個案總覽

Supply Chain Information Technology, Second Edition, is a seven-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author provides tools to evaluate, select, and coordinate systems for supply chain management (SCM). He reviews fundamental elements of different supply chain systems and provides tools for determining the type of system that will best fit a business process. The second edition includes new and updated examples. In Chapter 4, Business Process Reengineering in Supply Chains (11 pages), the author examines the role of business process reengineering (BRP) in an ERP system. He outlines the business process, dividing it into two categories: operational (business functions) and infrastructural (administrative). He explains how BPR identifies best practices and discusses the value of benchmarking with peer groups. He highlights two methods for implementing process reengineering, clean slate and technology-enabled, and compares the advantages of each method. He provides post-audit analysis of a large manufacturing company's SCM software implementation as an example of BPR.

Supply Chain Information Technology, Second Edition, is a seven-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author provides tools to evaluate, select, and coordinate systems for supply chain management (SCM). He reviews fundamental elements of different supply chain systems and provides tools for determining the type of system that will best fit a business process. The second edition includes new and updated examples. In Chapter 5, System Selection (20 pages), the author highlights the need to build a business case when selecting SCM software. He presents tools for basic financial analysis such as total cost of ownership, cost benefit analysis, and net present value. He also explains the limitations of these tools and suggests that most businesses need to use multiple objective analysis that incorporate both short- and long-term factors such as maintenance and quality. He illustrates methods such as SMART and value analysis with a short business case, Enterprise Resource Planning System Evaluation by Toroid International Ltd.

Supply Chain Information Technology, Second Edition, is a seven-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author provides tools to evaluate, select, and coordinate systems for supply chain management (SCM). He reviews fundamental elements of different supply chain systems and provides tools for determining the type of system that will best fit a business process. The second edition includes new and updated examples. Chapter 6, Supply Chain Software Installation Project Management (18 pages), the author reviews criteria for the successful implementation of a new system. He argues that the project manager has the most influence the ultimate success of the installation. He outlines three general approaches based on timing and location of the installation: pilot implementation approach, Big Bang implementation approach, and the phased implementation approach. He provides steps to manage risk involved in the transition to a new system. He demonstrates project management by outlining a critical path model (CPM) and two visual representations: a network and Gantt chart, as well as early and late start schedules. To further demonstrate the challenges of SCM installation, he provides a business case, Enterprise Resource Planning Project Problems in Nevada Department of Motor Vehicles.

Supply Chain Information Technology, Second Edition, is a seven-chapter book published by Business Expert Press in 2014 and written by David L. Olson, James & H. K. Stuart Professor in Management Information Systems and Chancellor's Professor at the University of Nebraska. In this book, the author provides tools to evaluate, select, and coordinate systems for supply chain management (SCM). He reviews fundamental elements of different supply chain systems and provides tools for determining the type of system that will best fit a business process. The second edition includes new and updated examples. In Chapter 7, Recapitulation (9 pages), the author discusses issues involved in implementing SCM systems. First, he explains the need for training as part of any transition to a new system, with a focus on both how to use the system as well as the business process that the system supports. He mentioned common problems in training and suggests several training methods. Second, he explains why systems are updated an outlines several benefits. Third, he outlines several common system add-ons, such as a customer relationship management module. He also looks at the considerations for green SCM.

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.

By 2013, Google, while not a traditional manufacturer of automobiles, had invested millions of dollars in its self-driving cars which had logged over 500,000 miles of testing. The Google management team faced several questions. Should Google continue to invest in the technology behind self-driving cars? How could Google's core software-based and search business benefit from self-driving car technology? As large auto manufacturers began to invest in automotive technology themselves, could Google compete? Was this investment of time and resources worth it for Google?

This is an MIT Sloan Management Review article. Effective collaboration on logistics can move mountains -and reduce emissions.

