Author: Bruce F. Baird
Publisher: John Wiley & Sons
ISBN: 9780471858911
Category : Business & Economics
Languages : en
Pages : 546
Book Description
How to improve decision-making skills in realistic situations and do it in a reasonably nonmathematical fashion. Develops practical techniques for deciding upon the best strategies in a variety of situations. Provides methods for reducing complex problems to easily-drawn decision diagrams (trees), supported by real-world examples. Includes detailed cases that employ the methods described in the text. Each chapter contains illustrative examples and exercises.
Managerial Decisions Under Uncertainty
Author: Bruce F. Baird
Publisher: John Wiley & Sons
ISBN: 9780471858911
Category : Business & Economics
Languages : en
Pages : 546
Book Description
How to improve decision-making skills in realistic situations and do it in a reasonably nonmathematical fashion. Develops practical techniques for deciding upon the best strategies in a variety of situations. Provides methods for reducing complex problems to easily-drawn decision diagrams (trees), supported by real-world examples. Includes detailed cases that employ the methods described in the text. Each chapter contains illustrative examples and exercises.
Publisher: John Wiley & Sons
ISBN: 9780471858911
Category : Business & Economics
Languages : en
Pages : 546
Book Description
How to improve decision-making skills in realistic situations and do it in a reasonably nonmathematical fashion. Develops practical techniques for deciding upon the best strategies in a variety of situations. Provides methods for reducing complex problems to easily-drawn decision diagrams (trees), supported by real-world examples. Includes detailed cases that employ the methods described in the text. Each chapter contains illustrative examples and exercises.
Decision Making Under Uncertainty
Author: Mykel J. Kochenderfer
Publisher: MIT Press
ISBN: 0262331713
Category : Computers
Languages : en
Pages : 350
Book Description
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.
Publisher: MIT Press
ISBN: 0262331713
Category : Computers
Languages : en
Pages : 350
Book Description
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.
Design Decisions Under Uncertainty with Limited Information
Author: Efstratios Nikolaidis
Publisher: CRC Press
ISBN: 9781138115095
Category :
Languages : en
Pages : 538
Book Description
Today's business environment involves design decisions with significant uncertainty. To succeed, decision-makers should replace deterministic methods with a risk-based approach that accounts for the decision maker¿s risk tolerance. In many problems, it is impractical to collect data because rare or one-time events are involved. Therefore, we need a methodology to model uncertainty and make choices when we have limited information. This methodology must use all available information and rely only on assumptions that are supported by evidence. This book explains theories and tools to represent uncertainty using both data and expert judgment. It teaches the reader how to make design or business decisions when there is limited information with these tools. Readers will learn a structured, risk-based approach, which is based on common sense principles, for design and business decisions. These decisions are consistent with the decision-maker¿s risk attitude. The book is exceptionally suited as educational material because it uses everyday language and real-life examples to elucidate concepts. It demonstrates how these concepts touch our lives through many practical examples, questions and exercises. These are designed to help students learn that first they should understand a problem and then establish a strategy for solving it, instead of using trial-and-error approaches. This volume is intended for undergraduate and graduate courses in mechanical, civil, industrial, aerospace, and ocean engineering and for researchers and professionals in these disciplines. It will also benefit managers and students in business administration who want to make good decisions with limited information.
Publisher: CRC Press
ISBN: 9781138115095
Category :
Languages : en
Pages : 538
Book Description
Today's business environment involves design decisions with significant uncertainty. To succeed, decision-makers should replace deterministic methods with a risk-based approach that accounts for the decision maker¿s risk tolerance. In many problems, it is impractical to collect data because rare or one-time events are involved. Therefore, we need a methodology to model uncertainty and make choices when we have limited information. This methodology must use all available information and rely only on assumptions that are supported by evidence. This book explains theories and tools to represent uncertainty using both data and expert judgment. It teaches the reader how to make design or business decisions when there is limited information with these tools. Readers will learn a structured, risk-based approach, which is based on common sense principles, for design and business decisions. These decisions are consistent with the decision-maker¿s risk attitude. The book is exceptionally suited as educational material because it uses everyday language and real-life examples to elucidate concepts. It demonstrates how these concepts touch our lives through many practical examples, questions and exercises. These are designed to help students learn that first they should understand a problem and then establish a strategy for solving it, instead of using trial-and-error approaches. This volume is intended for undergraduate and graduate courses in mechanical, civil, industrial, aerospace, and ocean engineering and for researchers and professionals in these disciplines. It will also benefit managers and students in business administration who want to make good decisions with limited information.
