{"product_id":"managing-risk-9780470699768","title":"Managing Risk","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThe human element is the principle cause of incidents and accidents in all technology industries; hence it is evident that an understanding of the interaction between humans and technology is crucial to the effective management of risk. Despite this, no tested model that explicitly and quantitatively includes the human element in risk prediction is currently available.  \u003cp\u003e\u003ci\u003eManaging Risk: the Human Element\u003c\/i\u003e combines descriptive and explanatory text with theoretical and mathematical analysis, offering important new concepts that can be used to improve the management of risk, trend analysis and prediction, and hence affect the accident rate in technological industries. It uses examples of major accidents to identify common causal factors, or echoes, and argues that the use of specific experience parameters for each particular industry is vital to achieving a minimum error rate as defined by mathematical prediction. New ideas for the perception, calculation and prediction of risk are\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"An excellently produced book with over 500 pages of detailed information on the management of risk and the avoidance of accidents.\" (\u003ci\u003eAMEC\u003c\/i\u003e, November 2008)\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eContents  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eAbout the Authors\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e \u003cb\u003ePreface\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eAcknowledgements\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eDefi nitions of Risk and Risk Management\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eIntroduction: The Art of Prediction and the Creation of Order\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Risk and Risk Management  \u003c\/p\u003e\u003cp\u003e Defi ning Risk  \u003c\/p\u003e\u003cp\u003e Managing Risk: Our Purpose, Plan and Goals  \u003c\/p\u003e\u003cp\u003e Recent Tragic Outcomes  \u003c\/p\u003e\u003cp\u003e Power Blackouts, Space Shuttle Losses, Concorde Crashes, Chernobyl, Three Mile Island and More . . .  \u003c\/p\u003e\u003cp\u003e How Events and Disasters Evolve in a Phased Development: The Human Element  \u003c\/p\u003e\u003cp\u003e Our Values at Risk: The Probable Improvement  \u003c\/p\u003e\u003cp\u003e Probably or Improbably Not  \u003c\/p\u003e\u003cp\u003e How this Book is Organised  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eTechnical Summary\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Defi ning the Past Probability  \u003c\/p\u003e\u003cp\u003e Predicting Future Risk: Sampling from the Jar of Life  \u003c\/p\u003e\u003cp\u003e A Possible Future: Defi ning the Posterior Probability  \u003c\/p\u003e\u003cp\u003e The Engineers Have an Answer: Reliability  \u003c\/p\u003e\u003cp\u003e Drawing from the Jar of Life: The Hazard Function and Species Extinction  \u003c\/p\u003e\u003cp\u003e Experiencing Failure: Engineering and Human Risk and Reliability  \u003c\/p\u003e\u003cp\u003e Experience Space  \u003c\/p\u003e\u003cp\u003e Managing Safely: Creating Order out of Disorder Using Safety Management Systems  \u003c\/p\u003e\u003cp\u003e Describing the Indescribable: Top-Down and Bottom-Up  \u003c\/p\u003e\u003cp\u003e What an Observer will Observe and the Depth of our Experience  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e1 The Universal Learning Curve\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Predicting Tragedies, Accidents and Failures: Using the Learning Hypothesis  \u003c\/p\u003e\u003cp\u003e The Learning Hypothesis: The Market Place of Life  \u003c\/p\u003e\u003cp\u003e Learning in HTSs: The Way a Human Learns  \u003c\/p\u003e\u003cp\u003e Evidence of Risk Reduction