Business Forecasting

A Practical Approach

A. Reza Hoshmand

• Publisher: Routledge
• Year: 2009
• ISBN:
  9781135257125
• Edition: 1
• Topic: Business
• Subtopic: Business General
• Index: Business

The information age has brought greater interconnection across the world, and transformed the global marketplace. To remain competitive, business firms look for ways of improving their ability to gauge business and economic conditions around the world. At the same time, advances in technology have revolutionized the way we process information and prepare business and economic forecasts. Secondary data searches, data collection, data entry and analysis, graphical visualization, and reporting can all be accomplished with the help of computers that provide access to information not previously available. Forecasters should therefore learn the techniques and models involved, as applied in this new era.

Business Forecasting: A Practical Approach is intended as an applied text for students and practitioners of forecasting who have some background in economics and statistics. The presentation is conceptual in nature with emphasis on rationale, application, and interpretation of the most commonly used forecasting techniques. The goal of this book is to provide students and managers with an overview of a broad range of techniques and an understanding of the strengths and weaknesses of each approach. It is based on the assumption that forecasting skills are best developed and retained by starting with simple models, followed by repeated exposure to real world examples. The book makes extensive use of international examples to amplify concepts.

1
Forecasting for Management Decisions

An Introduction

Today’s businesses are constantly looking for strategies to improve their financial performance. Business forecasters have played a significant role in the performance of these entrepreneurial activities by providing senior management with as accurate forecasts as possible given the dynamic nature of markets. The aim of a business forecast is to combine statistical analyses and domain knowledge (not judgment) to develop acceptable forecasts that will ultimately drive downstream business planning activities. A good business analyst or forecaster needs to focus on defining and measuring the key business indicators that impact sales and revenue, and provide senior management with business decision choices that are informed by good statistical analysis.

Advances in technology have revolutionized the way we process information and prepare business and economic forecasts. These advances in the theory and practice of forecasting have been in response to the increasing complexity and competitiveness in global business. Complexity increases the risk associated with business decisions, making it important to have a sound information base. Companies of all sizes now use forecasting as a tool to make economic and business decisions. Although most managers are aware of the need for improved forecasting, few are familiar with the variety of techniques that have been developed in the last few decades. They rely on professional staff with such knowledge. With the help of personal computers, professionals are able to utilize sophisticated data analysis techniques for forecasting purposes.

Forecasting methodologies have been in existence since the nineteenth century. An example is the regression analysis. Recent developments such as the Box–Jenkins and neural networks have significantly expanded the field of forecasting. As more complex and sophisticated approaches are being developed, forecasting professionals have to become proficient in the use of these tools, just as their managers need to develop a basic familiarity with such forecasting possibilities. While there may be an appreciation for the theoretical frameworks, most are interested in the practical use of these methodologies in their own work. This book presents forecasting methodologies that can be used by forecasting professionals and researchers to provide information for managers in decision making.

1.1 Forecasting and Decision Making

The objective of forecasting is to provide managers with information that will facilitate decision making. Virtually every organization, public or private, operates in an uncertain and dynamic environment with imperfect knowledge of the future. Forecasting is an integral part of the planning and control system, and organizations need a forecasting procedure that allows them to predict the future effectively and in a timely fashion. Part of successful business leadership comes from an ability to foresee future developments and to make the right decisions. Forecasting can be used as a tool to guide such business decisions, even though some level of uncertainty may still exist. Top management is generally interested in making decisions based on forecasting economic factors that are critical in strategic planning and action. While forecasters will not be completely certain of what will happen in the future, they can reduce the range of uncertainty surrounding a business decision.

