Vincent A. Mabert

Enterprise resource planning: Managing the implementation process

Abstract Over the past few years, thousands of companies around the world have implemented enterprise resource planning (ERP) systems. Implementing an ERP system is generally a formidable challenge, with a typical ERP implementation taking anywhere from one to five years. The story of the success of ERP systems in achieving the stated objectives is mixed. Some companies have had very successful implementations while others have struggled. This paper empirically investigates and identifies key differences in the approaches used by companies that managed their implementations on-time and/or on/under-budget versus the ones that did not using data collected through a survey of US manufacturing companies that have implemented ERP systems. Logistic regressions are used to classify on-time and on/under-budget firm groups based on the survey responses and to identify the significant variables that contribute to on-time and on/under-budget implementation performance. The results indicate that many different factors ranging from pre-implementation planning to system configuration influence performance, which managers should be sensitive about when implementing major systems like ERP.

The impact of organization size on enterprise resource planning (ERP) implementations in the US manufacturing sector

Enterprise Resource Planning (ERP) systems have experienced a phenomenal growth in the last 5 years and at present they are pervasive in the US manufacturing sector. This paper describes an attempt to chronicle this phenomenon through a series of case studies and an extensive survey. Manufacturing companies ranging in size from a few million dollars in annual revenues to over a hundred billion dollars are included in this study. The key finding from this study is that companies of different sizes approach ERP implementations differently across a range of issues. Also, the benefits differ by company size. Larger companies report improvements in financial measures whereas smaller companies report better performance in manufacturing and logistics.

A simulation analysis of due date assignment rules

Abstract In the job shop scheduling literature, due dates, when considered, are treated in one of two ways: 1) externally imposed or 2) internally set. Externally imposed due dates are outside the control of the scheduler and are assumed to be set by an order entry or marketing department in agreement with the customer. In this situation, current shop status information is not normally considered in setting the date. Research in this setting has focused on the identification of those priority (dispatching) rules which yield good “due date performance.” Due date performance is usually measured by job lateness, job tardiness, and/or proportion of jobs tardy. Internally set due dates are established by the scheduler as each job arrives. Using job characteristics and/or shop status information, the scheduler estimates the job flow time for each job and sets the due date accordingly. The early research in this setting did not focus explicitly on predicting individual job flow times, but rather on identifying simple due date assignment heuristics which provide good due date performance in concert with a variety of priority rules. More recent researchers have included shop status information in setting due dates. This article reports on a study of eight different rules for specifying due dates in a job shop and the evaluation of their performance. A series of tests is conducted with a computer simulation model utilizing three different dispatching rules to control the sequencing of work. Mean tardiness, mean absolute missed due dates, and standard deviation of lateness data are collected to measure each rules performance. This study reports the first comparative analysis of various due date assignment rules that have been mentioned in the literature by different authors. The findings reported here provide some useful insight into past and future research. First, both job characteristic and shop status information should be used to develop due date assignment rules. Second, the dispatching rule used to sequence jobs at work centers influences shop performance. Third, information about work center congestion along a jobs routing is more useful information than general shop conditions. And fourth, the use of more detailed information in predicting flow time provides only marginal improvement in performance over other rules that use more aggregate information.

Customizing concurrent engineering processes: Five case studies

Abstract Once hailed as the salvation of U.S. manufacturing competitiveness, concurrent engineering (CE) offers the potential for faster development of higher quality, more producible products. Unlike traditional, serial approaches to new product development (NPD), CE emphasizes cross-functional integration and concurrent development of a product and its associated processes. As Morgan L. Swink, J. Christopher Sandvig, and Vincent A. Mabert explain, however, CE is not a plug-and-play process. Successful CE implementation approaches differ depending on such factors as product characteristics, customer needs, and technology requirements. We can better understand those differences by examining CE implementation in the five NPD programs discussed here: the Boeing 777 aircraft, the heavy duty diesel engine at Cummins Engine Co., the thermoplastic olefin automotive coating at Red Spot Paint and Varnish Co., the airborne vehicle forward-looking infrared night vision system at Texas Instruments, and the digital satellite system at Thomson Consumer Electronics. Teams provide the primary integration mechanism in CE programs, and three types of teams appeared frequently in these projects: a program management team, a technical team, and numerous desing-build teams. Depending on the projects complexity, an integration team may be needed to consolidate the efforts of various design-build teams. Task forces also may be formed to address specific problems, such as investigating an emerging technology. Some projects emphasized collocation and face-to-face communication. Others relied on phone conversations, documents, and electronic mail. Projects focusing on design quality relied on formal presentations and periodic review meetings. Projects emphasizing development speed required frequent, informal communications. Programs addressing design quality required extended product definition and performance testing, with input from design engineering, marketing, and customers. Efforts to reduce development time involved small, informal teams led by design engineers and managers. Aggressive product cost goals necessitated intensive interaction between product designers and manufacturing personnel. Highly innovative products required early supplier involvement and joint engineering problem solving. Formal design reviews and shared design data systems aided information sharing between internal and external design groups.

Research Opportunities in Purchasing and Supply Management

Purchasing and supply management (PSM) are crucial for the effective and efficient operation of manufacturing firms, now more than ever. The PSM function has evolved from being routine and mechanical to a function that can deliver true competitive advantage. The trend toward increased globalisation and outsourcing, along with a focus on innovation- and capability-driven supply management, has led to an increased reliance on suppliers. This has significantly enhanced the importance of PSM for manufacturing companies. The heightened significance in practice has been paralleled by an increasing attention of researchers in developing theories and chronicling best practices. At the same time, the rapid rate of change represents both daunting challenges and exciting opportunities for research in PSM. It is the goal of this article to highlight such challenges and discuss ensuing opportunities in PSM research. This objective is accomplished via the nominal group technique involving a panel of leading scholars in the purchasing and supply management field. As such, the article presents a synthesis and discussion of important research themes, poses a set of intriguing research opportunities, and serves as a motivation for future investigation.