by Learning  \u003c\/p\u003e\u003cp\u003e Evidence of Learning from Experience: Case Studies  \u003c\/p\u003e\u003cp\u003e Evidence of Learning in Economics  \u003c\/p\u003e\u003cp\u003e Evidence of Learning in Engineering and Architecture: The Costs of Mistakes  \u003c\/p\u003e\u003cp\u003e Learning in Technology: the Economics of Reducing Costs  \u003c\/p\u003e\u003cp\u003e Evidence of Learning Skill and Risk Reduction in the Medical Profession: Practice Makes Almost Perfect  \u003c\/p\u003e\u003cp\u003e Learning in HTSs: The Recent Data Still Agrees  \u003c\/p\u003e\u003cp\u003e The Equations That Describe the Learning Curve  \u003c\/p\u003e\u003cp\u003e Zero Defects and Reality  \u003c\/p\u003e\u003cp\u003e Predicting Failures: The Human Bathtub  \u003c\/p\u003e\u003cp\u003e Experience Space: The Statistics of Managing Safety and of Observing Accidents  \u003c\/p\u003e\u003cp\u003e Predicting the Future Based on Past Experience: The Prior Ignorance  \u003c\/p\u003e\u003cp\u003e Future Events: the Way Forward Using Learning Probabilities  \u003c\/p\u003e\u003cp\u003e The Wisdom of Experience and Inevitability  \u003c\/p\u003e\u003cp\u003e The Last, First or Rare Event  \u003c\/p\u003e\u003cp\u003e Conclusions and Observations: Predicting Accidents  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e2 The Four Echoes\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Power Blackouts, Space Shuttle Losses, Concorde Crashes, and the Chernobyl and Three Mile Island Accidents  \u003c\/p\u003e\u003cp\u003e The Combination of Events  \u003c\/p\u003e\u003cp\u003e The Problem Is the Human Element  \u003c\/p\u003e\u003cp\u003e The Four Echoes Share the Same Four Phases  \u003c\/p\u003e\u003cp\u003e The First Echo: Blackout of the Power Grid  \u003c\/p\u003e\u003cp\u003e Management’s Role  \u003c\/p\u003e\u003cp\u003e The First Echo: Findings  \u003c\/p\u003e\u003cp\u003e Error State Elimination  \u003c\/p\u003e\u003cp\u003e The Second Echo: Columbia\/Challenger  \u003c\/p\u003e\u003cp\u003e The Results of the Inquiry: Prior Knowledge  \u003c\/p\u003e\u003cp\u003e The Second Echo: The Four Phases  \u003c\/p\u003e\u003cp\u003e Management’s Responsibility  \u003c\/p\u003e\u003cp\u003e Error State Elimination  \u003c\/p\u003e\u003cp\u003e The Third Echo: Concorde Tires and SUVs  \u003c\/p\u003e\u003cp\u003e Tire Failures: the Prior Knowledge  \u003c\/p\u003e\u003cp\u003e The Third Echo: The Four Phases  \u003c\/p\u003e\u003cp\u003e Management’s Responsibility  \u003c\/p\u003e\u003cp\u003e Error State Elimination  \u003c\/p\u003e\u003cp\u003e The Fourth Echo: Chernobyl  \u003c\/p\u003e\u003cp\u003e The Chernobyl Accident: An Echo of Three Mile Island  \u003c\/p\u003e\u003cp\u003e The Consequences  \u003c\/p\u003e\u003cp\u003e Echoes of Three Mile Island  \u003c\/p\u003e\u003cp\u003e The Causes  \u003c\/p\u003e\u003cp\u003e Error State Elimination  \u003c\/p\u003e\u003cp\u003e The Fourth Echo: The Four Phases  \u003c\/p\u003e\u003cp\u003e Regulatory Environment and Practices  \u003c\/p\u003e\u003cp\u003e Case study: Regulation in Commercial Aviation  \u003c\/p\u003e\u003cp\u003e \u003ci\u003ea) Regulations Development\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003eb) Compliance Standards\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003ec) Accident Investigation\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e Addressing Human Error  \u003c\/p\u003e\u003cp\u003e Management Responsibilities  \u003c\/p\u003e\u003cp\u003e Designing to Reduce Risk and the Role of Standards  \u003c\/p\u003e\u003cp\u003e Conclusion and Echoes: Predicting the Unpredictable  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e3 Predicting Rocket Risks and Refi nery Explosions: Near Misses, Shuttles, Safety and Anti-Missile Defence Systems Effectiveness\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Learning from Near Misses and Prior