Uncertainty Deconstructed: A Guidebook for Decision Support Practitioners

Description

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 Preface: ``We Should´ve Seen It Coming´´! Synopsis To Whom Is This Book Targeted? Book Structure Setting the Scene: Why Should I Read This Book? Acknowledgements Contents About the Authors Part I: Introducing the Programme and Its Contents Chapter 1: Setting the Scene and Introduction 1.1 Terms of Reference 1.2 Introduction 1.2.1 Looking at Uncertainty Through an Alternative Lens So as to Offer a Different Perspective? 1.2.2 Re-adjusting Our Perceptions 1.3 Conclusions References Part II: Theoretical Underpinnings: Structural Components of Uncertainty Chapter 2: Locating Uncertainty Along the Risk Spectrum 2.1 Introduction 2.1.1 Scoping the Risk Spectrum: Positioning Uncertainty 2.1.1.1 Certainty 2.1.1.2 Risk 2.1.1.3 Uncertainty Uncertainty and Risk: A Confusion of Terms When It Comes to Measurement Different Interpretations of Uncertainty: Confused Dot Com(plexity)! Version 1 Version 2 Version 3 Version 4 Version 5 Version 6 Version 7 2.1.1.4 Complexity and Interconnectivity Properties of Complexity Relevance of Complexity 2.1.2 The Uncertainty Profile: From ``Known-knowns´´ to ``Unknown-unknowns´´ 2.1.2.1 Background: The Existential Poetry of Donald H. Rumsfeld 2.1.2.2 Event Predictability 2.1.2.3 Event Visibility 2.1.2.4 The Uncertainty Profile Template 2.1.2.5 Quadrant 1 (Q1): Predictable and Identifiable (Known knowns) 2.1.2.6 Quadrant 2 (Q2): Identifies Predictable Events Not Yet Identifiable (Known Unknowns) 2.1.2.7 Quadrant 4 (Q4): Unpredictable and Not Identifiable (Unknown Unknowns) 2.1.2.8 Quadrant 3 (Q3): Unpredictable and Identifiable (Unknown Knowns) 2.1.3 Methods, Tools, and Techniques (MTTs) 2.1.3.1 Other Templates 2.1.3.2 Cynefin 2.1.3.3 VUCA 2.1.3.4 Animal Metaphors Which Metaphor to Use? 2.2 Summary References Chapter 3: Problem Status 3.1 Introduction: What Is the Problem? 3.2 Problem Types: Not All Problems Are the Same 3.2.1 A Note About Tame Problems 3.2.2 Wicked Problems and Messes 3.2.3 Problems and the Uncertainty Profile 3.3 Post Normal 3.4 Methods, Tools, and Techniques (MMTs) 3.4.1 Problem Structuring Methods (PSMs) 3.4.2 Robustness Analysis 3.4.3 Rosenhead´s Summary 3.5 Summary References Chapter 4: Time-Based Criteria 4.1 Introduction 4.2 Time Frames 4.2.1 Past Time 4.2.2 Now 4.2.3 Future Time 4.3 Time Paths 4.3.1 Linear 4.3.2 Non-linear and Asymmetric 4.3.3 Exponential 4.3.4 The Law of Accelerating Returns 4.3.5 How to Predict Exponential Growth 4.4 Time Path Overlays (Manifestations of Underlying Influences) 4.4.1 Cycles (and Waves) 4.4.2 Trends 4.4.3 Megatrends 4.5 Visibility (and Its Relationship with Time) 4.5.1 Current 4.5.2 Emerging Issues 4.5.3 Weak Signals 4.5.4 Outliers/Wilds Cards 4.6 Integrating Time-Based Criteria (MTTs) References Chapter 5: The Evidence Base 5.1 Introduction: Beware of the Past-What History Do You Believe in or Want to Believe in? 5.2 Evidence Status 5.2.1 The Availability of Data 5.2.2 Understanding and Actioning Data (How Can We React to Evidential Data?) 5.2.3 Beware of the Dark: Dark Data 5.3 Veracity (or Lies, Damned Lies, and ``Fake News´´) 5.3.1 Validated Evidence (Basically Truthful) 5.3.2 Misinformation, Disinformation, Malinformation (and of Course Fake News) 5.3.3 What to Do? 5.4 The Danger of Losing Control: A Fragmented Internet and Social Media Bubbles 5.5 MTT Support Template: Spotting the Bad Actors References Chapter 6: Ways of Seeing the Future 6.1 Introduction 6.2 History 6.3 Futures 6.3.1 Types of Potential Futures 6.3.2 The Prediction Challenge: Forecasting or Foresight, and Where Does Strategic Planning Fit in? 6.3.3 What Is Strategic Foresight? 