Better Governance Across the Board is a practical guide for achieving good corporate governance of organizations regardless of whether they are for profit, listed, state-owned, family owned, or widely held. It delves into the questions boards must ask if they are to fulfill their fiduciary duties, taking account of regulatory issues. Part 1 defines corporate governance, explaining the four reasons why it matters and how it applies to a wide range of organizations. Part 2 explores the "Five P" framework of Purpose, Principles, Power, People, and Processes that helps boards to create sustainable value. Part 3 concludes by showing how the organization's long-term "license to operate" is achieved by boards focusing on the three most important assets of the organization: its reputation; its people, and its processes. This book explores the dilemmas that currently exist in modern approaches to corporate governance and suggests ways of overcoming them. Based on ten years of teaching more than 1,500 directors of publicly listed companies, it integrates key principles of leadership, ethics, branding, and governance into a unique five-factor framework to help directors make good decisions in strategy, risk management, succession planning, internal controls, and stakeholder engagement.

The tools needed to make a better, more informed decision.

Decision analysis (DA) is the logic of making a decision using quantitative models of the decider's factual and value judgments. DA is already widely used in business, government, medicine, economics, law, and science. However, most resources present only the logic and models rather than demonstrating how these methods can be effectively applied to the real world. This book offers an innovative approach to decision analysis by focusing on decision-making tools that can be utilized immediately to make better, more informed decisions. It uses no mathematics beyond arithmetic.

Examining how deciders think about their choices, this book provides problem-solving techniques that not only reflect sound modeling but also meet other essential requirements: they build on the thinking and knowledge that deciders already possess; they provide knowledge in a form that people are able and willing to provide; they produce results that the decider can use; and they are based on intimate and continuous interactions with the decider. The methods outlined in this text take into account such factors as the use, the user, the organization, available data, and subjective knowledge.

Replete with exercises, case studies, and observations from the author's own extensive consulting experience, the book quickly engages readers and enables them to master decision analysis by doing rather than by simply reading. Using familiar situations, it demonstrates how to handle knowledge as it unfolds in the real world. A term project is presented in the final chapter, in which readers can select an actual decision-making problem and apply their newfound tools to prepare a recommendation. A sample report is provided in the appendix.

Beginning with qualitative structuring, the text advances to sophisticated quantitative skills that can be applied in both public and private enterprise, including:

- Modeling decision-making under conditions of uncertainty or multiple objectives

- Risk analysis and assessment

- Communicating and justifying controversial decisions

- Personal life choices and political judgments

- Adapting decision aid to organizations

The book's broad applicability makes it an excellent resource for any organization or as a textbook for decision-making courses in a variety of fields, including public policy, business management, systems engineering and general education.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department (email ialine@wiley.com) or directly from rexvbrown@aol.com.

This is the state-of-the-art, international handbook for a field of inquiry that is still emergent and yet occupies a central position in contemporary management and organization theory. Mark Easterby-Smith and Marjorie Lyles have drawn together in their authoritative reference work original essays from the leading scholars in organizational learning and knowledge management around the world.

Not least in importance is the linkage they make between these two adjacent areas: learning and knowledge are often debated separately despite their close relationship. In this volume leading scholars from the fields of organizational learning, the learning organization, knowledge management and organizational knowledge, examine the issues and debates, as well as the processes and management implications, that are key to each of these approaches. The resulting set of essays offers researchers and students an invaluable guide.

Tracing the roots of learning and knowledge debates across the disciplines of economics, psychology, and social theory, and charting the key contributions scholars have made, this is a major, in-depth overview which all scholars of organizational learning and knowledge management will need on their shelves.

"Advances in Business and Management Forecasting" is a blind refereed serial publication published on an annual basis. The objective of this research annual is to present state-of-the-art studies in the application of forecasting methodologies to such areas as sales, marketing, and strategic decision making. (An accurate, robust forecast is critical to effective decision making.) It is the hope and direction of the research annual to become an applications and practitioner-oriented publication. The topics will normally include sales and marketing, forecasting, new product forecasting, judgmentally-based forecasting, the application of surveys to forecasting, forecasting for strategic business decisions, improvements in forecasting accuracy, and sales response models. It is both the hope and direction of the editorial board to stimulate the interest of the practitioners of forecasting to methods and techniques that are relevant.

