This case focuses on a major manufacturing division ($1.2 billion sales; 5500 employees) of a global oilfield services company as it converts from a departmental organization with a "traditional" machine shop hierarchy to a team-based environment. During the conversion, roles and responsibilities change from a traditional foreman structure to a Self-Directed Work Team (SDWT) structure for the Radial Bearing Team. Individual behaviors and the dynamics of change influence how the team copes with new responsibilities, authority and problem solving as together, they manage equipment utilization and the day-to-day workflow, and control quality. Some dysfunction arises as the leaders of this organization manage the change process while trying to support the new roles and ideas. The team is successful, but everyone has to encourage innovation while adapting to the changing environment. The case also highlights specific techniques the team adopts for monitoring its performance as it assumes responsibility and accountability for quality improvement. Management had challenged the unit's leadership to produce results that justified the implementation of Self-Directed Work Teams (SDWTs). Now, George Smiley, the machine shop manager, and Shane Husky, the internal OD specialist, had to present evidence to help management decide if expansion of the SDWT program was warranted and the best practices learned from the RBT experience that would contribute to future success.

Statistical Process Control for Managers is an eight-chapter book published by Business Expert Press in 2014 and written by Victor E. Sower, professor emeritus of operations management at Sam Houston State University. The book provides a conceptual approach to using statistical process control (SPC) to inform and improve decision-making around business processes and quality improvement. The author reviews the basic methods of SPC and provides practical guidance for using specific tools. He incorporates real-world examples throughout the book and ends each chapter with a summary of key points, as well as questions for managers to ask when applying the concepts to their own organizations. In Chapter 1, The Value SPC Can Add to Quality, Operations, Supply Chain Management, and Continuous Improvement Programs (15 pages), the author explains the benefits of using SPC to understand and manage a manufacturing process. He demonstrates how control charts can help a manager assess and control the variation and uncertainty in a process. He explains how SPC relates to each stage of a business process, from scheduling to cost management and inventory to quality control. He also gives examples of the positive impact of SPC on continuous quality improvement and managing variation.

Statistical Process Control for Managers is an eight-chapter book published by Business Expert Press in 2014 and written by Victor E. Sower, professor emeritus of operations management at Sam Houston State University. The book provides a conceptual approach to using statistical process control (SPC) to inform and improve decision-making around business processes and quality improvement. The author reviews the basic methods of SPC and provides practical guidance for using specific tools. He incorporates real-world examples throughout the book and ends each chapter with a summary of key points, as well as questions for managers to ask when applying the concepts to their own organizations. Chapter 2, Variation and What It Means to be in Control and Capable (14 pages), addresses the concept of process variation. The author reviews the concepts of control and capability and offers illustrative examples. He explains how a control chart can be used to determine the level of control in a process. He also reviews measurement techniques and the importance of accuracy in quantitative measures and validity in qualitative measures.

Statistical Process Control for Managers is an eight-chapter book published by Business Expert Press in 2014 and written by Victor E. Sower, professor emeritus of operations management at Sam Houston State University. The book provides a conceptual approach to using statistical process control (SPC) to inform and improve decision-making around business processes and quality improvement. The author reviews the basic methods of SPC and provides practical guidance for using specific tools. He incorporates real-world examples throughout the book and ends each chapter with a summary of key points, as well as questions for managers to ask when applying the concepts to their own organizations. In Chapter 3, Introduction to Control Charts (20 pages), the author demonstrates how to read and create a map of a business process. Using an individual control chart (I-chart), he explains the chart elements and how software programs can be used to create them. He explains how to determine whether or not a process is in control by analyzing patterns on a control chart and reviews single point rules, run rules, and zone rules, as well as nonrandom patterns. He offers insight on how to react to a process out of control by creating and implementing an action plan.

Statistical Process Control for Managers is an eight-chapter book published by Business Expert Press in 2014 and written by Victor E. Sower, professor emeritus of operations management at Sam Houston State University. The book provides a conceptual approach to using statistical process control (SPC) to inform and improve decision-making around business processes and quality improvement. The author reviews the basic methods of SPC and provides practical guidance for using specific tools. He incorporates real-world examples throughout the book and ends each chapter with a summary of key points, as well as questions for managers to ask when applying the concepts to their own organizations. Chapter 4, Basic Control Charts for Variables (14 pages), provides an overview of the different charts that can be used to analyze continuous measurement information such as height, weight, and length. The author reviews the utility of different charts depending on the type of data sample. He also explains how charts are used in pairs to assess both the changes in process average and process variation (e.g. I- and MR charts, the X-bar and R-charts, and the X-bar and S-charts). The chapter includes a guide to determining which chart type to use.

