Operational failures in healthcare can hinder employees, potentially decreasing both productivity and quality of care. At the same time, regulatory agencies, industry experts, and consumers increasingly demand that health care organizations learn from prior failures to prevent recurrence. Building on the notion that learning from operational failures requires an accurate understanding of their nature, this paper reports on an in‐depth study of operational failures encountered by hospital nurses. Data analysis suggests that in this context (1) most operational failures stem from breakdowns in the supply of materials and information across organizational boundaries and (2) employees quickly compensate for most failures. We propose that these two conditions—lack of control of processes that create failures and the ease with which employees restore functioning—make it difficult for organizations to recognize these incidents as learning opportunities, and if they do, to capitalize on the opportunity. This has an important implication for efforts to generate organizational learning and improvement from employees’ experiences with failures. Highly interdependent front‐line workers do not control organizational processes responsible for the majority of failures they encounter and have a difficult task convincing powerful associates that these obstacles warrant solution efforts, making it likely operational failures will persist.

Operations management research is beginning to focus on the development and use of reliable and valid scales. OM scale development efforts and scale development in organizational behavior and psychology are compared. Major differences include the fact that OM research tended, until recently, to be theoretical and, when applied, tended to use the firm as a unit of measure. OM research, therefore, seems to lack a common language that other fields have developed. OM literature was searched for completely described scale development efforts, and six studies were identified and reviewed for this paper. Suggested techniques of scale development were compiled primarily from those methods used in research areas such as psychology, organizational behavior, and management. The reviewed studies were compared to the suggested techniques. Many of the same techniques were described by the six studies. The similarities should be encouraging to researchers thinking about scale development studies. Weaknesses in the studies are identified, and suggestions for researchers are presented. Finally, the study provides a discussion of when and why OM researchers might find the development and use of scales advantageous in their research efforts.

Group technology (GT) is a method of organization for factories in which organizational units known as “groups” each complete a particular set or “family” of parts with no backflow, or crossflow between groups, and are equipped with all the facilities they need to do so. Production flow analysis (PFA) is a technique for planning the change to GT in existing batch and jobbing production factories. It finds a total division into groups, using the existing machines and methods to make the existing parts, without any need to buy additional machine tools. Because the change to GT is generally both possible (if PFA is used for planning) and profitable, process organization, in which organizational units specialize in particular processes, is now obsolete.

For many production systems, delivery performance relative to promised job due dates is a critical evaluation criterion. Delivery performance is affected by the way in which work is dispatched on the shop floor, and also by the way the job due dates are assigned to begin with. This pape shows how information regarding congestion levels on the shop floor can be used to assign due dates to arriving jobs in such a way that the mean tardiness of jobs is decreased without increasing the average length of the promised delivery lead times. Baker and Bertrand suggested a modification of the Total Work (TWK) rule for assigning job due dates which adjusts the job flow allowance according to the level of congestion in the shop. Their method gives longer flow allowances to jobs which arrive when the system is congested. Although their modified TWK rule results in lower mean tardiness in many settings, it also generally results in a higher proportion of jobs tardy. This paper presents an alternative modification of the TWK rule which, in most cases, provides mean tardiness as low as or lower than Baker and Bertrand's rule and also results in a lower proportion of jobs tardy. The alternative rule suggested here still results in higher proportion of tardy jobs than the non‐workload adjusted rule in most settings, but suggestions are made for how this problem might be addressed.

Operations management is responsible for achieving an effective and efficient transformation process. Changes taking place in the marketplace and in technology require the correct positioning of operations in the production of goods and services. The service sector within our economy has grown tremendously, representing an ever greater share of our gross national product. A general operations management (OM) paradigm, combining both goods and services, will help researchers as well as practitioners. The operations classification schemes proposed previously have been narrower in scope and incorporated primarily manufacturing systems. The transformation process is universal; major constraints and standard approaches need to be identified regardless of whether it is a good or service produced. This article presents and defines a descriptive OM model. Sample industries and companies are positioned in the market and product/service matrix; in addition, operations activities and their long‐, medium‐, and short‐term solution approaches to operations problems are identified. This operations model keys on the definition of the product/service produced. The major groupings of the first two dimensions of the model depend on (1) market requirements, and (2) whether the product/service is discrete or divisible, fixed site or transportable. Major groupings of the operations activities, required to effectively and efficiently transform the product/service, define the management approach and product/process technology used. These represent the third dimension to our model. The fourth dimension is the time available to plan and implement solutions to operations problems. The four dimensional space‐time paradigm is cohesive and inclusive, and better identifies the major constraints on goods and/or services production. It is intended to analyze and synthesize both the similarities and differences among industries and companies positioned in matrix categories, and thus to help determine the appropriate actions of operations managers during the transformation process. The complexity of the OM paradigm shows realistically the trade‐offs that have to be made in this dynamic area. Changing markets, technology, management, and economics all play a part in positioning operations. Resulting changes in the market requirement and product/service positioning matrix can change unit costs. Movement in any direction on the matrix should not be thought of as a natural evolution but should be meticulously planned. Goods and services producers grouped in each of nine major transformation categories may be able to use similar planning, implementation, and control approaches.