Decision Making under Deep Uncertainty
Author: Vincent A. W. J. Marchau
Publisher: Springer
ISBN: 3030052524
Category : Business & Economics
Languages : en
Pages : 408
Book Description
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.
Publisher: Springer
ISBN: 3030052524
Category : Business & Economics
Languages : en
Pages : 408
Book Description
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.
Decisions Under Uncertainty
Author: Ian Jordaan
Publisher: Cambridge University Press
ISBN: 9780521782777
Category : Business & Economics
Languages : en
Pages : 696
Book Description
Publisher Description
Publisher: Cambridge University Press
ISBN: 9780521782777
Category : Business & Economics
Languages : en
Pages : 696
Book Description
Publisher Description
Investment under Uncertainty
Author: Robert K. Dixit
Publisher: Princeton University Press
ISBN: 1400830176
Category : Business & Economics
Languages : en
Pages : 484
Book Description
How should firms decide whether and when to invest in new capital equipment, additions to their workforce, or the development of new products? Why have traditional economic models of investment failed to explain the behavior of investment spending in the United States and other countries? In this book, Avinash Dixit and Robert Pindyck provide the first detailed exposition of a new theoretical approach to the capital investment decisions of firms, stressing the irreversibility of most investment decisions, and the ongoing uncertainty of the economic environment in which these decisions are made. In so doing, they answer important questions about investment decisions and the behavior of investment spending. This new approach to investment recognizes the option value of waiting for better (but never complete) information. It exploits an analogy with the theory of options in financial markets, which permits a much richer dynamic framework than was possible with the traditional theory of investment. The authors present the new theory in a clear and systematic way, and consolidate, synthesize, and extend the various strands of research that have come out of the theory. Their book shows the importance of the theory for understanding investment behavior of firms; develops the implications of this theory for industry dynamics and for government policy concerning investment; and shows how the theory can be applied to specific industries and to a wide variety of business problems.
Publisher: Princeton University Press
ISBN: 1400830176
Category : Business & Economics
Languages : en
Pages : 484
Book Description
How should firms decide whether and when to invest in new capital equipment, additions to their workforce, or the development of new products? Why have traditional economic models of investment failed to explain the behavior of investment spending in the United States and other countries? In this book, Avinash Dixit and Robert Pindyck provide the first detailed exposition of a new theoretical approach to the capital investment decisions of firms, stressing the irreversibility of most investment decisions, and the ongoing uncertainty of the economic environment in which these decisions are made. In so doing, they answer important questions about investment decisions and the behavior of investment spending. This new approach to investment recognizes the option value of waiting for better (but never complete) information. It exploits an analogy with the theory of options in financial markets, which permits a much richer dynamic framework than was possible with the traditional theory of investment. The authors present the new theory in a clear and systematic way, and consolidate, synthesize, and extend the various strands of research that have come out of the theory. Their book shows the importance of the theory for understanding investment behavior of firms; develops the implications of this theory for industry dynamics and for government policy concerning investment; and shows how the theory can be applied to specific industries and to a wide variety of business problems.
