Everette Gardner

Everette Gardner
University of Houston | U of H, UH · Department of Decision & Information Sciences

About

39
Publications
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3,334
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Publications

Publications (39)
Article
Although intermittent demand items dominate service and repair parts inventories in many industries, research in forecasting such items has been limited. A critical research question is whether one should make point forecasts of the mean and variance of intermittent demand with a simple parametric method such as simple exponential smoothing or else...
Article
The “Golden Rule” checklist by Armstrong, Green, and Graefe, in this issue (referred to as AGG below), is a systematic procedure for implementing conservative forecasting principles, and it should help close the long-standing gap between theory and practice. The checklist is both a practical tool and an empirical research agenda. Trend damping is a...
Article
In supply chains, forecasting is an important determinant of operational performance, although there have been few studies that have selected forecasting methods on that basis. This paper is a case study of forecasting method selection for a global manufacturer of lubricants and fuel additives, products usually classified as specialty chemicals. We...
Article
Full-text available
The damped trend method of exponential smoothing is a benchmark that has been difficult to beat in empirical studies of forecast accuracy. One explanation for this success is the flexibility of the method, which contains a variety of special cases that are automatically selected during the fitting process. That is, when the method is fitted, the op...
Article
Full-text available
Over the past twenty years, damped trend exponential smoothing has performed well in numerous empirical studies, and it is now well established as an accurate forecasting method. The original motivation for this method was intuitively appealing, but said very little about why or when it provided an optimal approach. The aim of this paper is to prov...
Article
Exponential smoothing methods gave poor forecast accuracy in Fildes et al.'s study of telecommunications time series. We reexamine this study and show that the accuracy of the Holt and damped trend methods can be improved by trimming the time series to eliminate irrelevant early data, fitting the methods to minimize the MAD rather than the MSE, and...
Article
Despite the general acceptance of exponential smoothing, the choice of a specific smoothing model is often a difficult problem. Previous research involving smoothing-model comparisons and the penalties for selection of the wrong model has been limited. This paper evaluates the performance of a representative group of smoothing models over a variety...
Article
Management goals in distribution inventories are often expressed in terms of the maximum percentage of aggregate sales that should be back ordered. This paper compares several strategies for allocating total inventory investment to each item stocked in order to meet such goals. Computational results are given from a wholesale distribution inventory...
Article
In Gardner [Gardner, E. S., Jr. (1985). Exponential smoothing: The state of the art. Journal of Forecasting 4, 1–28], I reviewed the research in exponential smoothing since the original work by Brown and Holt. This paper brings the state of the art up to date. The most important theoretical advance is the invention of a complete statistical rationa...
Article
Dimensional analysis is widely used in physics and engineering to contribute to modeling systems in which variables are measured in incompatible units. I used dimensional analysis to rank the airlines in overall quality based on US Department of Transportation data: on-time arrivals, denied boardings, mishandled baggage, and customer complaints. Th...
Article
This paper analyzes procedures for seasonal adjustment of inventory demand series at a large US auto parts distributor, BPX Holding Corporation of Houston, TX. The company’s forecasting system made no attempt to classify demand series as seasonal or nonseasonal. All demand series were assumed to be seasonal. They were seasonally-adjusted using a mu...
Article
In an earlier paper, we found that damped-trend, seasonal exponential smoothing was more accurate than a simple version of Focus Forecasting, based on Flores and Whybark [Production and Inventory Management Journal, (1986), 14, 339–366]. This note tests Demand Solutions, a more sophisticated version of Focus Forecasting. As in the earlier paper, we...
Article
This paper evaluates the ex ante performance of rule-based time series forecasting systems proposed in earlier research. The author shows that comparable performance can be obtained with a simpler alternative, a damped-trend version of exponential smoothing fitted to minimize the Mean-Absolute-Deviation (MAD) criterion. The results suggest that the...
Article
Focus Forecasting is a popular heuristic methodology for production and inventory control although there has never been a rigorous test of accuracy using real time series. We compare Focus Forecasting to damped-trend, seasonal exponential smoothing using five time series of cookware demand in a production planning application. We also make comparis...
