A Behavioral Intervention Approach for Small Business Consultants: Implementing Forecasting Techniques

Article excerpt

ABSTRACT

Over the last twenty years a variety of quantitative forecasting techniques have been developed and applied in organizations as diverse as manufacturing, marketing, and service concerns. Large firms typically have specific staff positions allocated to performing the forecasting function. Although the same forecasting techniques can be applied in smaller organizations, their acceptance has not been widespread.

An effective way for small businesses to develop formal forecasting procedures is through the services of a small business consultant via either Small Business Development Centers or Small Business Institute programs. To aid consultants in implementing quantitative forecasting techniques in small businesses, organizational barriers to adoption are identified, followed by a discussion of behavioral interventions and implications.

INTRODUCTION

Organizational forecasting is the process of estimating future events for the purpose of effective planning and decision making. It is one of the most critical organizational functions; the forecast enables managers to anticipate the future and to plan accordingly. The organizational forecast serves as a basis for all other business decisions. The quality of these business decisions can only be as good as the forecast upon which they are based. Forecasts are used to set production schedules, budget capital and allocate resources to programs. Forecasting accuracy has been made more difficult in today's economy with unstable business conditions. On the other hand, availability of technology such as computers and forecasting software has enhanced the forecasting process.

The field of formal forecasting has developed numerous quantitative forecasting techniques (QFTs). However, surveys of business managers show that organizations predominantly rely on judgmental forecasts (Dalrymple, 1987; Mentzer & Cox, 1984; Sparkes & McHugh, 1984). This can create problems for organizations that value accurate forecasting. Research comparing accuracy of judgmental and quantitative methods shows quantitative techniques to be superior both in terms of accuracy as well as timeliness (Armstrong, 1985; Hogarth & Makridakis, 1981), though judgmental forecasts can provide advantages under certain circumstances (Makridakis, Wheelwright, & McGee, 1983). Further, there is a large literature base that points to the numerous biases inherent in judgmental forecasting (Hogarth, 1987). These biases include lack of consistency, tendency to overforecast, anchoring effects, and wishful thinking.

In the smaller firm forecasting is generally viewed as a complicated set of tools which require a great deal of sophisticated data processing resources, complicated mathematical models, and expertise for interpretation (Wacker & Cromartie, 1979). However, it is the smaller firm, with reliance on competitive advantage and niche identification, that so critically needs to utilize forecasting methods. In addition, smaller firms typically have more restricted budgets; therefore, effective management of resources is more critical in these firms. To increase acceptance and use of quantitative forecasting methods in smaller firms, it is the small business consultant, through Small Business Development Centers (SBDC) and Small Business Institute (SBI) programs, that can play a decisive role. The SBDC and SBI should serve as the points of access for small businesses to receive such services. The success of implementation of formal forecasting will rest upon the ability of the small business consultant to understand not only small business needs and forecasting methodologies, but the behavioral implications of such a process.

In order to aid the small business consultant, this paper develops a prescriptive model and guidelines for use when assisting the small business in developing and implementing formal forecasting procedures.

We begin by taking a normative approach to identify the main organizational barriers to accepting and using formal forecasting techniques. …

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