GLOBAL RELATIONS BETWEEN INVENTORY, MANUFACTURING LEAD TIME AND DELIVERY DATE PROMISES

This paper reports a study of the inventory, lead time and delivery promise data from the Global Manufacturing Research Group. It finds that manufacturing lead time increases as work-in-process inventory increases, as theory suggests. Also, many companies promise delivery in less time than it takes to produce the product, and the difference is not explained by finished goods inventory. The research also shows that the chief benefit of JIT, for those few firms that are achieving benefits, seems to be reduced raw materials

Inventory management: Is there a knock-on effect?

Over the last several years a number of independent empirical studies have shown that organizational performance is related to a portfolio of management techniques, clearly demonstrating that there is no single "silver bullet." In fact, these studies indicate that performance is positively correlated with the number of techniques employed and the depth of their implementation. Operational outcomes in areas like product quality, on-time delivery and productivity, as well as market measures like margins and export sales are both positively related to the implementation of a variety of techniques. This paper explores the relationship between the use of effective inventory management practices (as reflected in inventory turnover) and the implementation of other manufacturing practices. The hypothesis is that effective inventory management practices have a positive knock-on effect on the implementation of other practices. Since organizational performance is related to the implementation of multiple practices, the knock-on effect should have a positive effect on performance as well. The results show that inventory turnover is significantly related to the implementation of other techniques and weakly related to an index of overall company performance. This suggests a positive knock-on effect, but that it takes more than inventory management to achieve high levels of performance. Having established the knock-on relationship adds more evidence to the notion that management excellence in one area begets management excellence in others. (C) 2004 Elsevier B.V. All rights reserved

MANUFACTURING PRACTICES - DIFFERENCES THAT MATTER

This paper presents a comparison of manufacturing practices between Hungary, Western Europe and North America. The supposition is that differences in operational practice may matter in the success of joint ventures or other strategic alliances. The comparison is based on a survey of firms in the small machine tool and non-fashion textile industries. The survey covered practices ranging from forecasting and planning procedures to shop floor decision making. Multivariate analyses were performed to find those areas of practice for which there were differences between the regions and industries. The differences were grouped into three broad categories: "metabolism" (the frequency, horizon, and increment for planning, forecasting and reacting to change), external orientation (the closeness to the market and degree of export sales), and managerial practices in several areas. The differences between the industries were judged less important than those between regions

Is anybody listening? An investigation into popular advice and actual practices

In the decade of the mid-1980s to the mid-1990s, management gurus and consultants alike were touting the advantages of speed over quality and were suggesting other initiatives. Early in this period the global manufacturing research group gathered data on manufacturing practices and performance in non-fashion textile and small machine tool firms. In 1995, follow-up data were gathered from some of the same firms. Data from these surveys are used to determine the extent to which firms exceeded the growth of the economy or the industry. The data are also used to see whether the implementation of manufacturing practices followed the theories elaborated during this period and where firms learn of the practices that show promise of improving performance. Recent case studies of three firms are used to provide insight into the aggregate findings of the surveys. We find that firms do not learn from the management literature, consultants or academics, but use business and trade contacts as their sources. We also find support for the theory that implementing a number of practices will help to provide competitive advantage and that new means of transferring management technology are needed if we are to reach the firms that can benefit from its application. (C) 2002 Elsevier Science B.V. All rights reserved

STATISTICAL INVENTORY CONTROL IN THEORY AND PRACTICE

In this paper the authors report on three areas where statistical inventory control (SIC) expectations diverge from reality. First, actual inventory performance seems immune to the use of modern techniques like material requirements planning (MRP) or just-in-time (JIT). Second, simulation studies seem to provide higher than expected customer service levels. Finally, dynamic organizational actions appear to change both the rules of the game and the way that it is scored. These observations suggest that the lack of effectiveness of SIC models in practice cannot be blamed exclusively on the scientists or the practitioners. The paper suggests that practitioners have not done well in applying the models that are available to them. It also points out that theory and practice are still far apart and suggests some research to remedy this

A new adaptive exponential smoothing method for non-stationary time series with level shifts

Simple exponential smoothing (SES) methods are the most commonly used methods in forecasting and time series analysis. However, they are generally insensitive to non-stationary structural events such as level shifts, ramp shifts, and spikes or impulses. Similar to that of outliers in stationary time series, these non-stationary events will lead to increased level of errors in the forecasting process. This paper generalizes the SES method into a new adaptive method called revised simple exponential smoothing (RSES), as an alternative method to recognize non-stationary level shifts in the time series. We show that the new method improves the accuracy of the forecasting process. This is done by controlling the number of observations and the smoothing parameter in an adaptive approach, and in accordance with the laws of statistical control limits and the Bayes rule of conditioning. We use a numerical example to show how the new RSES method outperforms its traditional counterpart, SES