A tried and tested formula for business planning What is the one thing you need to know in business? What s the single most important aspect of business to master in order to succeed and grow? It has to be planning. Whether you re sitting down to plan a whole brand strategy or tasked with planning a single product and taking it to market, nailing the planning and decision making will ensure you have full buy-in from all stakeholders, a high level of market knowledge, know exactly what value your product or service brings and a thorough understanding of how the financials will work. In short, you ll have an idea that succeeds. Ross Lovelock and his company SCQuARE have spent the last 20 years developing a formula for such planning. Ross has shared this formula with some of the world s leading companies now he s going to share it with you. The One Thing You Need to Know is a complete business planning toolkit. * A simple, implementable explanation of how to bring a product plan or a brand strategy together * Will teach you the critical business skill of creating and selling plans * Learn how to think through a complex business problem, create the right solution and then sell it through the corporate maze * Explains exactly how to distil vast amounts of information into a compelling business story that will warrant a YES decision from the boss

The future of work is already here. Customers are adopting disruptive technologies faster than your company can adapt. When your customers are delighted, they can amplify your message in ways that were never before possible. But when your company's performance runs short of what you've promised, customers can seize control of your brand message, spreading their disappointment and frustration faster than you can keep up. To keep pace with today's connected customers, your company must become a connected company. That means deeply engaging with workers, partners, and customers, changing how work is done, how you measure success, and how performance is rewarded. It requires a new way of thinking about your company: less like a machine to be controlled, and more like a complex, dynamic system that can learn and adapt over time. Connected companies have the advantage, because they learn and move faster than their competitors. While others work in isolation, they link into rich networks of possibility and expand their influence. Connected companies around the world are aggressively acquiring customers and disrupting the competition. In The Connected Company, we examine what they're doing, how they're doing it, and why it works. And we show you how your company can use the same principles to adapt - and thrive - in today's ever-changing global marketplace.

Doug Hall shares data-proven methods that can make sales, marketing, and business development measurably more effective.

This book deals with complex problems in the fields of logistics and supply chain management and discusses advanced methods, especially from the field of computational intelligence (CI), for solving them. The first two chapters provide general introductions to logistics and supply chain management on the one hand, and to computational intelligence on the other hand. The subsequent chapters cover specific fields in logistics and supply chain management, work out the most relevant problems found in those fields, and discuss approaches for solving them. Chapter 3 discusses problems in the field of production and inventory management. Chapter 4 considers planning activities on a finer level of granularity which is usually denoted as scheduling. In chapter 5 problems in transportation planning such as different types of vehicle routing problems are considered. While chapters 3 to 5 rather discuss planning problems which appear on an operative level, chapter 6 discusses the strategic problem of designing a supply chain or network. The final chapter provides an overview of academic and commercial software and information systems for the discussed applications. There appears to be a gap between general textbooks on logistics and supply chain management and more specialized literature dealing with methods for computational intelligence, operations research, etc., for solving the complex operational problems in these fields. For readers, it is often difficult to proceed from introductory texts on logistics and supply chain management to the sophisticated literature which deals with the usage of advanced methods. This book fills this gap by providing state-of-the-art descriptions of the corresponding problems and suitable methods for solving them.

This book offers a thorough and systematic introduction to the modified failure mode and effect analysis (FMEA) models based on uncertainty theories (e.g. fuzzy logic, intuitionistic fuzzy sets, D numbers and 2-tuple linguistic variables) and various multi-criteria decision making (MCDM) approaches such as distance-based MCDM, compromise ranking MCDM and hybrid MCDM, etc. As such, it provides essential FMEA methods and practical examples that can be considered in applying FMEA to enhance the reliability and safety of products and services. The book offers a valuable guide for practitioners and researchers working in the fields of quality management, decision making, information science, management science, engineering, etc. It can also be used as a textbook for postgraduate and senior undergraduate students.