Managers compete in a global economy that requires strategic decisions in every aspect of the corporate structure—from production and inventory to purchasing, accounting, marketing, finance, personnel, and services. Chief executive officers of many multinational corporations (MNC) recognize the importance of international markets in the growth of their business. Some of these firms have been operating in the international setting for a long time. Others are trying to take advantage of the new economic environment that has come about with globalization. Table 1.1 shows the top ten largest corporations from around the world. The nature of and size of these corporations indicates that the potential for economic gains is substantial when firms operate in the international arena. Some of the MNC’s attain more than half of their sales in foreign countries. For example, Dow Chemical, Coca-Cola, Honeywell, Eastman Kodak have long had presence in the global market and continue to earn substantial revenues from their operations in foreign

Table 1.1 Fortune’s Top Ten Largest Corporations 2008

countries. The Coca-Cola Company in 2007, with operations in more than 200 countries, and a diverse workforce of approximately 90,500 individuals, earned over 71 percent of its revenues from sales overseas (http://www.thecocacolacompany.com/investors/). For these firms, forecasting is an essential tool in business decisions.

Smaller firms are also entering the international markets by offering products or services that serve niche markets. Their ability to survive in these markets depends on recognizing market potentials for their products and good forecasts of demand in these markets.

Economists and policymakers similarly face strategic decisions when dealing with the overall performance of the economy. Forecasting the macroeconomy accurately has been critical to making successful business decisions. Arguably, shortening the time frames between decisions and consequences and accelerating globalization and technological changes have made forecasting more challenging. The simplest macroeconomic question—growth, stagnation, or recession—affects just about everything that is important to an enterprise. After all, investment in plant, equipment, acquisitions, inventories, systems, staff, and training depend heavily on expected demand for increased output. All of these decisions, in turn, depend on accurate forecasts.

Forecasting is a powerful tool that can be used in every functional area of business. Production managers use forecasting to guide their production strategy and inventory control. Firms with multiple product lines are concerned with cost minimization as it relates to material and labor. Furthermore, the trends and availability of material, labor, and plant capacity play a critical role in the production process. Production managers need regular short-term forecasts of product demand as well as long-term demand projections in view of new product lines, new markets, and uncertain demand conditions.

Marketers see similar need as the production managers in using forecasts to guide their decisions. Reliable forecasts about the market size and characteristics (such as market share, trends in prices, sources of competition, and the demographics of the market) are used in making choices on marketing strategy and advertising plans and expenditures. Product demand, sales revenues, and inventory can also enter into the forecast.

Forecasting is an integral part of product research. Marketers use both qualitative and quantitative approaches in making their forecasts. Qualitative approaches to forecasting include the jury of executive opinion, sales force estimates, the survey of customer intentions, and the Delphi method. These qualitative forecasting methods are fast, inexpensive, and flexible. The disadvantages of these approaches are that they are based on individual judgments and thus introduce biases, uncertainties, and inconsistencies in the forecast. The quantitative approaches used to forecast market conditions are either the time-series method or causal models. These methodologies are discussed in later chapters of this book.

Service sector industries such as financial institutions, airlines, hotels, hospitals, sport and other entertainment organizations all can benefit from good forecasts.

Finance and accounting departments make use of forecasting in a number of areas. Financial forecasting allows the financial manager to anticipate events before they occur, particularly the need for raising funds externally. The most comprehensive means of financial forecasting is to develop a series of pro forma, or projected, financial statements. Based on the projected statements, the firm is able to estimate its future levels of receivables, inventory, payables, and other corporate accounts as well as its anticipated profits and borrowing requirements. Cash flow and rates of revenue and expense projections are critical to making business decisions. In addition, speculation in the asset markets requires the use of effective forecast. The airlines, whether large or small, can benefit from good forecast of the load factor, fleet management, fuel and other cost projections. In the hotel and entertainment industries, accurate projection of hotel occupancy rates, for example, have implications for all the other guest services offered. Hospitals have long used forecasting tools to determine the use of emergency room personnel, and cost projections. In the sport industry, forecasts are used for ticket sales for any sporting event. Revenue projections are made based on the performance of a team during a year or years.

The use of forecasts in human resource departments is also critical when making decisions regarding the total number of employees a firm needs. This has implications for the resources of the firm and the need for training of employees. Such forecasts as the number of workers in functional areas, the nature of the workforce (i.e., part-time versus full-time), trends in absenteeism and lateness, and productivity can be helpful in resource planning and management decisions.

