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In this paper an investigation is made of the properties and use of two aggregate measures of forecast bias and accuracy. These are metrics used in business to calculate aggregate forecasting performance for a family (group) of products. We find that the aggregate measures are not particularly informative if some of the one-step-ahead forecasts are biased. This is likely to be the case in practice if frequently employed forecasting methods are used to generate a large number of individual forecasts. In the paper, examples are constructed to illustrate some potential problems in the use of the metrics. We propose a simple graphical display of forecast bias and accuracy to supplement the information yielded by the accuracy measures. This support includes relevant boxplots of measures of individual forecasting success. This tool is simple but helpful as the graphic display has the potential to indicate forecast deterioration that can be masked by one or both of the aggregate metrics. The procedures are illustrated with data representing sales of food items. Copyright © 2005 John Wiley & Sons, Ltd.

The Expert System that one of the authors had developed during his dissertation was tried on the data set of the M3 Competition. The expert system was originally designed to forecast monthly demand for industrial products in a distribution environment and was modified to run the data. The results of the application of the system were mixed as in some of the time series the results were statistically undistinguishable with the exception of the monthly series. In general, the intervention did not improve the accuracy and the effort required to do it was substantial.

We examined automatic feature identification and graphical support in rule-based expert systems for forecasting. The rule-based expert forecasting system (RBEFS) includes predefined rules to automatically identify features of a time series and selects the extrapolation method to be used. The system can also integrate managerial judgment using a graphical interface that allows a user to view alternate extrapolation methods two at a time. The use of the RBEFS led to a significant improvement in accuracy compared to equal-weight combinations of forecasts. Further improvement were achieved with the user interface. For 6-year ahead ex ante forecasts, the rule-based expert forecasting system has a median absolute percentage error (MdAPE) 15% less than that of equally weighted combined forecasts and a 33% improvement over the random walk. The user adjusted forecasts had a MdAPE 20% less than that of the expert system. The results of the system are also compared to those of an earlier rule-based expert system which required human judgments about some features of the time series data. The results of the comparison of the two rule-based expert systems showed no significant differences between them.

This paper discusses the development of a heuristic methodology to generate salary merit increases and to schedule these salary actions along a specified planning horizon. The heuristic approach consists of two procedures, referred to as Heuristic Procedure 1 and Heuristic Procedure 2. For a group of executive personnel, Heuristic Procedure 1 yields salary increase percentages, in such a way that external consistency is maximized without violating internal consistency conditions. Heuristic Procedure 2 establishes the time intervals between salary increases for each eligible employee. A comparison is performed, in terms of computer execution time and optimality of solutions, between the heuristic methodology and a mathematical programming approach developed for formulating salary administration guidelines. Computational results are reported for a number of sample problems.

A difficult inventory control decision is that encountered by electronics warehouses which must stock a large variety of items in a rapidly changing, high cost industry. Electronic component distributors face high variability in demand, a lack of sufficient historical data and short product life cycles. The selection of accurate forecasting techniques for such a data set is of major importance. Four forecasting approaches were tested. They include single exponential smoothing with different smoothing constants as well as double exponential smoothing, adaptive response rate exponential smoothing and median of the historical data as the forecast The selection process requires the utilization of an appropriate metric. In this study, in addition to the traditional accuracy metric an added criterion, the use of an asymmetric economic measure of forecasting accuracy is proposed and tested. The forecasting methods utilized accuracy and economic measures, with a large data set. The different measures yie...

A large body of empirical studies has shown that a forecast developed by combining individual base forecasts performs surprisingly well. Previous work on the combination of forecasts has been confined to the area of time series forecasting. This work extends the combination of forecasts technique into the domain of forecasting one-time competitive events, specifically the scaled, relative finishing position of horses in thoroughbred sprint races. The present research develops a framework for the selection of the base forecasts and selects 12 base forecasts for analysis. The performance of the combination of the base forecasts is assessed on a sample of sprint races. Results of the analysis strongly suggest that the combination approach is both appropriate and effective. Some differences in results between this work and previous work in the time series domain suggest promising avenues for future research.

The most common method that materials managers use for classifying inventory items for planning and control purposes is the annual-dollar-usage ranking method (ABC classification). Recently, it has been suggested that multiple criteria ABC classification can provide a more comprehensive managerial approach, allowing consideration of other criteria such as lead time and criticality. This paper proposes the use of the Analytical Hierarchy Process (AHP) to reduce these multiple criteria to a univariate and consistent measure to consider multiple inventory management objectives.

ABC analysis is used to sort inventory into categories which determine how much attention they will be given. But it is of wider management application and can be extended to cope with more than one classification criterion.

The selection of forecasting methods is a complicated issue. The situation is created by the need to identify the best method for a time series. Criteria for selection must be defined. If the sole criterion is accuracy, then a comparison of two forecasting methods can be made by testing them ex post while utilizing the time series. Care should be exercised in the selection of the accuracy metric. A statistical test should be made to determine if the results are significantly different. The test recommended is the Wilcoxson test since it is less restrictive to the nature of the error and less susceptible to outliers.

This paper addresses the importance of goal setting in the operations function. The importance of goal setting and its possible role in the implementation and operation of production systems is considered with particular emphasis on Material Requirements Planning (MRP). It has been argued that an operative goal setting process can improve employees' performance in any area of the organisation. Likewise, companies with a high‐level MRP system are expected to show high performance levels. This paper offers empirical support for these claims and further argues that the combination and interaction of the two processes results in synergistic effects. To support these arguments the paper draws on both theoretical studies and the results of a small regional survey.

This article presents the results of applying multicriteria ABC analysis to maintenance inventories. A large service organization and a consumer goods manufacturer participated in the study. The managers in both organizations used cost and noncost criteria for developing the ABC categories for inventory management. The study shows that managers can develop noncost criteria and classify the inventory items in ways that combine the criteria types. Specific policies were defined for managing the items in the industrial firm. Once the benefits of the methodology were demonstrated, a year-long program for implementing the system was developed. The project is estimated to cost less than 10 to 15% of the available storeroom clerk manhours and provide substantially greater benefits.

The paper reports results of an experiment conducted to evaluate subjective versus objective combination of forecasts. The subjects were undergraduate students at Texas A&M. The students forecasted two different types of time series. The results found show that the subjective combination of forecasts improves their accuracy as compared with individual efforts. Four ex-ante weighting methods were also used to combine the forecasts. They all improve the accuracy of the forecasts. The best results, though, were from the subjective combination of forecasts.

Prioritising items for management attention has been advocated in operations management for a long time, normally using ABC analysis (inventory control). This focuses attention on the “A” category items to maximise managerial effectiveness. Empirical evidence shows that this is a reasonable rule for allocating scarce resource‐management time but presents difficulties when the manager has to take more than one important dimension of a situation into account. A joint criteria matrix is put forward within the ABC framework and an industrial application given. The joint criteria matrix has practical utility provided ranking on some scale of measurement is realistic. The appropriate number of categories must be defined by the user. Combining criteria will probably require different analytical approaches, e.g. goal programming or heuristic approaches. Utilisation of the matrix by managers can provide an explicit method for taking a range of criteria into account in the development of inventory policies.