This book lays the foundations for quality modeling and analysis in the context of supply chains through a synthesis of the economics, operations management, as well as operations research/management science literature on quality. The reality of today's supply chain networks, given their global reach from sourcing locations to points of demand, is further challenged by such issues as the growth in outsourcing as well as the information asymmetry associated with what producers know about the quality of their products and what consumers know. Although much of the related literature has focused on the micro aspects of supply chain networks, considering two or three decision-makers, it is essential to capture the scale of supply chain networks in a holistic manner that occurs in practice in order to be able to evaluate and analyze the competition and the impacts on supply chain quality in a quantifiable manner. This volume provides an overview of the fundamental methodologies utilized in this book, including optimization theory, game theory, variational inequality theory, and projected dynamical systems theory. It then focuses on major issues in today's supply chains with respect to quality, beginning with information asymmetry, followed by product differentiation and branding, the outsourcing of production, from components to final products, to quality in freight service provision. The book is filled with numerous real-life examples in order to emphasize the generality and pragmatism of the models and tools. The novelty of the framework lies in a network economics perspective through which the authors identify the underlying network structure of the various supply chains, coupled with the behavior of the decision-makers, ranging from suppliers and manufacturers to freight service providers. What is meant by quality is rigorously defined and quantified. The authors explore the underlying dynamics associated with the competitive processes along with the equilibrium solutions. As appropriate, the supply chain decision-makers compete in terms of quantity and quality, or in price and quality. The relevance of the various models that are developed to specific industrial sectors, including pharmaceuticals and high technology products, is clearly made. Qualitative analyses are provided, along with effective, and, easy to implement, computational procedures. Finally, the impacts of policy interventions, in the form of minimum quality standards, and their ramifications, in terms of product prices, quality levels, as well as profits are explored. The book is filled with many network figures, graphs, and tables with data.

Dieser erste von zwei Sammelbanden zur Bestandsaufnahme von betriebswirtschaftlicher Frauen- und Geschlechterforschung bietet einen Einblick in die Prozesse der Geschlechter(re)produktion der Betriebswirtschaftslehre auf theoretischkonzeptioneller Ebene. Die 10 Beitrage dieses Buches zeigen auf, welche Konstruktions- und Produktionprozesse sowie Reproduktions- und Dekonstruktionsprozesse in den betriebswirtschaftlichen Teildisziplinen Geschlechter diskursiv reproduzieren und damit einhergehend Reprasentationen von Geschlechtern fur die betriebswirtschaftliche Disziplin gestalten.

This volume presents advanced techniques to modeling markets, with a wide spectrum of topics, including advanced individual demand models, time series analysis, state space models, spatial models, structural models, mediation, models that specify competition and diffusion models. It is intended as a follow-on and companion to Modeling Markets (2015), in which the authors presented the basics of modeling markets along the classical steps of the model building process: specification, data collection, estimation, validation and implementation. This volume builds on the concepts presented in Modeling Markets with an emphasis on advanced methods that are used to specify, estimate and validate marketing models, including structural equation models, partial least squares, mixture models, and hidden Markov models, as well as generalized methods of moments, Bayesian analysis, non/semi-parametric estimation and endogeneity issues. Specific attention is given to big data. The market environment is changing rapidly and constantly. Models that provide information about the sensitivity of market behavior to marketing activities such as advertising, pricing, promotions and distribution are now routinely used by managers for the identification of changes in marketing programs that can improve brand performance. In today's environment of information overload, the challenge is to make sense of the data that is being provided globally, in real time, from thousands of sources. Although marketing models are now widely accepted, the quality of the marketing decisions is critically dependent upon the quality of the models on which those decisions are based. This volume provides an authoritative and comprehensive review, with each chapter including: * an introduction to the method/methodology * a numerical example/application in marketing * references to other marketing applications * suggestions about software. Featuring contributions from top authors in the field, this volume will explore current and future aspects of modeling markets, providing relevant and timely research and techniques to scientists, researchers, students, academics and practitioners in marketing, management and economics.

"Applications of Management Science" is a blind refereed serial publication published on an annual basis. The objective of this research annual is to present state-of-the-art studies in the application of management science to the solution of significant managerial decision-making problems. It significantly aids the dissemination of actual applications of management science in both the public and the private sectors. Volume 14 is directed toward the application of management science to multi-criteria decision making, Data Envelopment Analysis (DEA) and financial performance analyses. This volume is arranged in three sections. The first section focuses on multi-criteria decision making; the second focus is on the application of DEA to public schools, paper mills, nursing home quality, retailing, health care services, and performance efficiencies in cities. The third section focuses on multi-dimensional performance of a national stock market and the effect of organizational structure on micro-financial institutions. This volume will prove to be most valuable to those interested in financial performance measurements, productivity measurement and analysis, and management science, both as practitioners and researchers.

