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Guidebook For Supporting Decision Making Under Uncertainties: Today's Managers, Tomorrow's Business

Guidebook For Supporting Decision Making Under Uncertainties: Today's Managers, Tomorrow's Business
Author: Ettore Piccirillo
Publisher: World Scientific
Total Pages: 159
Release: 2008-02-19
Genre: Business & Economics
ISBN: 9814474916

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This book provides much-needed guidance in making sound business decisions for the business leader or decision maker, especially investment appraisal practitioners such as strategic planners, business analysts, financial partners, and supply chain experts. By “supply chain”, the authors mean the network of retailers, distributors, transporters, storage facilities and suppliers that participate in the sale, delivery and production of a particular product.The book begins with an introduction to the concept of decision making under uncertainty and the forces driving the business. A gap in the current knowledge is then discovered as it arises from an analysis of the profitability indicators that are currently being used.With hands-on experience in decision making within the supply chain environment, and coupled with leading-edge mathematical and business formulations, the authors propose how to enrich quantitative and qualitative decision-making measures. This further leads to a decision-making framework and process, supported by a ready-to-use tool (PADOVA).


Guidebook for Supporting Decision Making Under Uncertainties

Guidebook for Supporting Decision Making Under Uncertainties
Author: Ettore Piccirillo
Publisher: World Scientific
Total Pages: 159
Release: 2008
Genre: Business & Economics
ISBN: 9812708030

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The Inside Ring is the first novel in Mike Lawson’s critically acclaimed series of political thriller starring Joe DeMarco, fixer for the Speaker of the House. It opens with an assassination attempt on the president. He is only wounded, but his best friend and a Secret Service Agent are killed. It turns out that the attack wasn't without warning. General Andrew Banks, the Secretary of Homeland Security, received a note that the president was in danger, and even more alarming, that Secret Service agents guarding the president had been compromised. General Banks is reluctant to tell the FBI about the note, partly for self-serving political reasons, and partly because he doesn’t want to damage the Secret Service’s reputation based on something that might very well be a hoax. So he requests help from his friend, Speaker Mahoney, and Mahoney assigns his man DeMarco to determine if the Secret Service was really involved. Moving at a breakneck pace, and packed with plenty of humor and suspense, The Inside Ring is a must-read for fans of political thrillers.


Uncertainty Deconstructed

Uncertainty Deconstructed
Author: Bruce Garvey
Publisher: Springer Nature
Total Pages: 316
Release: 2022-08-26
Genre: Business & Economics
ISBN: 3031080076