A service framework is needed to foster strategic thinking in services. This paper introduces the service process/service package matrix to meet that need. The important feature of the service process is the degree of customer influence on the service process. The unique characteristic of the service package is that it consists of both tangible and intangible aspects. The service package is described by the degree of customization found in those tangible and intangible elements. Strategic competencies are identified and discussed along the service process dimension, the service package dimension, and the main diagonal of the matrix. Some existing strategic frameworks are embedded and incorporated in the matrix. Additionally, we formulate research propositions based on the matrix. Service firms can use this matrix to gain strategic insights by aligning the type of service package offered with the type of process used to create the service and to have a better understanding of their service operations strategy.

The primary purpose of the research project was to determine if the flow time reductions that occur from splitting jobs into smaller transfer batches result in improved due data performance. The research was performed using a computer simulation of a five machine open job shop. In the open shop environment, each job is unique, and the flow time reductions are solely a result of overlapping operations rather than saved setups from processing similar jobs in sequence. To determine the impact of lot splitting on due date performance, two questions had to be answered. First, how does the impact of lot splitting vary with the magnitude of setup times? Second, how does the size of the transfer batch affect lot splitting performance? This study shows the benefits from lot splitting improve monotonically with decreasing transfer batch size and that lot splitting provides improvements that are essentially independent of the setup time as long as the total utilization (ratio of setup and processing time to available time) is constant. As for the primary research question, lot splitting can provide substantial reductions in mean tardiness (up to 39%) and number of jobs tardy in the open shop environment. The repetitive lots logic developed by Jacobs and Bragg (1988) is reformulated to clearly show that it can be used in combination with any dispatching rule. This rule demonstrates that the repetitive lots logic makes surprisingly good scheduling decisions in spite of its simplicity. Lot splitting is shown to be a simple and effective means of improving the performance of an open job shop. Based on its robust performance in this study, the benefits should be able to be realized in combination with other shop floor control techniques, such as order review release and order expediting.

Although there are numerous studies that address the problems of optimal machine grouping and part family classification for cellular manufacturing, little research has been reported that studies the conditions where cellular manufacturing is appropriate. Flynn (1984) was one of the first to address this issue through a simulation modeling study, and although she did not specifically control for the effect of intercell flow, i.e., the proportion of operations that must be completed for a part outside its assigned cell, the models developed in this study resulted in large amounts of intercell flow. More recently, Morris and Tersine (1990) also addressed the desirability of cellular manufacturing under select manufacturing environments, but their models assumed that no intercell flow was present. In practice, some intercell flow will typically occur after a large‐scale conversion unless many additional machines are purchased to allow each cell to process the complete set of tasks for all parts in a family. In our study, we seek to fill the gaps between the prior simulation studies of cellular manufacturing system performance. We do this by 1) illustrating the negative impact of low to medium intercell flow levels when operating in a wide range of cellular manufacturing environments, and 2) indicating how changes in other operating factors caused by the conversion of a job shop to cellular manufacturing may counter the negative impact of intercell flow. Indeed, we show that many conditions exist where cellular manufacturing can achieve better system performance than a traditional job shop. However, our experiments also point out, like the previous studies, that a conversion to cellular manufacturing can easily degrade system performance—unless other environmental factors are simultaneously changed to counter the negative impact of intercell flow and other problems caused by conversion to cellular manufacturing. Simulation experiments were designed to accomplish these two objectives. We tested the effect of independent variables including intercell flow level, setup time, run time variability, batch size, material handling time, the reduction of setup time made possible by conversion to cellular manufacturing, and product‐mix stability. We found that a conversion to cellular manufacturing is a good alternative to job shop manufacturing when the conversion results in much lower run time variability or in a great reduction in setup times, or when small batch sizes are deemed necessary by management. Further, we found that, in many cases, the performance of cellular manufacturing as measured by mean flow time or work‐in‐ process inventory is better than that of a job shop when the conversion to cellular manufacturing results in a low level of intercell flow—even when other operating factors do not improve after the conversion. This notion substantiates the objective of many cell formation techniques to minimize the level of intercell flow. Finally, we showed that the effect of product‐mix variation is most detrimental to system performance when operating in a cellular manufacturing mode.

The management of large continuous process chemical plants oftentimes must make operating decisions within a rapidly changing economic environment. This paper describes a decision making aid in the form of a production planning model which is immediately responsive to such changes. The model provides cost minimization solutions to “what if” questions of management through the use of linear programming. Implementation upon an interactive computer system provides a user oriented model. A specific type of chemical plant operation involving 13 decision variables illustrates the approach. Five example real‐world situations demonstrate the approach's capability.

This study investigates the existence of different patterns of quality management systems (QMS) and the relationship between such patterns and organizational performance by conducting a quantitative and qualitative study of 225 international and local firms in the electronics industry in Hong Kong. A cluster analysis of the survey data results in the identification of four patterns of QMS, which are labeled as undeveloped, frame, accommodating and strategic, respectively, according to the characteristics that each pattern displays. These four types of QMS were found to be associated with various organizational performance measures according to the stage of their development. The study suggests that organizations can improve their time‐based operational performance by establishing a frame quality system. However, the overall performance of an electronics company can be enhanced only by the establishment of a strategic quality system (SQS), which requires the involvement of top management. Our investigation further suggests that the development of a QMS is influenced by top management’s view on quality management. If quality management is viewed as an assurance system or a defensive strategy for answering customer requirements, a more advanced system will not be developed. The taxonomy developed here also enables researchers to understand the differences of major functions of quality systems at various stages of their development, the obstacles that management faces in the transformation process, and the corresponding strategies to be adopted.