Decision-Making Under Uncertainty
Author: George K. Chacko
Publisher: Praeger
ISBN:
Category : Business & Economics
Languages : en
Pages : 280
Book Description
In real-life decision-making situations it is necessary to make decisions with incomplete information, for oftentimes uncertain results. In Decision-Making Under Uncertainty, Dr. Chacko applies his years of statistical research and experience to the analysis of twenty-four real-life decision-making situations, both those with few data points (eg: Cuban Missile Crisis), and many data points (eg: aspirin for heart attack prevention). These situations encompass decision-making in a variety of business, social and political, physical and biological, and military environments. Though different, all of these have one characteristic in common: their outcomes are uncertain/unkown, and unknowable. Chacko Demonstrates how the decision-maker can reduce uncertainty by choosing probable outcomes using the statistical methods he introduces. This detailed volume develops standard statistical concepts (t, x2, normal distribution, ANOVA), and the less familiar concepts (logical probability, subjective probability, Bayesian Inference, Penalty for Non-Fulfillment, Bluff-Threats Matrix, etc.). Chacko also offers a thorough discussion of the underlying theoretical principles. The end of each chapter contains a set of questions, three quarters of which focus on concepts, formulation, conclusion, resource commitments, and caveats; only one quarter with computations. Ideal for the practitioner, the work is also designed to serve as the primary text for graduate or advanced undergraduate courses in statistics and decision science.
Publisher: Praeger
ISBN:
Category : Business & Economics
Languages : en
Pages : 280
Book Description
In real-life decision-making situations it is necessary to make decisions with incomplete information, for oftentimes uncertain results. In Decision-Making Under Uncertainty, Dr. Chacko applies his years of statistical research and experience to the analysis of twenty-four real-life decision-making situations, both those with few data points (eg: Cuban Missile Crisis), and many data points (eg: aspirin for heart attack prevention). These situations encompass decision-making in a variety of business, social and political, physical and biological, and military environments. Though different, all of these have one characteristic in common: their outcomes are uncertain/unkown, and unknowable. Chacko Demonstrates how the decision-maker can reduce uncertainty by choosing probable outcomes using the statistical methods he introduces. This detailed volume develops standard statistical concepts (t, x2, normal distribution, ANOVA), and the less familiar concepts (logical probability, subjective probability, Bayesian Inference, Penalty for Non-Fulfillment, Bluff-Threats Matrix, etc.). Chacko also offers a thorough discussion of the underlying theoretical principles. The end of each chapter contains a set of questions, three quarters of which focus on concepts, formulation, conclusion, resource commitments, and caveats; only one quarter with computations. Ideal for the practitioner, the work is also designed to serve as the primary text for graduate or advanced undergraduate courses in statistics and decision science.
Managing Risk and Uncertainty
Author: Richard Friberg
Publisher: MIT Press
ISBN: 0262528193
Category : Business & Economics
Languages : en
Pages : 395
Book Description
A comprehensive framework for assessing strategies for managing risk and uncertainty, integrating theory and practice and synthesizing insights from many fields. This book offers a framework for making decisions under risk and uncertainty. Synthesizing research from economics, finance, decision theory, management, and other fields, the book provides a set of tools and a way of thinking that determines the relative merits of different strategies. It takes as its premise that we make better decisions if we use the whole toolkit of economics and related fields to inform our decision making. The text explores the distinction between risk and uncertainty and covers standard models of decision making under risk as well as more recent work on decision making under uncertainty, with a particular focus on strategic interaction. It also examines the implications of incomplete markets for managing under uncertainty. It presents four core strategies: a benchmark strategy (proceeding as if risk and uncertainty were low), a financial hedging strategy (valuable if there is much risk), an operational hedging strategy (valuable for conditions of much uncertainty), and a flexible strategy (valuable if there is much risk and/or uncertainty). The book then examines various aspects of these strategies in greater depth, building on empirical work in several different fields. Topics include price-setting, real options and Monte Carlo techniques, organizational structure, and behavioral biases. Many chapters include exercises and appendixes with additional material. The book can be used in graduate or advanced undergraduate courses in risk management, as a guide for researchers, or as a reference for management practitioners.