6.3.4 From Market Intelligence to Foresight 6.3.5 Benefits of Systematically Organised Foresight Activity 6.3.6 So How Can the Differences Between Forecasting vs Foresight Be Summarised? 6.4 Foresight: Challenging Uncertainty So We Can Move from the ``Unknown-Known´´ Quadrant (3) to the ``Known-Unknown´´ Quadran... 6.4.1 Alternative Outcomes and the Futures Cone: An Aid to Foresight 6.4.2 The Role of Science Fiction 6.5 Methods, Tools, and Techniques (MTTs) 6.5.1 Causal Layered Analysis 6.5.2 Summary of Benefits and Disadvantages of CLA References Part III: Theoretical Underpinnings: Scenarios and Their Role in Dealing with Uncertainty Chapter 7: Scenarios: What Are They, Why Are They Useful and How Can We Best Use Them? 7.1 Introduction 7.2 Lenses 7.2.1 Reactive 7.2.2 Exploratory 7.2.3 Scenarios as a Design Process 7.2.4 So, What Is the Design Process? 7.2.5 Strategic Options Analysis or ``What If´´ Scenarios: An Exploratory Approach 7.3 Types of Outcome: A Work Through of a Tentative Options Analysis Process 7.3.1 Towards a Synthesis of Scenario Options 7.3.2 Strategic Options Analysis for Different Scenarios 7.4 Allocation of Viable Scenarios to the Uncertainty Profile Template 7.4.1 So, How Does This All Work and What Does It All Mean: A Process Summary? 7.5 Methods, Tools, and Techniques 7.5.1 Morphological Analysis (MA) 7.6 A New Approach to Identifying Weak Signals for Scenario Development Using MA: Distance Analysis 7.6.1 Using MA as a Tool to Draw Out Weak Signals 7.6.2 Issue of Determining What Is Current Knowledge (State of the Art) 7.7 Catastrophic and Existential Risks 7.7.1 Welcome to the Anthropocene 7.7.2 MTT: Support Tool 7.7.3 Allocating the Risks to the Uncertainty Profile 7.8 Case Examples 7.8.1 A Scenario Based Example 7.9 A Concluding Set of Questions References Chapter 8: Scenario Derivatives First, Second, and Third Order Scenarios: Generic (Landscape) Variables 8.1 Introduction 8.2 Methods, Tools, and Techniques (MTTs) 8.2.1 Horizon Scanning 8.2.1.1 The Process 8.2.2 Mind Maps 8.2.3 PESTLE and Dynamic PESTLE 8.2.3.1 A Basic Contextual Framework Using PESTLE 8.2.3.2 Dynamic PESTLE: A New Approach 8.2.3.3 Dynamic PESTLE: A Summary 8.2.4 Hypothesis Generation 8.2.4.1 Analysis of Competing Hypotheses (ACH) 8.2.4.2 The Method of Analysis of Competing Hypotheses 8.2.4.3 Other Strengths of the Method 8.2.4.4 Weaknesses 8.2.4.5 Summary 8.2.4.6 Inconsistency Finder (IF) Tm 8.2.4.7 Quadrant Crunching (QC) 8.2.4.8 The Method 8.2.5 The Analytic Hierarchy Process (AHP) 8.2.6 Bayesian Belief Networks (BBNs) 8.3 Conclusion References Part IV: Theoretical Underpinnings: Behaviour-The Hidden Influencer in How We Deal with Uncertainty Chapter 9: Behavioural Factors: Cognitive Biases and Dissonance, Anomie, and Alienation (Or How We Humans Mess Things Up) 9.1 Introduction: How Our Behaviour Determines How We React to Uncertainty 9.2 The Fallacy of the Rational Man 9.3 The Conundrum of Bias 9.3.1 Bias and Expert Opinion 9.3.2 Bias and the Determination of the Future 9.3.3 Bias and the Media, Bias Clusters, and ``Le Defi Objectif´´ 9.4 Cognitive Dissonance 9.4.1 Examples of Cognitive Dissonance 9.5 Anomie (and Alienation) 9.6 Our Behaviour in Relation to Others: Considerations References Chapter 10: How to Mitigate the Impact of the Behavioural Minefield 10.1 Introduction 10.2 Counteracting Biases 10.3 Digital Disinformation, Media Literacy, and Fact-checking 10.3.1 The Finnish Approach 10.4 Filter Bubbles and Echo Chambers: The Curse of the Selective Algorithm 10.4.1 A New Tool to Help Mitigate the Impact of Filter Bubbles 10.5 How to Reduce