Market Analysis and Forecasting as a Strategic Business Tool

Abstract

Pugh-Roberts has developed a number of simulation models to forecast the demand for products in specific markets. These models contain key feedback relationships which create growth, decline, and cycles in demand. They are unique in their integrated representation of macro-economic, micro-economic, and regulatory factors. Their broad scope makes them powerful enough to specifically show the relative importance of industry factors such as manufacturer pricing policies, inventory and production policies, capacity expansion policies, and the timing of new product introduction, in creating or magnifying market cycles. These models are highly valuable because, unlike simple statistical models, they explain the root causes of cyclical behaviour and can therefore more accurately predict the timing and severity of market cycles. As a result, the models provide valuable information regarding:

• * timing of “booms” and “busts”

• * required production capacity and production rates

• * “windows of opportunity” for new product introduction

• * relative growth of market segments

• * relative importance of growth versus replacement demand

• * relative importance of price, availability, and technology in determining demand and market share

• * effects of macro-economic, regulatory, and/or political changes on overall demand patterns.

These market models have been used successfully in the aerospace, automobile, computer, container shipping, financial services, industrial coatings, insurance, health care, and mail order retailing industries, so they are quite generally applicable. To illustrate their value versus statistical models, two of the existing aerospace models are examined in detail. With emphasis on the “Macro/Micro” issues, the basic causal structure is described and the importance of feedback is demonstrated with sensitivity tests. General uses, and examples of other potential applications, are also discussed.