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This book argues that uncertainty is not really uncertainty at all but just demonstrates a lack of vision and willingness to think about the unthinkable – good and bad. The task of accepting that uncertainty is about exploring the possible, rather than the impossible has to be taken on board by strategists, policy developers, and political leaders, if we are to meet the challenges that an ever changing world is throwing at us. The term “unknown – unknowns” is ubiquitous, albeit the vast majority of future uncertain events do not fall into this category. However, it has been used to absolve decision makers from criticism post-event, whereas poor foresight is the prime culprit and that most future uncertainties are “known-unknowns” or “inevitable surprises”. This re-positioning of uncertainties can help mitigate the impact of such risks through better foresight aware contingency planning. The enemy is not uncertainty itself but our lack of imagination when trying to visualize the future – we need to transform our behaviour. To better understand uncertainty we have to deconstruct it and get to grips with its component parts. Three main questions are posed and practical approaches presented: What are the main structural components that make up the conditions under which uncertainty operates? What scenario lenses can be used when exploring uncertainty? What behavioural factors do we need to consider when analysing the human responses to uncertainty? Practitioners, having to deal with making better decisions under uncertainty, will find the book a useful guide. Endorsements for the book: "With this book, Bruce Garvey performs a great service for consultants, planners and, indeed, anyone whose job involves a degree of speculation about what will happen in the future. Through a comprehensive survey of methods, tools and techniques, he provides a practical guide to unpacking the uncertainty that besets all human endeavour. This is no dry academic treatise: it deals with highly contemporary topics such as “fake news” – part of a fascinating dissection of “dark data” – and how our biases and preconceptions shape our views. The book finishes with three case studies dealing with the Covid-19 pandemic, social mobility and inequality, and achieving net zero – all topics that are sorely in need of the critical thinking and analysis skills described previously. No one can completely eliminate “20:20 hindsight” from all business decisions but readers applying the lessons of this book may find themselves saying “if only we’d known...” less frequently." -- Nick Bush, Director - CMCE (Centre for Management Consulting Excellence) "Academic literature and practical guides to uncertainty management are disparate: this exciting edition brings it all together. Principal author, Bruce Garvey, recognises the erroneous attribution of many recent events to unforeseeable uncertainty (‘unknown unknowns’), calling these out as inevitable surprises (or ‘unknown knowns’), a category of uncertainty that is typically overlooked. Garvey describes critical dimensions of uncertainty, before examining scenarios and behavioural aspects, the latter being a ‘hidden influencer’ which is too often neglected. The guidebook contains a variety of methods, tools and techniques, including several that deserve more use, and contains a detailed glossary and reference list. Practical advice covers topics such as identifying weak signals for use in scenario development and overcoming cognitive dissonance. This well-structured and engagingly written guide should serve as a standard text for students, academics and practitioners across policy making, business, and industry." -- Dr. Geoff Darch, Water Resources Strategy Manager, Anglian Water. Co-Founder, Analysis under Uncertainty for Decision-Makers (AU4DM) Network "This is a valuable companion volume to John Kay and Mervyn King's Radical Uncertainty - and it is a necessary corrective to the physics envy of disciplines such as economics which achieve a false sense of certainty by creating highly plausible but unreliable simplifications of things through over generalisation - leading to simplistic proposals for interventions which can only rightly be judged through a lens of complexity and probability. I would like to be more optimistic about the ultimate effects of books of this kind - and in some fields, perhaps in military decision-making and defence I am quite optimistic. In such fields, people tend to approach decision-making through the assumption that things will go wrong, and that the effects of any mistakes will be very keenly, perhaps fatally experienced. In business and softer social policy-making, I fear the battle will be much harder. In such fields as politics and business, it is often better for the reputation "as Keynes remarked, "to fail conventionally than to succeed unconventionally." In such fields, it is more important to make defensible decisions than to make good decisions, so an artificial sense of logical certainty will perhaps always hold an unhealthy appeal. But here's hoping anyway!" -- Rory Sutherland, Vice Chairman, Ogilvy Group "Here is a most insightful book, which holistically examines the ‘world of uncertainty', particularly as it impacts sense- to decision-making processes for many different stakeholders. Both scholars and practitioners, strategists to operators, soon gain from reading. Journeying from theory to practice, we embark on a comprehensive definition of uncertainty to subsequently become better equipped for its greater contemporary navigation when going forward, all elucidated by several well-structured scenarios and case-study examples. How uncertainty relates to risk (both qualitative and quantitative) is systematically charted, articulating their close interactivity. Forming a successful guide, this book has much enduring reference value and is therefore deserving of being readily retrievable as events and developments benefit from their improved understanding. Uncertainty can demonstrably be negotiated much more effectively. Alternative situations and conditions of denial, lamented as ‘we should have (fore)seen that’, no longer stand as acceptable when it comes to anticipating futures ahead. With this book, further help is now at hand." -- Adam D.M. Svendsen, PhD, International Intelligence & Defence Strategist, Researcher, Analyst, Educator & Consultant


Decision Making under Deep Uncertainty

Decision Making under Deep Uncertainty
Author: Vincent A. W. J. Marchau
Publisher: Springer
Total Pages: 408
Release: 2019-04-04
Genre: Business & Economics
ISBN: 3030052524

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This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work. The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.


