"In this book, Peter Bogetoft - THE expert on the theory and practice of benchmarking - provides an in–depth yet very accessible and readable explanation of the best way to do benchmarking, starting from the ground up." Rick Antle William S. Beinecke Professor of Accounting, Yale School of Management CFO, Compensation Valuation, Inc. "I highly recommend this well-written and comprehensive book on measuring and managing performance. Dr. Bogetoft summarizes the fundamental mathematical concepts in an elegant, intuitive, and understandable way." Jon A. Chilingerian Professor, Brandeis University and INSEAD "Bogetoft gives in his book Performance Benchmarking an excellent introduction to the methodological basis of benchmarking." Christian Parbøl Director, DONG Energy "This book is the primer on benchmarking for performance management." Albert Birck Business Performance Manager, Maersk Oil "This excellent book provides a non technical introduction for performance management." Misja Mikkers, Director, Dutch Health Care Authority "With this very well written and comprehensive introduction to the many facets of benchmarking in hand, organizations have no excuse for not applying the best and cost effective benchmarking methods in their performance assessments." Stig P. Christensen Senior R&D Director, COWI

Use this in-depth guide to correctly design benchmarks, measure key performance metrics of .NET applications, and analyze results. This book presents dozens of case studies to help you understand complicated benchmarking topics. You will avoid common pitfalls, control the accuracy of your measurements, and improve performance of your software. Author Andrey Akinshin has maintained BenchmarkDotNet (the most popular .NET library for benchmarking) for five years and covers common mistakes that developers usually make in their benchmarks. This book includes not only .NET-specific content but also essential knowledge about performance measurements which can be applied to any language or platform (common benchmarking methodology, statistics, and low-level features of modern hardware). What You'll LearnBe aware of the best practices for writing benchmarks and performance testsAvoid the common benchmarking pitfalls Know the hardware and software factors that affect application performanceAnalyze performance measurements Who This Book Is For .NET developers concerned with the performance of their applications

Application-level monitoring of continuously operating software systems provides insights into their dynamic behavior, helping to maintain their performance and availability during runtime. Such monitoring may cause a significant runtime overhead to the monitored system, depending on the number and location of used instrumentation probes. In order to improve a system’s instrumentation and to reduce the caused monitoring overhead, it is necessary to know the performance impact of each probe. While many monitoring frameworks are claiming to have minimal impact on the performance, these claims are often not backed up with a detailed performance evaluation determining the actual cost of monitoring. Benchmarks can be used as an effective and affordable way for these evaluations. However, no benchmark specifically targeting the overhead of monitoring itself exists. Furthermore, no established benchmark engineering methodology exists that provides guidelines for the design, execution, and analysis of benchmarks. This thesis introduces a benchmark approach to measure the performance overhead of application-level monitoring frameworks. The core contributions of this approach are 1) a definition of common causes of monitoring overhead, 2) a general benchmark engineering methodology, 3) the MooBench micro-benchmark to measure and quantify causes of monitoring overhead, and 4) detailed performance evaluations of three different application-level monitoring frameworks. Extensive experiments demonstrate the feasibility and practicality of the approach and validate the benchmark results. The developed benchmark is available as open source software and the results of all experiments are available for download to facilitate further validation and replication of the results.

Computer and microprocessor architectures are advancing at an astounding pace. However, increasing demands on performance coupled with a wide variety of specialized operating environments act to slow this pace by complicating the performance evaluation process. Carefully balancing efficiency and accuracy is key to avoid slowdowns, and such a balance can be achieved with an in-depth understanding of the available evaluation methodologies. Performance Evaluation and Benchmarking outlines a variety of evaluation methods and benchmark suites, considering their strengths, weaknesses, and when each is appropriate to use. Following a general overview of important performance analysis techniques, the book surveys contemporary benchmark suites for specific areas, such as Java, embedded systems, CPUs, and Web servers. Subsequent chapters explain how to choose appropriate averages for reporting metrics and provide a detailed treatment of statistical methods, including a summary of statistics, how to apply statistical sampling for simulation, how to apply SimPoint, and a comprehensive overview of statistical simulation. The discussion then turns to benchmark subsetting methodologies and the fundamentals of analytical modeling, including queuing models and Petri nets. Three chapters devoted to hardware performance counters conclude the book. Supplying abundant illustrations, examples, and case studies, Performance Evaluation and Benchmarking offers a firm foundation in evaluation methods along with up-to-date techniques that are necessary to develop next-generation architectures.

Benchmarking applications such as competitive product testing, reverse engineering, competitive analysis, process benchmarking.

