Business Forecast

Abstract

This Paper examines and compares various forecasting techniques used for qualitative and quantitative business forecasting and their use in Firstlogic Inc., to forecast the demand under conditions of uncertainty. Time series and Delphi forecasting methods are considered for this research to evaluate their ability to make effective decisions regarding the future.

Business Forecasting

Business forecasting is the process of studying historical performance for the purpose of using the knowledge gained to project future business conditions so that decisions can be made today that will aid in the achievement of established goals. Forecasting plays a crucial role in today's uncertain global marketplace. Forecasting is traditionally either qualitative or quantitative, with each offering specific advantages and disadvantages.

Qualitative and Quantitative Forecasting Techniques

Forecasting can be classified into qualitative and quantitative. Qualitative techniques are subjective or judgmental and are based on estimates and opinions. The Delphi technique, a common form of qualitative forecasting, allows experts to create an effective forecast under conditions of extreme uncertainty. Time's series forecasting, a quantitative technique, uses a statistical analysis of past sales in order to effectively predict future outcomes, but can be limited under conditions of uncertainty (Chase, 2003, p.364).

Business forecasting can be used in a wide variety of contexts, and by a wide variety of businesses. For example, effective forecasting can determine sales based on attendance at a trade show, or the customer demand for products and services (Business and Economic Forecasting, p.1). One of the most important assumptions of business forecasters is that the past acts as an important guide for the future. It is important to note that forecasters must consider a number of new information, including rapidly changing economic conditions and globalization, when creating business forecasts based on past sales.

Globalization and economic slowdown has made businesses subject to a great deal of uncertainty. In this time of rapid change, economies worldwide change rapidly, new markets open up and old ones change, and demand for products is often uncertain. As such, businesses must be flexible and adaptable in the types of methods that they use to forecast future sales (chase, 2003, p.472).

In ever-changing global marketplace, organizations are constantly coming up against unusual and novel situations. It is in these situations that modern methods of business forecasting can be especially useful. Modern forecasting methods are usually grouped into two main categories: qualitative methods, and quantitative methods. Qualitative analysis includes the intuitive and knowledge-based approach as discussed earlier. The decision maker reviews all of the information available, and then makes an estimated forecast. Quantitative techniques are used mostly when qualitative information is not available. In contrast, qualitative techniques are based on an analysis of data (Namvar, 2000, p.8).

Delphi Forecasting Method

Qualitative forecasting techniques are: executive committee, the Delphi method, and surveys of the sales force, surveys of customers, historical analogy, and market research. 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 (chase, 2003, P471).

The Delphi method is a variation of the executive committee approach. But the interaction is indirect, iterative and structured. The basic premise of Delphi method is to identify a group of experts and each of them are given a set of questions or issues, and asked to respond. After a given amount of time, the responses are sent to a coordinator or monitoring group that does not participate in the earlier stages of the Delphi processes. This group then feeds back the responses to other members of the group, while never giving away the identity of the response. The experts are then asked to respond again, after reviewing the responses of other respondents. This process may continue until a consensus is reached among the group. The group may be united to form a final consensus (Namvar, 2000, p.8).

Time Series Forecasting Method

Time series techniques are the most popular quantitative method. These techniques use statistical methods for projecting from historical data. Quantitative techniques are preferred when appropriate data are available. The main assumption is that the historical pattern will continue into the future. The two main types of time series forecasting are average smoothing and exponential smoothing. The moving average is simply a series of arithmetic averages. Predicting sales for next year is simple. The actual sales for a certain number of years is added, and then divided by the number of years used to get the moving average. A weighted moving average is obtained by assigning a specific weight to previous years. The sum of all weights must equal one. Recent years are given a higher weight (Namvar, 2000, p.13).

Exponential smoothing is simply a subtype of the weighted moving average. A new forecast is a weighted sum of actual variables (usually sales) in the current year and the weighted forecast of the variable for that period. It has the advantage of being relatively easy to compute. In contrast the moving average method is quick, cheap, and easy to use, but does not easily take into account variations based on seasonal effects and cycles (Namvar, 2000, p.14).

Both the Delphi technique and Time series forecasting are valuable forecasting tools in the right circumstance. The Delphi technique is useful for short-term forecasts.