degree in the beginning of summer. The other months of the year provide far less certainty into how the company will perform.
The forecasts in demand will shift from month to month and the focus of the employees will shift to compensate for the increased demand or the decrease in demand. Most private universities do not operate on the same traditional schedule as state universities and have students starting periodically throughout the whole year. With the start dates that fall during off times the schools can give the students more attention and promote those students to stick with their academic program. When enrollment is smaller, the focus turns to holding on to the students that are already enrolled.