A framework for the study of due date management in job shops

This paper presents a conceptual model of due date management in job shops. The model describes, in general terms, some of the important variables in the due date management problem and some of their interrelationships. The model is used as a framework within which to discuss the treatment of the due date management problem in the literature, and some ideas for directions for further research are presented.

ITEC: An Integrated Manufacturing Instructional Exercise

Describes an integrative microcomputer‐based exercise, ITEC, used in teaching manufacturing strategy and manufacturing planning and control courses. The exercise allows students the opportunity to gain actual experience in making strategic decisions in manufacturing and in managing the flow of materials in complex operations. It gives students experience in making process choice decisions, and reinforces their understanding of the difference between the planning and execution decisions necessary to manage manufacturing operations using MRPII planning logic under dynamic conditions. It provides experience in managing both batch and line operations and is useful in demonstrating the introduction of Just‐in‐Time manufacturing. The exercise also provides experience in scheduling and co‐ordinating vendor operations to support manufacturing requirements. Because of the uncertainty in customer demand, process yields and vendor deliveries, students gain insight and facility in managing complex operations with imp...

Scheduling projects with heterogeneous resources to meet time and quality objectives

In service organizations, heterogeneity in workforce skills can lead to variation in end-product/service quality. The multi-mode, resource-constrained, project scheduling problem (MRCPSP), which assumes similar skills among resources in a given resource pool, accounts for differences in quality levels of individuals by assigning different activity durations depending on the skill level used. This approach is often inadequate to model the problem type investigated here. Using typical projects from the customer training division of a large telecommunications company (which motivated this research), a labor assignment problem using a successive work-time concept is formulated and solved using integer programming optimization procedures. The setting represents a multiple-project environment where projects are separate and independent, but require the same renewable resource mix for their completion. The paper demonstrates how the output of the model can be used to identify bottlenecks (or critical resource skills), and also demonstrates how cross-training the appropriately skilled groups or individuals can increase throughput. The approach guides decision-making concerning which workers to cross-train in order to extract the greatest benefits from worker-flexibility.

Measuring the impact of part-time workers in service organizations

Abstract In the last twenty years we have seen a significant increase in interest by practicing managers and academic researchers in the labor/staff scheduling decision. In particular, service firm managers have focused their attention on improving the productivity of their labor intensive operations by an increased use of part-time personnel. These actions have been motivated by the presence of significant variations in hourly and daily work loads faced by these firms and the desire to provide flexibility to adequately match staff capacity with customer demand. The past employment practice of using full-time staff causes significant idle capacity to exist in many firms, reducing productivity. The significant increased use of part-time staff has allowed todays managers to correct this situation by reducing the amount of idle labor capacity, thus reducing operating cost. Academic researchers have also investigated the labor scheduling problem during the past two decades. They have analyzed and evaluated mathematical algorithms, optimal and heuristic, to efficiently solve the staff tour scheduling problem. Some of this work has eventually found applicability in a number of service firms. However, most of these studies have focused on the scheduling of full-time staff to meet varying daily and hourly work load shifts and little insight has been attained in understanding a number of trade-off issues in this area. In this paper we investigate the complex issue of the trade-off between full-time and part-time staff and develop a relative “measure of flexibility” for using part-time individuals. First, we demonstrate, as might be expected, how greater flexibility reduces idle labor capacity. Second, we define and test what is “scheduling flexibility,” as measured by work-hours-per-day and work-days-per-week. Third, we document the marginal reduction in labor hours scheduled attainable with increased flexibility, using actual operating data from a lockbox department in a large Chicago commercial bank. And fourth, we demonstrate the cost implications of using part-time staff by employing operating data from the wire transfer department of a New York commercial bank, where we examine the problem using cost data as a basis for comparing the relative impact of various labor scheduling decisions and flexibility. We illustrate the common trade-offs that must be evaluated due to various labor costs, turnover rates, full and part-time personnel hours and differing productivity rates among various categories of personnel. Our approach illustrates the type of analysis that should be conducted by practicing managers to adequately evaluate the trade-offs for the staffing decision when using both full and part-time personnel.

A decision support system for the courier vehicle scheduling problem

The timely collection and transportation of checks from branches to the operations center is a primary concern to bank managers. Transit checks need to be cleared quickly to maximize available funds to the banks cash managers. However, management must not over-commit resources, such as drivers and vehicles, to improve the movement of checks from branch banks to the operations center. Bank managers must make difficult decisions regarding courier fleet size, routing, and scheduling in order to balance these conflicting goals and to minimize overall system costs. We present a micro-computer based decision support system (DSS) that helps bank managers make good decisions for their vehicle courier service. This system, known as Chexpedite, helps establish the correct number of vehicles, the appropriate collection routes, the timing of the routes, and a view of the check flow pattern into the operations center (back office check processing center). The system has been implemented at a number of banks, indicating its value to bank management. In this paper, the logic of Chexpedite and its database, optimization, and simulation capabilities are presented. A case study application demonstrates the system. The final section concludes with a discussion of Chexpedites strengths and weaknesses.