Publisher: MIT Press
ISBN: 0262528193
Category : Business & Economics
Languages : en
Pages : 395
Book Description
A comprehensive framework for assessing strategies for managing risk and uncertainty, integrating theory and practice and synthesizing insights from many fields. This book offers a framework for making decisions under risk and uncertainty. Synthesizing research from economics, finance, decision theory, management, and other fields, the book provides a set of tools and a way of thinking that determines the relative merits of different strategies. It takes as its premise that we make better decisions if we use the whole toolkit of economics and related fields to inform our decision making. The text explores the distinction between risk and uncertainty and covers standard models of decision making under risk as well as more recent work on decision making under uncertainty, with a particular focus on strategic interaction. It also examines the implications of incomplete markets for managing under uncertainty. It presents four core strategies: a benchmark strategy (proceeding as if risk and uncertainty were low), a financial hedging strategy (valuable if there is much risk), an operational hedging strategy (valuable for conditions of much uncertainty), and a flexible strategy (valuable if there is much risk and/or uncertainty). The book then examines various aspects of these strategies in greater depth, building on empirical work in several different fields. Topics include price-setting, real options and Monte Carlo techniques, organizational structure, and behavioral biases. Many chapters include exercises and appendixes with additional material. The book can be used in graduate or advanced undergraduate courses in risk management, as a guide for researchers, or as a reference for management practitioners.
Managing Project Uncertainty
Author: David Cleden
Publisher: Routledge
ISBN: 1351920413
Category : Business & Economics
Languages : en
Pages : 131
Book Description
Dealing effectively with uncertainty requires today's project manager to be familiar with a broad spectrum of strategies, encompassing both 'hard' and 'soft' methods. This theme of unified thinking (i.e. the need to selectively draw upon a wide range of strategies in any given situation) will differentiate the book from its contemporaries. By picking up where traditional risk management techniques begin to fail, it brings together leading-edge thinking from a variety of disciplines and shows how these techniques can be used to conquer uncertainty in projects. The ability to make good decisions when faced with uncertainty is the real challenge. It is a universal truth that a decision is only as good as the information it is based on. But good information is often hard to come by, and all projects are vulnerable to the unknown and the unknowable. Thus, uncertainty becomes the sworn enemy of the project manager. Wherever we try to analyse, quantify, plan and act, uncertainty lies in wait to surprise us with its ambiguity and unpredictability. It lurks in every stage of the project lifecycle: in the planning (how long will this really take?), the initiation (this isn't the situation I expected!), the execution (who could have foreseen that happening?), and even the completion of a project (where are the expected benefits?). But managing uncertainty is a lot more than just applying risk management techniques. It requires a deep appreciation of how uncertainty arises and, by recognising its different guises, the appropriate strategies can be formulated. If we can learn how to reduce uncertainty, we can make better management decisions and increase the chances of the project succeeding. This book addresses five key questions: ¢ Why is there uncertainty in projects? ¢ How do you spot the symptoms of uncertainty, preferably at an early stage? ¢ What can be done to avoid uncertainty? ¢ What strategies can be used to deal with project uncertainty? ¢ How can both the individual and the organisation learn to cope more effectively in the future? The reader is assumed to be a either a project management professional, or a senior manager looking for ways to improve project management strategy within their organisation. As such, a foundation in project management basics is assumed, although not essential. The book then builds on this by exposing new ideas and concepts, and shows how these can be harnessed to tackle uncertainty in its many guises.
Publisher: Routledge
ISBN: 1351920413
Category : Business & Economics
Languages : en
Pages : 131
Book Description
Dealing effectively with uncertainty requires today's project manager to be familiar with a broad spectrum of strategies, encompassing both 'hard' and 'soft' methods. This theme of unified thinking (i.e. the need to selectively draw upon a wide range of strategies in any given situation) will differentiate the book from its contemporaries. By picking up where traditional risk management techniques begin to fail, it brings together leading-edge thinking from a variety of disciplines and shows how these techniques can be used to conquer uncertainty in projects. The ability to make good decisions when faced with uncertainty is the real challenge. It is a universal truth that a decision is only as good as the information it is based on. But good information is often hard to come by, and all projects are vulnerable to the unknown and the unknowable. Thus, uncertainty becomes the sworn enemy of the project manager. Wherever we try to analyse, quantify, plan and act, uncertainty lies in wait to surprise us with its ambiguity and unpredictability. It lurks in every stage of the project lifecycle: in the planning (how long will this really take?), the initiation (this isn't the situation I expected!), the execution (who could have foreseen that happening?), and even the completion of a project (where are the expected benefits?). But managing uncertainty is a lot more than just applying risk management techniques. It requires a deep appreciation of how uncertainty arises and, by recognising its different guises, the appropriate strategies can be formulated. If we can learn how to reduce uncertainty, we can make better management decisions and increase the chances of the project succeeding. This book addresses five key questions: ¢ Why is there uncertainty in projects? ¢ How do you spot the symptoms of uncertainty, preferably at an early stage? ¢ What can be done to avoid uncertainty? ¢ What strategies can be used to deal with project uncertainty? ¢ How can both the individual and the organisation learn to cope more effectively in the future? The reader is assumed to be a either a project management professional, or a senior manager looking for ways to improve project management strategy within their organisation. As such, a foundation in project management basics is assumed, although not essential. The book then builds on this by exposing new ideas and concepts, and shows how these can be harnessed to tackle uncertainty in its many guises.