Action Learning - Activity Based Costing - Adhocracy - Agility - Balanced Scorecard - Benchmarking - Boston Matrix - Broadbanding - Channel Management - Core Competencies - Core Values - Crisis Management - Customer Relationship Management - Decision Theory - Discounted Cash Flow - Downsizing - E-commerce - Emotional Intelligence - Employability Empowerment - Four Ps of Marketing - Game Theory - Intellectual Capital Interim Management - Just-in-Time - Kaizen - Kepener-Tregoe - Knowledge Management - Leadership Theory - Lean Production - Learning Organization - Managerial Grid - Maslow's Hierarchy of Needs - Matrix Model Outsourcing - Porter's Five Forces - Psychological Contract Re-engineering - Relationship Marketing - Ringi - Scenario Planning - Scientific Management - Seven S Framework - Shamrock Organization - Shareholder Value - Strategic Inflection Points - Strategic Management Succession Planning - Supply Chain Management - Theories X Y (& Z) Thought Leadership - 60 Degree Feedback - TQM - Transnational Corporation - Value Innovation - Virtual Organization

This book develops and assesses a decision-making model for resource management in complex work systems in line with the "Systems Engineering" method. It applies the Balanced Scorecard to the development of the criteria system for decision-making, and employs fuzzy linguistics theory to evaluate the alternatives. Further, the book assesses the application of this model in a hospital that has to decide whether or not to outsource its sterile goods. The use of the model opens up a diverse range of fields for decision-making in the area of complex work systems.

Evidence-Based Decision-Making: How to Leverage Available Data and Avoid Cognitive Biases examines how a wide range of factual evidence, primarily derived from a variety of data available to organizations, can be used to improve the quality of business decision-making, by helping decision makers circumvent the various cognitive biases that adversely impact how we all think. The book is built on the following premise: During the past decade, the new 'data world' emerged, in which the rush to develop competencies around business analytics and data science can be characterized as nothing less than the new commercial arms race. The ever-expanding volume and variety of data are well known, as are the great advances in data processing/analytics, data visualization, and related information production-focused capabilities. Yet, comparatively little effort has been devoted to how the informational products of business analytics and data science are 'consumed' or used in the organizational decision-making processes, as the available evidence shows that only some of that information is used to drive some business decisions some of the time. Evidence-Based Decision-Making details an explicit process describing how the universe of available and applicable evidence, which includes organizational and other data, industry benchmarks, scientific studies, and professional experience, can be assessed, amalgamated, and funneled into an objective driver of key business decisions. Introducing key concepts in relation to data and evidence, and the history of evidence-based management, this new and extremely topical book will be essential reading for researchers and students of data analytics as well as those working in the private and public sectors, and in the voluntary sector.

In every decision problem there are things we know and things we do not know. Risk analysis science uses the best available evidence to assess what we know while it is carefully intentional in the way it addresses the importance of the things we do not know in the evaluation of decision choices and decision outcomes. The field of risk analysis science continues to expand and grow and the second edition of Principles of Risk Analysis: Decision Making Under Uncertainty responds to this evolution with several significant changes. The language has been updated and expanded throughout the text and the book features several new areas of expansion including five new chapters. The book's simple and straightforward style-based on the author's decades of experience as a risk analyst, trainer, and educator-strips away the mysterious aura that often accompanies risk analysis. Features: Details the tasks of risk management, risk assessment, and risk communication in a straightforward, conceptual manner Provides sufficient detail to empower professionals in any discipline to become risk practitioners Expands the risk management emphasis with a new chapter to serve private industry and a growing public sector interest in the growing practice of enterprise risk management Describes dozens of quantitative and qualitative risk assessment tools in a new chapter Practical guidance and ideas for using risk science to improve decisions and their outcomes is found in a new chapter on decision making under uncertainty Practical methods for helping risk professionals to tell their risk story are the focus of a new chapter Features an expanded set of examples of the risk process that demonstrate the growing applications of risk analysis As before, this book continues to appeal to professionals who want to learn and apply risk science in their own professions as well as students preparing for professional careers. This book remains a discipline free guide to the principles of risk analysis that is accessible to all interested practitioners. Files used in the creation of this book and additional exercises as well as a free student version of Palisade Corporation's Decision Tools Suite software are available with the purchase of this book. A less detailed introduction to the risk analysis science tasks of risk management, risk assessment, and risk communication is found in Primer of Risk Analysis: Decision Making Under Uncertainty, Second Edition, ISBN: 978-1-138-31228-9.