Article
US-Japan productivity comparisons published by the US Bureau of Labor Statistics are misleading. In the US, growth is understated because the BLS is unable to measure productivity for more than half of the labor force. Productivity growth is assumed to be zero for all of these people. In Japan, growth is exaggerated because small business output is...
Article
This paper is an applied study in forecasting the failure of component parts in computer systems to aid in production planning and inventory control. The aim is to develop a reasonably simple forecasting system that can be operated by managers rather than statisticians. Monthly failures of components are shown to be related to cumulative shipments...
Article
This paper analyzes the impact of forecasting on inventory decisions in a large physical distribution system. Alternative forecasting models are evaluated by developing tradeoff curves between inventory investment and customer service. The results demonstrate that the choice of forecasting model is an important factor in determining the amount of i...
Article
In this paper we apply the strategy of trend-damping to the popular Winters exponential smoothing systems for seasonal time series. Efficient model formulations are derived for both multiplicative and additive seasonal patterns. An algorithm is given to test the stability of the models in cases where predetermined smoothing parameters are used. Emp...
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Full-text available
Model identification has traditionally been ignored in forecasting via exponential smoothing. The usual practice is to apply the same model to every time-series in a collection. This paper develops a procedure for model identification in large forecasting applications based on an examination of variances of differences of the time-series. The order...
Article
Theoretical approaches to computing prediction intervals require strong assumptions that do not appear to hold in practice. This paper presents an empirical approach to prediction intervals that assumes very little. During model-fitting, variances of the errors are computed at different forecast leadtimes. Using these variances, the Chebyshev inequ...
Article
This paper discusses our aims in organizing this special issue. We believe that a synthesis of the field is needed to resolve the many conflicts between theory and empirical evidence and between advocates of the various forecasting methods. One step toward synthesis is to agree on the major problems in the field, the goal of this issue. Another ste...
Article
For a miltary distribution system with a fixed investment budget, trade-off curves between two aggregate variables were developed: reordering work load and customer service. The curves showed that reallocating investment funds from safety stocks to cycle stocks would cut reordering work load by 20 percent, with no impact on customer service. Implem...
Article
Most time series methods assume that any trend will continue unabated, regardless of the forecast lead time. But recent empirical findings suggest that forecast accuracy can be improved by either damping or ignoring altogether trends which have a low probability of persistence. This paper develops an exponential smoothing model designed to damp err...
Article
This paper is a critical review of exponential smoothing since the original work by Brown and Holt in the 1950s. Exponential smoothing is based on a pragmatic approach to forecasting which is shared in this review. The aim is to develop state-of-the-art guidelines for application of the exponential smoothing methodology. The first part of the paper...
Article
This paper compares the performance of CUSUM and smoothed-error tracking signals for monitoring the adequacy of exponential smoothing forecasts. Previous research has favoured the CUSUM. However, there is some evidence that the performance of the smoothed-error signal can be improved by a simple modification in its application: the use of different...
Article
Constrained multi-item inventory models have long presented signifcant computational problems. This article presents a general algorithm to obtain simultaneous solutions for order quantities and safety stocks for each line item in an inventory, while satisfying constraints on average inventory investment and reordering workload. Computational exper...
Article
This paper evaluates a variety of automatic monitoring schemes to detect biased forecast errors. Backward cumulative sum (cusum) tracking signals have been recommended in previous research to monitor exponential smoothing models. This research shows that identical performance can be had with much simpler tracking signals. The smoothed-error signal...
Article
Adapting the appropriate forecasting technique to a health care environment is essential for cost control. As the Chapel Hill experience shows, forecasting is within everyone's reach and can successfully reduce costs.
Article
The marginal cost information needed to implement traditional inventory models is not likely to be available in practice. The most important inventory management issues in practive involve aggregate objectives and constraints while the richest theoretical models deal with single item management. To help resolve these problems, the authors propose t...