Business Forecasting Research Paper Starter

Business Forecasting

(Research Starters)

This article explores how businesses rely on sales forecasting to grow the business as well as develop strategic plans as to what direction the organization should move. Even though there are many benefits when forecasting, many believe there are factors that make the markets difficult to forecast. For example, forecasting is difficult in real markets because of the nature of these markets; the dominant characteristic of real world markets is probably never the same twice. There are three broad schools of thought that have an influence on how forecasting is practiced. These three schools of thought are economic, statistical or operations research and judgmental.

In order for a business to be successful, it must have the ability to make timely and accurate forecasts. One could assert that all businesses forecast in some way. "Virtually every manufacturing or service company needs to generate forecasts of their short to medium term sales" (Boulton, 2003, p. 1). However, "while most business people recognize the need for effective forecasts, there is a tendency to view forecasting as either a black art or an impossible task" (Crosby, 1997, p. 3).

This article explores how businesses rely on sales forecasting to grow the business as well as develop strategic plans as to what direction the organization should move. "The objective of forecasting sales is to assist businesses (and other organizations) in planning their purchasing, personnel, production or service functions, and finances" (Sartorius & Mohn, 1976, p. 2). Boulton (2003) believed that organizations would have commercial advantages if they could forecast demand more accurately, and the forecasts could be used to:

  • Plan purchasing, production and inventory.
  • Serve as the basis for marketing or sales planning.
  • Assist in financial planning and reporting or budgeting.

According to Crosby (1997), there are tangible and intangible benefits when a successful forecasting system is in place. Some of these benefits include:

Tangible Benefits

  • Increased profits from operations
  • Decrease in nonproductive cash consumption
  • Increased factory utilization
  • Decrease in excess and obsolete inventories
  • Increased inventory turns
  • Decrease in negative manufacturing variances
  • Increased performance to "customer request date" (CRD)
  • Decrease in number of stock-out situations
  • Decrease in cost of purchased items
  • Decreased time-to-market for new products

Intangible Benefits

  • Improved customer relations
  • Reduced level of frustration (internally and externally)
  • Reduced meeting time
  • Critical resources freed up from expediting tasks
  • More frequent and more accurate views of the marketplace
  • Increased organizational flexibility (p. 4).

Even though there are many benefits when forecasting, many believe there are factors that make the markets difficult to forecast. For example, forecasting is difficult in real markets because of the nature of these markets; the superior trait of real world markets is most likely never the same more than once. Most of the markets tend to share most of the characteristics listed below:

  • Frequent promotional activity
  • Fluctuating positioning at point of sale between value (i.e. low prices) and added value (i.e. quality)
  • High level and variety of competitor activity
  • Promotions are seldom at the same time each year
  • The size of the distribution "pipeline" tends to vary
  • Growing concentration in sales to biggest customers (Boulton, 2003, p. 2).

Application

Forecasting System Schools of Thought

There are three broad schools of thought that have an influence on how forecasting is practiced. These three schools of thought are economic, statistical or operations research, and judgmental.

  • The economic school was a creation of the economics departments of the academic world and focuses on the use of causal or explanatory models that are developed from simple and complex regression analyses of key economic variables.
  • The statistical and operations research school tends to go from the specific to the general by taking individual parts of the equation and summing them in order to produce an organizational or industry forecast.
  • The judgmental school relies on practices such as the sales force estimates, the jury of executive opinion, and a group of forecasting approaches called the Delphi Technique.

Techniques for Forecasting

Chambers, Mullick, and Smith (1971) wrote an article that described 18 sales forecasting techniques that can be broken down into three categories.

CATEGORY Technique Description Typical Application Qualitative Methods Delphi Methods This technique eliminates the bandwagon effect of majority opinion. Forecasts of longrange and new product sales, forecasts of margins. Market Research The systematic, formal, and conscious procedure for evolving and testing hypotheses about real markets. Forecasts of longrange and new product sales, forecasts of margins. Panel Consensus Based on the assumption that several experts can arrive at a better forecast than one person. Forecasts of longrange and new product sales, forecasts of margins. Visionary Forecast A prophecy that uses personal insights, judgment and facts about different scenarios of the future. Forecasts of longrange and new product sales, forecasts of margins. Historical Analogy A comparative analysis of the introduction and growth of similar new products that bases the forecast on similarity patterns. Forecasts of longrange and new product sales, forecasts of margins. Time Series Analysis and Projection Moving Average Each point of a moving average of a time series is the arithmetic or weighted average of a number of consecutive points of the series, where the number of data points is chosen so that the effects of seasonals or irregularity or both are eliminated. Inventory control for low volume items.

CATEGORY Technique Description Typical Application Exponential Smoothing This technique is similar to the moving average, except that more recent data points are given more weight. Production and inventory control, forecasts of margins and other financial data. Box-Jenkins The time series is fitted with a mathematical model that is optimal in the sense that it assigns smaller errors to history than any other model. Production and inventory control for large-volume items, forecasts of cash balances. X-11 This technique decomposes a time series into seasonal, trend cycles, and irregular elements. Tracking and warning, forecasts of company, division, or department sales. Trend Projections This technique fits a trend line to a mathematical equation and then projects it into the future by means of this equation. New product...

(The entire section is 3121 words.)