Decision Making Under Uncertainty

Decision Making Under Uncertainty
Author: Mykel J. Kochenderfer
Publisher: MIT Press
Total Pages: 350
Release: 2015-07-24
Genre: Computers
ISBN: 0262331713

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An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with unknown outcomes. Designers of automated decision support systems must take into account the various sources of uncertainty while balancing the multiple objectives of the system. This book provides an introduction to the challenges of decision making under uncertainty from a computational perspective. It presents both the theory behind decision making models and algorithms and a collection of example applications that range from speech recognition to aircraft collision avoidance. Focusing on two methods for designing decision agents, planning and reinforcement learning, the book covers probabilistic models, introducing Bayesian networks as a graphical model that captures probabilistic relationships between variables; utility theory as a framework for understanding optimal decision making under uncertainty; Markov decision processes as a method for modeling sequential problems; model uncertainty; state uncertainty; and cooperative decision making involving multiple interacting agents. A series of applications shows how the theoretical concepts can be applied to systems for attribute-based person search, speech applications, collision avoidance, and unmanned aircraft persistent surveillance. Decision Making Under Uncertainty unifies research from different communities using consistent notation, and is accessible to students and researchers across engineering disciplines who have some prior exposure to probability theory and calculus. It can be used as a text for advanced undergraduate and graduate students in fields including computer science, aerospace and electrical engineering, and management science. It will also be a valuable professional reference for researchers in a variety of disciplines.


Decision Making Under Uncertainty

Decision Making Under Uncertainty
Author: Claude Greengard
Publisher: Springer Science & Business Media
Total Pages: 166
Release: 2012-12-06
Genre: Mathematics
ISBN: 146849256X

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In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.


Principles of Risk Analysis

Principles of Risk Analysis
Author: Charles Yoe
Publisher: CRC Press
Total Pages: 576
Release: 2016-04-19
Genre: Technology & Engineering
ISBN: 1439857504

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In every decision context there are things we know and things we do not know. Risk analysis uses science and the best available evidence to assess what we know-and it is intentional in the way it addresses the importance of the things we don't know. Principles of Risk Analysis: Decision Making Under Uncertainty lays out the tasks of risk analysis i


Handbook of Decision Analysis

Handbook of Decision Analysis
Author: Gregory S. Parnell
Publisher: John Wiley & Sons
Total Pages: 441
Release: 2013-01-24
Genre: Business & Economics
ISBN: 1118515846

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A ONE-OF-A-KIND GUIDE TO THE BEST PRACTICES IN DECISION ANALYSIS Decision analysis provides powerful tools for addressing complex decisions that involve uncertainty and multiple objectives, yet most training materials on the subject overlook the soft skills that are essential for success in the field. This unique resource fills this gap in the decision analysis literature and features both soft personal/interpersonal skills and the hard technical skills involving mathematics and modeling. Readers will learn how to identify and overcome the numerous challenges of decision making, choose the appropriate decision process, lead and manage teams, and create value for their organization. Performing modeling analysis, assessing risk, and implementing decisions are also addressed throughout. Additional features include: Key insights gleaned from decision analysis applications and behavioral decision analysis research Integrated coverage of the techniques of single- and multiple-objective decision analysis Multiple qualitative and quantitative techniques presented for each key decision analysis task Three substantive real-world case studies illustrating diverse strategies for dealing with the challenges of decision making Extensive references for mathematical proofs and advanced topics The Handbook of Decision Analysis is an essential reference for academics and practitioners in various fields including business, operations research, engineering, and science. The book also serves as a supplement for courses at the upper-undergraduate and graduate levels.


Decision Making under Deep Uncertainty

Decision Making under Deep Uncertainty
Author: Vincent A. W. J. Marchau
Publisher: Springer
Total Pages: 405
Release: 2019-04-27
Genre: Business & Economics
ISBN: 9783030052515

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This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work.


Decision Making Under Deep Uncertainty

Decision Making Under Deep Uncertainty
Author: Vincent A. W. J. Marchau
Publisher:
Total Pages:
Release: 2019
Genre: Differentiable dynamical systems
ISBN: 9783030052539

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This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work.