Effective Decision-Making
Author: Edoardo Binda Zane
Publisher: Createspace Independent Publishing Platform
ISBN: 9781530800094
Category :
Languages : en
Pages : 140
Book Description
The aim of this book is to quickly empower you to make better decisions by giving you step-by-step explanations of the best techniques. We always make decisions under uncertainty and pressure, especially in business. We need faster and better decisions to cope, but we don''t have the time to learn how to make them well. That is where I come in. I wrote this book to allow you to make better decisions without spending weeks studying theory and practice. THE INTRODUCTION gives you a snapshot of two decision-making biases, of the worst mistake you can do when making decision, and a lesson taken straight from philosophy. - Decision Biases (why your brain isn''t always your friend in decisions) - The Worst Mistake in Decision-Making - A Lesson From Another Time THE FIRST CHAPTER looks at frameworks of reference, meaning how you can apply decision-making to achieve your goals, for example how and why some decisions are able to automatically give you a competitive advantage. - The OODA Loop - The Recognition-Primed Decision Model - GROW or the John Whitmore Model - The PDSA Cycle CHAPTERS 2 TO 5 look at separate phases of decision-making: understanding your context, understanding the problem, generating solutions and selecting one option out of many. 2 - CONTEXT Contexts can be very different - and there is no one size fits all approach, which is why this book provides you with five. - SWOT and PEST - TELOS - Porter''s Five Forces - Causal Loops Diagrams 3 - PROBLEM ASSESSMENT Before making decisions, then, you need to work on finding out exactly what you are trying to solve. This chapter gives you 5 tools to do so: - Root Cause Analysis: Ishikawa''s Diagramand the 5 Whys Technique - Pareto Analysis - Kipling Method (5W1H) - CATWOE 4 - GENERATING IDEAS In "pure" decision-making, little attention is given to this phase, as it belongs to a different field: creativity. This book includes two tools: - Zwicky''s Box - SCAMPER 5 - WEIGHING ALTERNATIVES This book gives you six tools for this, each one with its specificities: - Weights and Factors: the Grid Analysis and the KT Matrix - The Paired Comparison Analysis - The Quantitative Strategic Planning Matrix - The Analytic Hierarchy Process - The Eisenhower Matrix CHAPTER 6 AND 7 look at group decisions, meaning whether it''s a good idea to make decisions in a group and, if it is, how that group should make decisions. 6 - DO YOU NEED YOUR TEAM? You can either involve your team in decisions or exclude them. Often, managers are torn between these two options - you have three tools to help you though: - The Vroom-Yetton-Jago Model - The Hoy-Tarter Model - The Hersey-Blanchard Model 7 - GROUP TECHNIQUES To be used when making decisions in a group is necessary. - The Nominal Group Technique - The Delphi Method - Hartnett''s Consensus-Oriented Decision-Making Model - The Stepladder Technique - DeBono''s Six Thinking Hats - The Charette Procedure - RAPID CHAPTERS 8 AND 9 look at decisions in corporate strategy and analyse a decision''s consequence 8 - CORPORATE STRATEGY These decision tools have all been developed for corporations, but they still hold value for smaller businesses. - The BCG Matrix - The Advantage Matrix - The GE Matrix - Blind Spot Analysis 9 - CONSEQUENCES In other words: "how can I make sure that the decision I made is the best one and will work in my specific situation?" Unfortunately nobody can answer this. Any decision method can only skew the odds of having made the right decision in your favour. That said, there are a few techniques you can apply. - Impact Assessment - Plus-Minus-Interesting - Decision Trees - Cost-Benefit Analysis - Futures Wheel