Statistical Process Control for Managers is an eight-chapter book published by Business Expert Press in 2014 and written by Victor E. Sower, professor emeritus of operations management at Sam Houston State University. The book provides a conceptual approach to using statistical process control (SPC) to inform and improve decision-making around business processes and quality improvement. The author reviews the basic methods of SPC and provides practical guidance for using specific tools. He incorporates real-world examples throughout the book and ends each chapter with a summary of key points, as well as questions for managers to ask when applying the concepts to their own organizations. Chapter 5, Advanced Control Charts for Variables (10 pages), expands on the concepts in the previous chapter by reviewing additional tools to use in specific process scenarios. The first tool is a delta control chart for short production runs that may not provide sufficient data samples. The second tool is an exponentially weighted moving average (EWMA) chart when facing a short-term variance. The third method is adapting X-bar charts, R-charts, S-charts, and delta charts when the sample size varies. For each method, the author provides a basic explanation of the tool and example of how to apply it in decision-making. There is a chart at the end of the chapter to guide how to select the appropriate method for the process.

Statistical Process Control for Managers is an eight-chapter book published by Business Expert Press in 2014 and written by Victor E. Sower, professor emeritus of operations management at Sam Houston State University. The book provides a conceptual approach to using statistical process control (SPC) to inform and improve decision-making around business processes and quality improvement. The author reviews the basic methods of SPC and provides practical guidance for using specific tools. He incorporates real-world examples throughout the book and ends each chapter with a summary of key points, as well as questions for managers to ask when applying the concepts to their own organizations. Chapter 6, Control Charts for Attributes (13 pages), looks at methods for measuring go/no-go or count information such as the number of defective units overall, or number of customer complaints received. The author compares and contrasts four methods to use depending on what is being counted, defective products or defects in products. First, he looks at the utility of the proportion defective control chart (p-chart) and number-defective control chart (np-chart), reviewing the pros and cons for each. Second, he offers a similar analysis of the count chart (c-chart) and count chart per unit, (u-chart). There is a chart at the end of the chapter to guide how to select the appropriate method for the process.

Statistical Process Control for Managers is an eight-chapter book published by Business Expert Press in 2014 and written by Victor E. Sower, professor emeritus of operations management at Sam Houston State University. The book provides a conceptual approach to using statistical process control (SPC) to inform and improve decision-making around business processes and quality improvement. The author reviews the basic methods of SPC and provides practical guidance for using specific tools. He incorporates real-world examples throughout the book and ends each chapter with a summary of key points, as well as questions for managers to ask when applying the concepts to their own organizations. In Chapter 7, Process Capability (14 pages), the author explores methods for process improvement depending on whether there is a specified target value. He considers the importance of both process control and capability, and reviews measurement methods for both variable and attribute data. He looks at appropriate uses of process capability indices and process indices, with examples for both double-sided and single-sided specifications. He also examines adaptations for using process capability with non-normal Distributions. He reviews the methods for measuring attribute data, such as PPM and sigma notation.

Statistical Process Control for Managers is an eight-chapter book published by Business Expert Press in 2014 and written by Victor E. Sower, professor emeritus of operations management at Sam Houston State University. The book provides a conceptual approach to using statistical process control (SPC) to inform and improve decision-making around business processes and quality improvement. The author reviews the basic methods of SPC and provides practical guidance for using specific tools. He incorporates real-world examples throughout the book and ends each chapter with a summary of key points, as well as questions for managers to ask when applying the concepts to their own organizations. Chapter 8, SPC in Service Industries (18 pages), considers the differences in using SPC in the service industry rather than manufacturing. The author explains the challenges in assessing service quality control and the fact that there are no universal standards. He provides guidance on how to asses a service scenario and, thus determine which control chart(s) to use. He provides real-world examples from hospitals, retail, and finance.