The scope of contemporary higher education is wide, and concerns about the performance of higher education systems are widespread. The number of young people with a higher education qualification is expected to surpass 300 million in OECD and G20 countries by 2030. Higher education systems are faced with challenges that include expanding access, containing costs, and ensuring the quality and relevance of provision. The project on benchmarking higher education system performance provides a comprehensive and empirically rich review of the higher education landscape across OECD countries, taking stock of how well they are performing in meeting their education, research and engagement responsibilities.

The author is one of the prominent researchers in the field of Data Envelopment Analysis (DEA), a powerful data analysis tool that can be used in performance evaluation and benchmarking. This book is based upon the author’s years of research and teaching experiences. It is difficult to evaluate an organization’s performance when multiple performance metrics are present. The difficulties are further enhanced when the relationships among the performance metrics are complex and involve unknown tradeoffs. This book introduces Data Envelopment Analysis (DEA) as a multiple-measure performance evaluation and benchmarking tool. The focus of performance evaluation and benchmarking is shifted from characterizing performance in terms of single measures to evaluating performance as a multidimensional systems perspective. Conventional and new DEA approaches are presented and discussed using Excel spreadsheets — one of the most effective ways to analyze and evaluate decision alternatives. The user can easily develop and customize new DEA models based upon these spreadsheets. DEA models and approaches are presented to deal with performance evaluation problems in a variety of contexts. For example, a context-dependent DEA measures the relative attractiveness of similar operations/processes/products. Sensitivity analysis techniques can be easily applied, and used to identify critical performance measures. Two-stage network efficiency models can be utilized to study performance of supply chain. DEA benchmarking models extend DEA’s ability in performance evaluation. Various cross efficiency approaches are presented to provide peer evaluation scores. This book also provides an easy-to-use DEA software — DEAFrontier. This DEAFrontier is an Add-In for Microsoft® Excel and provides a custom menu of DEA approaches. This version of DEAFrontier is for use with Excel 97-2013 under Windows and can solve up to 50 DMUs, subject to the capacity of Excel Solver. It is an extremely powerful tool that can assist decision-makers in benchmarking and analyzing complex operational performance issues in manufacturing organizations as well as evaluating processes in banking, retail, franchising, health care, public services and many other industries.

With growing demands for increased operational efficiency and process improvement in organizations of all sizes, more and more companies are turning to benchmarking as a means of setting goals and measuring performance against the products, services and practices of other organizations that are recognized as leaders. The Benchmarking Book is an indispensable guide to process improvement through benchmarking, providing managers, practitioners and consultants with all the information needed to carry out effective benchmarking studies. Covering everything from essential theory to important considerations such as project management and legal issues, The Benchmarking Book is the ideal step-by-step guide to assessing and improving your company’s processes and performance through benchmarking.

This new edition continues to emphasize the use of data envelopment analysis (DEA) to create optimization-based benchmarks within hospitals, physician group practices, health maintenance organizations, nursing homes and other health care delivery organizations. Suitable for graduate students learning DEA applications in health care as well as for practicing administrators, it is divided into two sections covering methods and applications. Section I considers efficiency evaluations using DEA; returns to scale; weight restricted (multiplier) models; non-oriented or slack-based models, including in this edition two versions of non-controllable variable models and categorical variable models; longitudinal (panel) evaluations and the effectiveness dimension of performance evaluation. A new chapter then looks at new and advanced models of DEA, including super-efficiency, congestion DEA, network DEA, and dynamic network models. Mathematical formulations of various DEA models are placed in end-of-chapter appendices. Section II then looks at health care applications within particular settings, chapter-by-chapter, including hospitals, physician practices, nursing homes and health maintenance organizations (HMOs). Other chapters then explore home health care and home health agencies; dialysis centers, community mental health centers, community-based your services, organ procurement organizations, aging agencies and dental providers; DEA models to evaluate provider performance for specific treatments, including stroke, mechanical ventilation and perioperative services. A new chapter then examines international-country-based applications of DEA in health care in 16 different countries, along with OECD and multi-country studies. Most of the existing chapters in this section were expanded with recent applications. Included with the book is online access to a learning version of DEA Solver software, written by Professor Kaoru Tone, which can solve up to 50 DMUs for various DEA models listed in the User’s Guide at the end of the book.

A pioneer of the benchmarking movement shows managers how this revolutionary process can improve company performance at every level. This book goes beyond the simple "how to" of the process to show managers exactly how benchmarking fits into long-term strategic planning. Watson is a quality executive with Xerox and one of the pioneers in benchmarking.