Forecasts are used in the public sector in making decisions in the macroeconomy. Economic policy is based, in part, on forecast of important economic indicators. Projections of the GNP, employment, rate of inflation, industrial production, and expected revenues from personal and corporate income taxes all depend on good forecasts. Government uses these forecasts to guide monetary and fiscal policy of the country. Among the many uses of forecasts, population (or demographic) forecasts play an important role in planning government expenditures on health care, social insurance, and infrastructure.

The above examples of how forecasts are used in the various business and economic activities are by no means exhaustive. This simply indicates the significance and breadth of forecasting in decision making.

1.2 The Art and Science of Forecasting

Forecasting as a tool in planning has received a great deal of attention in recent decades. Part of this increased attention is the need to operate successfully in a dynamic global market that is changing constantly. Secondly, with technological advances in computers and quick access to firm-generated data, organizations are looking at ways to improve their decision-making processes. Furthermore, methodological improvements in forecasting have expanded the ability of managers in the private and the public sectors to effectively use these tools in making timely business and economic decisions. How to incorporate these developments into the firm’s decisions is both an art and a science.

Today, firms have a wide range of forecasting methodologies at their disposal. They range from intuitive forecasting to highly sophisticated quantitative methods. Each of these methods has its merits and limitations. To use them appropriately is an art. A manager must depend on personal experience and professional judgment in choosing a particular methodology. The art of forecasting is in recognizing when it is needed and how to incorporate qualitative and quantitative data in the forecasting process. This text discusses forecasting techniques that can supplement the common sense managerial decisions.

The science of forecasting is embedded in the scientific principles of model building. As in any scientific field, scientists begin with using the simplest approach to explain a phenomenon. If the model is a good representation of the real world conditions, and its results do conform with observed phenomena, it is usually accepted as an appropriate tool to predict the future. If, on the other hand, the simple model is not able to capture or explain the observed phenomenon in detail, scientists use more complex models. The more complex the model, the more the assumptions have to be made in the model.

Economists have used simple models to determine the pattern of data and then used this information to predict the future. An economic theory, or a model, is a set of definitions and assumptions that an economist can use to explain certain types of events. Typically expressed in the form of a set of equations, an economic theory describes the mechanism by which certain economic variables interact. For example, the theory of consumer choice suggests that the quantity of a particular good that consumers will buy depends on consumer preferences, their incomes, the price of the good in question, and the price of other goods and services. This theory suggests that, as the price of a good rises, the amount purchased will typically decline. In macroeconomics, we find theories that imply that the aggregate level of investment depends on the rate of interest. Specifically, these theories indicate that higher rates of interest will discourage spending on real capital formation (investment). To evaluate the usefulness of these theories, we must determine their reliability in predicting (forecasting) economic events. Multivariate models are used in these situations to capture the impact of the various variables on the model.

1.3 The Forecasting Process

To develop accurate forecasts consistently, an organization must utilize a systematic procedure for forecasting that can be applied quickly and modified as needed....

Table of contents

• Contents
• Preface
• 1 Forecasting for Management Decisions
• 2 Data Patterns and Choice of Forecasting Techniques
• 3 The Macroeconomy and Business Forecasts
• 4 Data Collection and Analysis in Forecasting
• 5 Forecasting with Smoothing Techniques
• 6 Adaptive Filtering as a Forecasting Technique
• 7 Forecasting with Simple Regression
• 8 Forecasting with Multiple Regression
• 9 Advanced Regression Methodologies in Forecasting
• 10 The Box–Jenkins Method of Forecasting
• 11 Communicating Forecasts to Management
• Appendix A Student t Distribution
• Appendix B Critical Values for the F Distribution
• Appendix C The Durbin–Watson Statistic
• Appendix D Chi-Square (χ2) Distribution
• Appendix E Minitab Guide
• Index