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The conditions under which forecasts from expert judgement outperform traditional quantitative methods are investigated. It is shown that judgement is better than quantitative techniques at estimating the magnitude, onset, and duration of temporary change. On the other hand, quantitative methods provide superior performance during periods of no change, or constancy, in the data pattern. These propositions were tested on a sample of real business time series. To demonstrate how these propositions might be implemented, and to assess the potential value of doing so, a simple rule is tested on when to switch from quantitative to judgemental forecasts. The results show that it significantly reduces forecast error. These findings provide operations managers with some guidelines as to when (and when not) they should intervene in the forecasting process.

Accurate forecasting has become a challenge for companies operating in today's business environment, characterized by high uncertainty and short response times. Rapid technological innovations and e‐commerce have created an environment where historical data are often of limited value in predicting the future. In business organizations, the marketing function typically generates sales forecasts based on judgmental methods that rely heavily on subjective assessments and “soft” information, while operations rely more on quantitative data. Forecast generation rarely involves the pooling of information from these two functions. Increasingly, successful forecasting warrants the use of composite methodologies that incorporate a range of information from traditional quantitative computations usually used by operations, to marketing's judgmental assessments of markets. The purpose of this paper is to develop a framework for the integration of marketing's judgmental forecasts with traditional quantitative forecasting methods. Four integration methodologies are presented and evaluated relative to their appropriateness in combining forecasts within an organizational context. Our assessment considers human factors such as ownership, and the location of final forecast generation within the organization. Although each methodology has its strengths and weaknesses, not every methodology is appropriate for every organizational context.

Examines an alternative approach to labour utilisation, based on the concept of simulated annealing, implemented on a microcomputer. Demonstrates the use of the new approach in a study of the potential labour utilisation effect of two types of scheduling flexibility: shift length flexibility and meal‐break placement flexibility. Finally, offers implications of the new approach for management.

In the decade since Tillery, Rutledge and Inman reviewed the treatment of quality management in leading US production and operations management (P/OM) textbooks, attention to quality, once the watchword and driving force in world business, has faded in both the practitioner and popular press. The ultimate purpose of the present research was to establish the progress, current status, and relevancy of the treatment of quality in current US P/OM textbooks, which remain the principal source of quality information in the undergraduate P/OM core course, preparing most future US managers as well as many international managers of tomorrow. Results of the present study indicate that over the last decade US P/OM textbooks have begun to reflect a more proactive and less reactive approach to quality management. However, results also indicate that current US P/OM textbooks lack relevancy of their quality content to practitioner needs, treat TQM and other holistic approaches to quality management superficially, and have little consistency concerning quality emphases.

The paper proposes that improvements in the productivity of process technology can be achieved by analyzing and instituting changes in the rules and methods through which work is organized. The implementation of information‐based process technology in a bank’s check processing system provides the context for the study. A simulation approach is used to assess the benefits of introducing alternative workflow scheduling rules after implementation of the new technology. Results from a hypothetical setting, using data from an actual check processing center, demonstrate the cost advantages of introducing a priority‐based scheduling rule. The implications and problems associated with practical implementation are discussed.

This paper proposes a relationship between decision making and key qualities of business systems.

The authors explore the relationship between decision making and systems by contrasting the decision making in two well‐known systems: MRP and JIT. The two systems present two sets of opposing qualities. By considering the relationship between a decision and its environment, we propose that these sets of qualities are not unique to MRP and JIT. They arise from two general approaches to decision making. Having introduced the two approaches, we analyze three product development systems: Stage‐Gate, Agile and Lean.

In manufacturing, MRP is a push system; JIT is a pull system. MRP seeks perfection; JIT seeks consistency. MRP gives decision makers great discretion; JIT constrains decisions. These opposing qualities, and others, arise from two general approaches to decision making: outside‐in and inside‐out. As the difficulty of decisions increase, relative to a decision maker's ability, the cost of mistakes becomes significant. In these situations, the inside‐out approach should outperform the outside‐in approach. The inside‐out approach constrains decision making to limit the cost of errors. The outside‐in approach embraces complexity, exposing itself to more decision errors. In product development, the Lean and Agile systems exploit the inside‐out approach. They constrain decisions and reduce the cost of errors that arise from two sources. Lean addresses interactions, which add complexity to business systems. Agile addresses unpredictability, which adds uncertainty to business systems.

The relationships the authors propose show how decision making affects the development, control and performance of business systems.