Decision Management

"A very rich book sprinkled with real-life examples as well as battle-tested advice.” —Pierre Haren, VP ILOG, IBM "James does a thorough job of explaining Decision Management Systems as enablers of a formidable business transformation.” —Deepak Advani, Vice President, Business Analytics Products and SPSS, IBM Build Systems That Work Actively to Help You Maximize Growth and Profits Most companies rely on operational systems that are largely passive. But what if you could make your systems active participants in optimizing your business? What if your systems could act intelligently on their own? Learn, not just report? Empower users to take action instead of simply escalating their problems? Evolve without massive IT investments? Decision Management Systems can do all that and more. In this book, the field’s leading expert demonstrates how to use them to drive unprecedented levels of business value. James Taylor shows how to integrate operational and analytic technologies to create systems that are more agile, more analytic, and more adaptive. Through actual case studies, you’ll learn how to combine technologies such as predictive analytics, optimization, and business rules—improving customer service, reducing fraud, managing risk, increasing agility, and driving growth. Both a practical how-to guide and a framework for planning, Decision Management Systems focuses on mainstream business challenges. Coverage includes Understanding how Decision Management Systems can transform your business Planning your systems “with the decision in mind” Identifying, modeling, and prioritizing the decisions you need to optimize Designing and implementing robust decision services Monitoring your ongoing decision-making and learning how to improve it Proven enablers of effective Decision Management Systems: people, process, and technology Identifying and overcoming obstacles that can derail your Decision Management Systems initiative

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/ to access the figures and tables from the book.

Over the years I have worked with or consulted for many managers throughout the world at all levels of industry and government. I have seen who succeeded, achieved goals, and made progress, and who failed or crashed. I have studied their methods of operation and their decision-making approach, as well as the range of people involved in the decision-making. I similarly personally managed large industrial and service organizations and their operations, and found that to succeed and have a content team of collaborators, decision-making had to be joint and delegated to the lowest competent and informed level. Using this approach not only improved the performance of the organization or firm, but also resulted in a more content, professional, cooperative, happy, and competent workforce. In general, people like to assume responsibility, particularly of functions with which they are intimately familiar. They enjoy the role of de- sion-maker and the use of their knowledge and experience in guiding their and related work. Delegation of decision-making not only infuses pride and conte- ment but also assures more informed, timely, and effective implementation of de- sions. It also adds to worker training and education as workers inquire, develop information and use of their own experience in improving their decision-making. Worker pride and feeling of control and involvement lead to contentment and s- isfaction which, in return, pays dividends in worker productivity, morale, retention, and resulting low turnover.

A proven decision management methodology for increased profits and lowered risks Knowledge Automation: How to Implement Decision Management in Business Processes describes a simple but comprehensive methodology for decision management projects, which use business rules and predictive analytics to optimize and automate small, high-volume business decisions. It includes Decision Requirements Analysis (DRA), a new method for taking the crucial first step in any IT project to implement decision management: defining a set of business decisions and identifying all the information—business knowledge and data—required to make those decisions. Describes all the stages in automating business processes, from business process modeling down to the implementation of decision services Addresses how to use business rules and predictive analytics to optimize and automate small, high-volume business decisions Proposes a simple "top-down" method for defining decision requirements and representing them in a single diagram Shows how clear requirements can allow decision management projects to be run with reduced risk and increased profit Nontechnical and accessible, Knowledge Automation reveals how DRA is destined to become a standard technique in the business analysis and project management toolbox.

Decision Making in Systems Engineering and Management is a comprehensive textbook that provides a logical process and analytical techniques for fact-based decision making for the most challenging systems problems. Grounded in systems thinking and based on sound systems engineering principles, the systems decisions process (SDP) leverages multiple objective decision analysis, multiple attribute value theory, and value-focused thinking to define the problem, measure stakeholder value, design creative solutions, explore the decision trade off space in the presence of uncertainty, and structure successful solution implementation. In addition to classical systems engineering problems, this approach has been successfully applied to a wide range of challenges including personnel recruiting, retention, and management; strategic policy analysis; facilities design and management; resource allocation; information assurance; security systems design; and other settings whose structure can be conceptualized as a system.

Author is a leading theorist in negotiation and decision-making.

CD-ROM contains: Crystal Ball -- TreePlan -- AnimaLP -- Queue -- ExcelWorkbooks.

Why do the people in some companies continually dazzle us with their brilliant decisions while those in others make one blunder after another? Do they understand their businesses better? Are they just plain smarter? Or is it all a matter of luck? The answer, says J. Frank Yates, is none of the above. The real key, rarely recognized, is how the leaders manage the company's decision processes—the leaders' decision management practices. Drawing on his thirty years of research and experience as well as scholarship from psychology, economics, statistics, strategy, medicine, and other fields to explain the fundamental nature of business decision problems, Yates highlights the ten cardinal decision issues crucial to managing the decision-making process—and ultimately better company decisions. He covers problems ranging from recognizing whether a decision is actually called for to assuring that a preferred course of action will be implemented. He shows how solid decisions result when managers ensure that deciders resolve every cardinal issue effectively for every decision problem facing the company. He also reveals how, conversely, chronically poor decisions are traceable to managers allowing—or even creating—conditions that encourage deciders to fall short in how they address at least one of those critical issues.

Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers. The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management. The book features chapters on cutting-edge topics, including: • Big data • Analytics • Managing emerging technologies and decision-making • Managing the ethics, security, privacy and legal aspects of data-driven decision-making The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles. Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels.

Decision-Making Management: A Tutorial and Applications provides practical guidance for researchers seeking to optimizing business-critical decisions employing Logical Decision Trees thus saving time and money. The book focuses on decision-making and resource allocation across and between the manufacturing, product design and logistical functions. It demonstrates key results for each sector with diverse real-world case studies drawn primarily from EU projects. Theory is accompanied by relevant analysis techniques, with a progressional approach building from simple theory to complex and dynamic decisions with multiple data points, including big data and lot of data. Binary Decision Diagrams are presented as the operating approach for evaluating large Logical Decision Trees, helping readers identify Boolean equations for quantitative analysis of multifaceted problem sets. Computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques are expertly blended to support analysis of multi-criteria decision-making problems with defined constraints and requirements. The final objective is to optimize dynamic decisions with original approaches employing useful tools, including Big Data analysis. Extensive annexes provide useful supplementary information for readers to follow methods contained in the book. Explores the use of logical decision trees to solve business problems Uses mathematical optimization techniques to resolve ‘big data’ or other multi-criteria problems Provides annexes showcasing application in manufacturing, product design and logistics Shows case examples in telecommunications, renewable energy and aerospace Supplies introduction by Benjamin Lev, Editor-in-Chief of Omega, the highest-ranked journal in management science (JCR)