Making decisions is certainly the most important task managers are faced with, and it is often a very difficult one. This book offers a procedure for solving complex decision problems step by step. Unlike other texts, the book focuses on problem analysis, on developing potential solutions, and on establishing a decision-making matrix. In this fourth edition of the book, published under a new title, the authors present simplified, actionable guidelines that can be easily applied to the individual steps in the heuristic process. The book is intended for decision-makers at companies, non-profit organizations and in public administration whose work involves complex problems. It will also benefit students and participants in executive courses.

"Stafford Beer is undoubtedly among the world s most provocative, creative, and profound thinkers on the subject of management, and he records his thinking with a flair that is unmatched. His writing is as much art as it is science. He is the most viable system I know." Dr Russell L Ackoff, The Institute for Interactive Management, Pennsylvania, USA.
"If anyone can make it Operations Research] understandably readable and positively interesting it is Stafford Beer everyone in management ..should be grateful to him for using clear and at times elegant English and even elegant diagrams." The Economist
In Brain of the Firm and The Heart of Enterprise Stafford Beer worked out the scientific laws that govern any viable system. They constitute the basis for this book which is concerned solely with the application of those laws to the understanding of any particular enterprise. In the form of a Handbook or Manager s Guide, Diagnosing the System deals with the fundamental problem of management how to cope with complexity itself. It shows you how to design (or redesign) an enterprise in conformity with the laws of viability, and will help you to diagnose faults in your organizational structure.

Why is the Mona Lisa the most famous painting in the world? Why did Facebook succeed when other social networking sites failed? Did the surge in Iraq really lead to less violence? How much can CEO's impact the performance of their companies? And does higher pay incentivize people to work hard?
If you think the answers to these questions are a matter of common sense, think again. As sociologist and network science pioneer Duncan Watts explains in this provocative book, the explanations that we give for the outcomes that we observe in life--explanation that seem obvious once we know the answer--are less useful than they seem.
Drawing on the latest scientific research, along with a wealth of historical and contemporary examples, Watts shows how common sense reasoning and history conspire to mislead us into believing that we understand more about the world of human behavior than we do; and in turn, why attempts to predict, manage, or manipulate social and economic systems so often go awry.
It seems obvious, for example, that people respond to incentives; yet policy makers and managers alike frequently fail to anticipate how people will respond to the incentives they create. Social trends often seem to have been driven by certain influential people; yet marketers have been unable to identify these "influencers" in advance. And although successful products or companies always seem in retrospect to have succeeded because of their unique qualities, predicting the qualities of the next hit product or hot company is notoriously difficult even for experienced professionals.
Only by understanding how and when common sense fails, Watts argues, can we improve how we plan for the future, as well as understand the present--an argument that has important implications in politics, business, and marketing, as well as in science and everyday life.

Provides the reader with a perspective on the efficient operation of complicated systems.
* Spreadsheets are used to employ and teach techniques.
* Includes the facets of probability that relate to decision making.

"Operational Risk Management" offers peace of mind to business and government leaders who want their organizations to be ready for any contingency, no matter how extreme. This invaluable book is a preparatory resource for when times are good, and an emergency reference when times are bad. "Operational Risk Management" is destined to become every risk manager's ultimate weapon to help his or her organization survive ? no matter what.

Rooted in the study of chaos and complexity, Adaptive Action introduces a simple, common sense process that will guide you and your organization into reflective action. This elegant method prompts readers to engage with three deceptively simple questions: What? So what? Now what? The first leads to careful observation. The second invites you to thoughtfully consider options and implications. The third ignites effective action. Together, these questions and the tools that support them produce a dynamic and creative dance with uncertainty. The road-tested steps of adaptive action can be used to devise solutions and improve performance across multiple challenges, and they have proven to be scalable from individuals to work groups, from organizations to communities. In addition to laying out the adaptive action framework and clear protocols to support it, Glenda H. Eoyang and Royce J. Holladay introduce best practices from exemplary professionals who have used adaptive action to meet personal, professional, and political challenges in leadership, consulting, Alzheimer's treatment, evaluation, education reform, political advocacy, and cultural engagement-readying readers to employ this new toolkit to meet their own goals with a sense of ingenuity and flexibility.