Strategic Decisions and Weak Signals. Anticipation for Decision-Making

The expression «We did not see it coming!» has often been heard in recent years from decision makers at the highest levels of the private and public sectors. Yet there were actually early warning signals, but they were often ignored due to a lack of appropriate methodology. Focusing on the concept of a weak signal, this book provides methods for anticipating problems and dealing with blind spots. Along with examples of this concept, the authors provide answers to questions of feasibility, including how to recognize a weak signal, and how to exploit it. Numerous applications are also presented throughout.

Finance for Strategic Decision Making demystifies and clarifies for non-financial executives the basics of financial analysis. It shows how they can make important financial decisions that can critically enhance their institution’s ability to respond to competitive challenges, undertake new projects, overcome financial setbacks, and most importantly, create shareholder value. Written by M. P. Narayanan and Vikram K. Nanda—two of the country’s leading authorities on financial strategy—this book offers a practical guide for using financial analysis to enhance strategicdecision making. The book includes a coherent framework that outlines practical and intellectually sound guidance for executives who must make strategic decisions. Finance for Strategic Decision Making Explains the role of finance in corporate strategy Offers guidance on resource allocation decisions Explores how to determine the right balance of debt and equity capital to maximize firm value Demonstrates how to use payout policy as a strategic tool Clarifies if a merger, acquisition, or divestiture is in the best interest of an organization Shows how to manage risk Reveals how to measure value created and the effectiveness of upper level management

Vital Notes for Nurses: Professional Development, Reflection and Decision-making provides a concise, accessible introduction to professional development, reflective practice and clinical decision-making. Vital Notes for Nurses: Professional Development, Reflection and Decision-making explores the core strategies of reflective practice and decision-making underlying professional nursing development. Separate chapters on reflective writing, evidence-based practice, clinical supervision and portfolios demonstrate the inter-relationship between professional development and professional practice. It is aimed at both student and qualified nurses, recognising that professional development is a life-long commitment. It provides clear guidance to help practitioners think critically about their actions, work within professional boundaries, be accountable for their actions and plan for their future. * Provides a concise introduction to professional development, reflective practice, and clinical decision-making * Written in a clear accessible style which assumes no prior knowledge * Enables students to consider and develop their practice in order to become competent practitioners * Each chapter includes learning objectives, scenarios and case studies * In the Vital Notes for Nurses series

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify trends and profiles, allowing, for example, retailers to discover patterns on which to base marketing objectives. This book looks at both classical and recent techniques of data mining, such as clustering, discriminant analysis, logistic regression, generalized linear models, regularized regression, PLS regression, decision trees, neural networks, support vector machines, Vapnik theory, naive Bayesian classifier, ensemble learning and detection of association rules. They are discussed along with illustrative examples throughout the book to explain the theory of these methods, as well as their strengths and limitations. Key Features: Presents a comprehensive introduction to all techniques used in data mining and statistical learning, from classical to latest techniques. Starts from basic principles up to advanced concepts. Includes many step-by-step examples with the main software (R, SAS, IBM SPSS) as well as a thorough discussion and comparison of those software. Gives practical tips for data mining implementation to solve real world problems. Looks at a range of tools and applications, such as association rules, web mining and text mining, with a special focus on credit scoring. Supported by an accompanying website hosting datasets and user analysis. Statisticians and business intelligence analysts, students as well as computer science, biology, marketing and financial risk professionals in both commercial and government organizations across all business and industry sectors will benefit from this book.

Decision-making has evolved recently thanks to the introduction of information and communication technologies in many organizations, which has led to new kinds of decision-making processes, called “collaborative decision-making”, at the organizational and cognitive levels. This book looks at the development of the decision-making process in organizations. Decision-aiding and its paradigm of problem solving are defined, showing how decision-makers now need to work in a cooperative way. Definitions of cooperation and associated concepts such as collaboration and coordination are given and a framework of cooperative decision support systems is presented, including intelligent DSS, cooperative knowledge-based systems, workflow, group support systems, collaborative engineering, integrating with a collaborative decision-making model in part or being part of global projects. Several models and experimental studies are also included showing that these new processes have to be supported by new types of tools, several of which are described in order to calculate or simulate solutions or global solutions for decision-making modification. Definitions and new trends for these models are given, along with types of systems. Contents 1. Alteration of Decision-Making Processes in Organizations. 2. New Decision-Making Processes. 3. The Need to Cooperate. 4. Cooperative Decision-Making. 5. Activity Support Systems. 6. Cooperative Decision Support Systems: CDSSS. About the Authors Pascale Zarat? is Professor at Toulouse 1 Capitole University, France. She conducts her research at the IRIT Laboratory and is the Editor-in-Chief of the International Journal of Decision Support Systems Technologies. She is co-chair of the European Working Group on DSS and has published several studies and books.

The only book to combine emergency management principLEs with proven military concepts Good disaster plans do not guarantee a good response. Any disaster plan rarely survives the first rain bands of a hurricane or the first tremors of an earthquake. While developing plans is essential, there must be systems in place to adapt these plans to the ever-changing operational environment of a disaster. Currently there is no set of standard disaster response principles to guide a community. The National Incident Management System (NIMS) and the Incident Command System (ICS) provide the framework to implement operational decisions, but they were never designed as operational concepts. The military has developed just such concepts and many of them can be adapted for civilian use. Disaster Operations and Decision Making adapts those military concepts and combines them with disaster lessons learned to create a new opera-tional paradigm. Emphasizing team building, Emergency Operations Center operational systems, and situational awareness, the book details easily adopted methods. All of these methods are designed to be incorporated into the NIMS and ICS framework to enhance a community's response to any type of disaster. Disaster Operations and Decision Making is an essential resource for emergency managers, fire chiefs, law enforcement officers, homeland security professionals, public health officials, and anyone else involved or interested in crisis management.