Publisher: Createspace Independent Publishing Platform
ISBN: 9781530800094
Category :
Languages : en
Pages : 140
Book Description
The aim of this book is to quickly empower you to make better decisions by giving you step-by-step explanations of the best techniques. We always make decisions under uncertainty and pressure, especially in business. We need faster and better decisions to cope, but we don''t have the time to learn how to make them well. That is where I come in. I wrote this book to allow you to make better decisions without spending weeks studying theory and practice. THE INTRODUCTION gives you a snapshot of two decision-making biases, of the worst mistake you can do when making decision, and a lesson taken straight from philosophy. - Decision Biases (why your brain isn''t always your friend in decisions) - The Worst Mistake in Decision-Making - A Lesson From Another Time THE FIRST CHAPTER looks at frameworks of reference, meaning how you can apply decision-making to achieve your goals, for example how and why some decisions are able to automatically give you a competitive advantage. - The OODA Loop - The Recognition-Primed Decision Model - GROW or the John Whitmore Model - The PDSA Cycle CHAPTERS 2 TO 5 look at separate phases of decision-making: understanding your context, understanding the problem, generating solutions and selecting one option out of many. 2 - CONTEXT Contexts can be very different - and there is no one size fits all approach, which is why this book provides you with five. - SWOT and PEST - TELOS - Porter''s Five Forces - Causal Loops Diagrams 3 - PROBLEM ASSESSMENT Before making decisions, then, you need to work on finding out exactly what you are trying to solve. This chapter gives you 5 tools to do so: - Root Cause Analysis: Ishikawa''s Diagramand the 5 Whys Technique - Pareto Analysis - Kipling Method (5W1H) - CATWOE 4 - GENERATING IDEAS In "pure" decision-making, little attention is given to this phase, as it belongs to a different field: creativity. This book includes two tools: - Zwicky''s Box - SCAMPER 5 - WEIGHING ALTERNATIVES This book gives you six tools for this, each one with its specificities: - Weights and Factors: the Grid Analysis and the KT Matrix - The Paired Comparison Analysis - The Quantitative Strategic Planning Matrix - The Analytic Hierarchy Process - The Eisenhower Matrix CHAPTER 6 AND 7 look at group decisions, meaning whether it''s a good idea to make decisions in a group and, if it is, how that group should make decisions. 6 - DO YOU NEED YOUR TEAM? You can either involve your team in decisions or exclude them. Often, managers are torn between these two options - you have three tools to help you though: - The Vroom-Yetton-Jago Model - The Hoy-Tarter Model - The Hersey-Blanchard Model 7 - GROUP TECHNIQUES To be used when making decisions in a group is necessary. - The Nominal Group Technique - The Delphi Method - Hartnett''s Consensus-Oriented Decision-Making Model - The Stepladder Technique - DeBono''s Six Thinking Hats - The Charette Procedure - RAPID CHAPTERS 8 AND 9 look at decisions in corporate strategy and analyse a decision''s consequence 8 - CORPORATE STRATEGY These decision tools have all been developed for corporations, but they still hold value for smaller businesses. - The BCG Matrix - The Advantage Matrix - The GE Matrix - Blind Spot Analysis 9 - CONSEQUENCES In other words: "how can I make sure that the decision I made is the best one and will work in my specific situation?" Unfortunately nobody can answer this. Any decision method can only skew the odds of having made the right decision in your favour. That said, there are a few techniques you can apply. - Impact Assessment - Plus-Minus-Interesting - Decision Trees - Cost-Benefit Analysis - Futures Wheel