What makes such partnerships -which the author calls adaptive strategic partnerships -counterintuitive is that they are being used in situations where the two most relevant streams of organizational economics would argue for vertical integration. One company that has pursued adaptive strategic partnerships is Bharti Airtel Ltd., the Indian telecommunications services company. Back in 2004, Bharti Airtel's managers found that negotiating and updating contracts with vendors interfered with their ability to focus on satisfying the company's customers and outsmarting its competition. Contrary to what other telecom operators have done, it negotiated unconventional relationships with some of its leading vendors, including Nokia Siemens Networks (now Nokia Solutions and Networks), Ericsson and IBM. Instead of expanding network infrastructure by purchasing increasing amounts of equipment (such as exchanges and cellular antennas), which often results in unused capacity, Bharti Airtel pays the vendors to operate the network; it compensates them based on telecom volume, paying only when equipment is in use. In addition to rethinking its approach to network capacity, vendors take responsibility for network performance and troubleshooting. Typically, companies with outside partners rely on simple tools such as service-level agreements, which specify what is expected from each party and provide for performance standards to assess compliance. But in managing its partnerships with vendors, Bharti Airtel uses a joint governing structure that encourages people at different levels of the organizations to communicate and address problems as they arise. In some cases, such interactions have led the company and its partners to redraw the scope of their collaborations (for example, assign responsibility for building and maintaining the cell towers to a new company), something that would be more difficult to do in a more traditional partnership.

Traditional methods of managing supply chain risk require estimations of how likely a disruption is to occur. For fairly common risks--poor supplier performance, forecast errors, transportation breakdowns--the traditional methods work quite well. But it's a different story for rare, high-impact events such as megadisasters, pandemics, and political upheavals. These risks are hard to quantify using traditional models, and as a result, many companies do not adequately prepare for them, which can have calamitous consequences when catastrophes do strike. A new model allows managers to quantify the "impact" of a supply chain disruption on a company's operational and financial performance, rather than focusing on the "cause" or "likelihood" of the disruption. This type of analysis obviates the need to determine the probability of any specific risk's occurring--a valid approach since the mitigation strategies are equally effective regardless of what caused the disruption. In this article, the authors describe how companies can use the model to reduce their exposure to all types of supply chain risk.

The supply chain director of Indo-Euro Pharma summoned an urgent meeting in response to significant losses incurred by the company in the last fiscal year. This was primarily due to the return of yet another international consignment of temperature-sensitive drugs (TSDs) - this time worth millions of dollars. The meeting focused on the inability of Indo-Euro Pharma to appropriately distribute and monitor TSDs cost effectively across the various stages and locations of the supply chain - especially at the pharmacist level. Deviations from drugs' required temperature ranges could happen during packaging, storage, transport, loading and unloading in aircraft, sea containers, trucks, etc. It was extremely difficult to monitor whether pharmacists were following proper procedures for storing TSDs. Most medical stores in India had domestic refrigerators that required frequent calibration. The problems indicated the need for Indo-Euro Pharma to adopt an alternative distribution system that was specifically tailored for TSDs.

The supply chain director of Indo-Euro Pharma summoned an urgent meeting in response to significant losses incurred by the company in the last fiscal year. This was primarily due to the return of yet another international consignment of temperature-sensitive drugs (TSDs) — this time worth millions of dollars. The meeting focused on the inability of Indo-Euro Pharma to appropriately distribute and monitor TSDs cost effectively across the various stages and locations of the supply chain — especially at the pharmacist level. Deviations from drugs’ required temperature ranges could happen during packaging, storage, transport, loading and unloading in aircraft, sea containers, trucks, etc. It was extremely difficult to monitor whether pharmacists were following proper procedures for storing TSDs. Most medical stores in India had domestic refrigerators that required frequent calibration. The problems indicated the need for Indo-Euro Pharma to adopt an alternative distribution system that was specifically tailored for TSDs.

This reading provides an introduction to forecasting methods. It includes a brief summary of methods based on judgment and a longer section on quantitative analysis. It also provides sample data so readers can develop an understanding of concepts such as correlation, covariance, time-series data, moving averages, exponential smoothing, time-series decomposition, trend estimation, simple linear regression, autocorrelation, and multiple linear regression.

Supplements the (A) case