IIE/Joint Publishers Book of the Year Award 2016! Awarded for ‘an outstanding published book that focuses on a facet of industrial engineering, improves education, or furthers the profession’. Engineering Decision Making and Risk Management emphasizes practical issues and examples of decision making with applications in engineering design and management Featuring a blend of theoretical and analytical aspects, this book presents multiple perspectives on decision making to better understand and improve risk management processes and decision-making systems. Engineering Decision Making and Risk Management uniquely presents and discusses three perspectives on decision making: problem solving, the decision-making process, and decision-making systems. The author highlights formal techniques for group decision making and game theory and includes numerical examples to compare and contrast different quantitative techniques. The importance of initially selecting the most appropriate decision-making process is emphasized through practical examples and applications that illustrate a variety of useful processes. Presenting an approach for modeling and improving decision-making systems, Engineering Decision Making and Risk Management also features: Theoretically sound and practical tools for decision making under uncertainty, multi-criteria decision making, group decision making, the value of information, and risk management Practical examples from both historical and current events that illustrate both good and bad decision making and risk management processes End-of-chapter exercises for readers to apply specific learning objectives and practice relevant skills A supplementary website with instructional support material, including worked solutions to the exercises, lesson plans, in-class activities, slides, and spreadsheets An excellent textbook for upper-undergraduate and graduate students, Engineering Decision Making and Risk Management is appropriate for courses on decision analysis, decision making, and risk management within the fields of engineering design, operations research, business and management science, and industrial and systems engineering. The book is also an ideal reference for academics and practitioners in business and management science, operations research, engineering design, systems engineering, applied mathematics, and statistics.

A practical guide to network meta-analysis with examples and code In the evaluation of healthcare, rigorous methods of quantitative assessment are necessary to establish which interventions are effective and cost-effective. Often a single study will not provide the answers and it is desirable to synthesise evidence from multiple sources, usually randomised controlled trials. This book takes an approach to evidence synthesis that is specifically intended for decision making when there are two or more treatment alternatives being evaluated, and assumes that the purpose of every synthesis is to answer the question “for this pre-identified population of patients, which treatment is ‘best’?” A comprehensive, coherent framework for network meta-analysis (mixed treatment comparisons) is adopted and estimated using Bayesian Markov Chain Monte Carlo methods implemented in the freely available software WinBUGS. Each chapter contains worked examples, exercises, solutions and code that may be adapted by readers to apply to their own analyses. This book can be used as an introduction to evidence synthesis and network meta-analysis, its key properties and policy implications. Examples and advanced methods are also presented for the more experienced reader. Methods used throughout this book can be applied consistently: model critique and checking for evidence consistency are emphasised. Methods are based on technical support documents produced for NICE Decision Support Unit, which support the NICE Methods of Technology Appraisal. Code presented is also the basis for the code used by the ISPOR Task Force on Indirect Comparisons. Includes extensive carefully worked examples, with thorough explanations of how to set out data for use in WinBUGS and how to interpret the output. Network Meta-Analysis for Decision Making will be of interest to decision makers, medical statisticians, health economists, and anyone involved in Health Technology Assessment including the pharmaceutical industry.

Medical Decision Making provides clinicians with a powerful framework for helping patients make decisions that increase the likelihood that they will have the outcomes that are most consistent with their preferences. This new edition provides a thorough understanding of the key decision making infrastructure of clinical practice and explains the principles of medical decision making both for individual patients and the wider health care arena. It shows how to make the best clinical decisions based on the available evidence and how to use clinical guidelines and decision support systems in electronic medical records to shape practice guidelines and policies. Medical Decision Making is a valuable resource for all experienced and learning clinicians who wish to fully understand and apply decision modelling, enhance their practice and improve patient outcomes. “There is little doubt that in the future many clinical analyses will be based on the methods described in Medical Decision Making, and the book provides a basis for a critical appraisal of such policies.” – Jerome P. Kassirer M.D., Distinguished Professor, Tufts University School of Medicine, US and Visiting Professor, Stanford Medical School, US

This book outlines the creative process of making environmental management decisions using the approach called Structured Decision Making. It is a short introductory guide to this popular form of decision making and is aimed at environmental managers and scientists. This is a distinctly pragmatic label given to ways for helping individuals and groups think through tough multidimensional choices characterized by uncertain science, diverse stakeholders, and difficult tradeoffs. This is the everyday reality of environmental management, yet many important decisions currently are made on an ad hoc basis that lacks a solid value-based foundation, ignores key information, and results in selection of an inferior alternative. Making progress – in a way that is rigorous, inclusive, defensible and transparent – requires combining analytical methods drawn from the decision sciences and applied ecology with deliberative insights from cognitive psychology, facilitation and negotiation. The authors review key methods and discuss case-study examples based in their experiences in communities, boardrooms, and stakeholder meetings. The goal of this book is to lay out a compelling guide that will change how you think about making environmental decisions. Visit www.wiley.com/go/gregory/sdm to access the figures and tables from the book.