Cognitive Dissonance References Part V: Theory into Practice: Reactive and Exploratory Scenarios and Case Studies Chapter 11: Reactive: The Covid-19 Pandemic 11.1 Introduction 11.2 Scenario Proposals in Reaction to the Pandemic Event 11.2.1 Not Just Health 11.2.1.1 Challenge 1: Detecting Incoming Issues in a Fast-Changing Situation 11.2.1.2 Challenge 2: Making Sense of a Dynamic Threat with Limited Information 11.2.1.3 Challenge 3: Making Life-or-Death Decisions 11.2.1.4 Challenge 4: The Art of Strategic Coordination 11.2.1.5 Challenge 5: Keep Worried Publics and Wary Workers On Side 11.3 Reacting to the Experts 11.4 A Note on MTTs 11.4.1 Red Teaming References Chapter 12: An Exploratory Scenario Case Study: Social Mobility and Inequality 12.1 Introduction 12.2 The Problem Statement 12.3 Social Mobility Background 12.4 Why We Are Doing This? 12.5 Core Issues 12.6 What to Do? 12.7 Summary Process Workflow Using Strategic Options Analysis 12.7.1 Basic Process 12.7.2 Breakdown of the Process Phases Applied to Social Mobility 12.8 Conclusion Reference Chapter 13: Achieving Net Zero-The Small Island Developing States (SIDS) Initiative: An Exploratory Investment Decision Suppor... 13.1 Introduction 13.2 Towards a Climate Neutral Strategy 13.3 The Importance of Net Zero in SIDS 13.3.1 What Is Different for Small States? 13.4 Key Objectives (+ Vision and Mission) 13.5 The Investment Structure 13.5.1 Investment Opportunities 13.5.2 Initiative Drivers 13.5.2.1 Driver 1 Bioregional Planning Systems 13.5.2.2 Driver 2 Smart Agriculture 13.5.2.3 Driver 3 (Village 21) Sustainability Communities 13.5.2.4 Driver 4 Carbon Finance/Urban Forests 13.5.2.5 Driver 5 ESG/SDG Mapping Applications 13.5.2.6 Driver 6 Sustainability and Law 13.5.2.7 Driver 7 Wicked Problems 13.5.2.8 Driver 8 Corporate Models 13.5.2.9 Driver 9 Green Technologies 13.5.2.10 Driver 10 Future Opportunities (Focus Areas) 13.6 Supporting Technologies 13.7 Support Facilities 13.7.1 Support Tools 13.7.1.1 Sustainability Toolbox 13.7.1.2 Crypto Basket 13.7.1.3 Sustainability Wrap 13.7.2 Methodologies 13.7.2.1 Unlocking Intellectual Capital 13.7.2.2 Decision-Making Under Deep Uncertainty 13.8 Decision Support Systems: Decision-Making Under Deep Uncertainty (DMDU) 13.8.1 Introduction 13.8.2 An Overview of DMDU Tools and Approaches 13.8.3 Strategic Options Analysis (SOA) 13.9 Conclusions References Chapter 14: Concluding Comments 14.1 Main Structural Components 14.2 Scenarios 14.3 Behavioural Factors 14.4 A Different Perspective on How We Treat Uncertainty Reference Appendices Appendix 1 Robustness Analysis: Rosenhead´s Summary Principles of Robustness Analysis Specifying a Problem Situation for Robustness Analysis Analysing for Robustness Some Comments Applications of Robustness Appendix 2 Causal Layered Analysis (CLA): After Inayatullah Method Process Appendices 3 to 7 Appendix 8 Morphological Analysis/Morphological Distance (MA/MD) Case Study Proof of Concept Case Study 1 Integrating MA and MD Summary The MA Process: Cross Consistency Assessment Analysis Morphological Distance Analysis Results and Discussion Methodology and Rationale The Solution Space Post Cross Consistency Assessment Morphological Distance Analysis Parametric Modelling of Terra Incognita Solutions Results and Discussion Conclusions Appendix 9: Distance Examples in Creative Design & PESTLE Appendix 10 Quadrant Crunching Appendix 11 Analytic Hierarchy Process: AHP Appendix 12: Strategic Options Analysis and Social Mobility Case Study Appendix 13 Social Mobility Workshop: Sample Schedule Glossary Bibliography and Resources Main List of Bibliographical Sources Used in Book Additional Resources