Knowledge  \u003c\/p\u003e\u003cp\u003e Problems in Quantifying Risk: Predicting the Risk for the Next Shuttle Mission  \u003c\/p\u003e\u003cp\u003e Estimating a Possible Range of Likelihoods  \u003c\/p\u003e\u003cp\u003e Learning from Experience: Maturity Models for Future Space Mission Risk  \u003c\/p\u003e\u003cp\u003e Technology versus Technology  \u003c\/p\u003e\u003cp\u003e Missiles Risks over London: The German Doodlebug  \u003c\/p\u003e\u003cp\u003e Launching Missile Risk  \u003c\/p\u003e\u003cp\u003e The Number of Tests Required  \u003c\/p\u003e\u003cp\u003e Estimating the Risk of a Successful Attack and How Many Missiles We Must Fire  \u003c\/p\u003e\u003cp\u003e Uncertainty in the Risk of Failing to Intercept  \u003c\/p\u003e\u003cp\u003e What Risk Is There of a Missile Getting Through: Missing the Missile  \u003c\/p\u003e\u003cp\u003e Predicting the Risk of Industrial Accidents: The Texas City Refinery Explosion  \u003c\/p\u003e\u003cp\u003e From Lagging to Leading: Safety Analysis and Safety Culture  \u003c\/p\u003e\u003cp\u003e Missing Near Misses  \u003c\/p\u003e\u003cp\u003e What these Risk Estimates Tell Us: The Common Sense Echo  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e4 The Probability of Human Error: Learning in Technological Systems\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e What We Must Predict  \u003c\/p\u003e\u003cp\u003e The Probability Linked to the Rate of Errors  \u003c\/p\u003e\u003cp\u003e The Defi nition of Risk Exposure and the Level of Attainable Perfection  \u003c\/p\u003e\u003cp\u003e Comparison to Conventional Social Science and Engineering Failure and Outcome Rate Formulations  \u003c\/p\u003e\u003cp\u003e The Learning Probabilities and the PDFs  \u003c\/p\u003e\u003cp\u003e The Initial Failure Rate and its Variation with Experience  \u003c\/p\u003e\u003cp\u003e The ‘Best’ MERE Risk Values  \u003c\/p\u003e\u003cp\u003e Maximum and Minimum Likely Outcome Rates  \u003c\/p\u003e\u003cp\u003e Standard Engineering Reliability Models Compared to the MERE Result  \u003c\/p\u003e\u003cp\u003e Future Event Estimates: The Past Predicts the Future  \u003c\/p\u003e\u003cp\u003e Statistical Bayesian-Type Estimates: The Impact of Learning  \u003c\/p\u003e\u003cp\u003e Maximum and Minimum Likelihood  \u003c\/p\u003e\u003cp\u003e Comparison to Data: The Probability of Failure and Human Error  \u003c\/p\u003e\u003cp\u003e Comparison of the MERE Result to Human Reliability Analysis  \u003c\/p\u003e\u003cp\u003e Implications for Generalised Risk Prediction  \u003c\/p\u003e\u003cp\u003e Conclusions: The Probable Human Risk  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e5 Eliminating Mistakes: The Concept of Error States\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e A General Accident Theory: Error States and Safety Management  \u003c\/p\u003e\u003cp\u003e The Physics of Errors  \u003c\/p\u003e\u003cp\u003e The Learning Hypothesis and the General Accident Theory  \u003c\/p\u003e\u003cp\u003e Observing Outcomes  \u003c\/p\u003e\u003cp\u003e A Homage to Boltzmann: Information from the Grave  \u003c\/p\u003e\u003cp\u003e The Concept of Depth of Experience and the Theory of Error States  \u003c\/p\u003e\u003cp\u003e The Fundamental Postulates of Error State Theory  \u003c\/p\u003e\u003cp\u003e The Information in Error States: Establishing the Risk Distribution  \u003c\/p\u003e\u003cp\u003e The Exponential Distribution of Outcomes, Risk and Error States  \u003c\/p\u003e\u003cp\u003e The Total Number of Outcomes  \u003c\/p\u003e\u003cp\u003e The Observed Rate and the Minimum Number of Outcomes  \u003c\/p\u003e\u003cp\u003e Accumulated Experience Measures and Learning Rates  \u003c\/p\u003e\u003cp\u003e The Average Rate  \u003c\/p\u003e\u003cp\u003e Analogy and Predictions: Statistical Error Theory and Learning Model Equivalence  \u003c\/p\u003e\u003cp\u003e The Infl uence of Safety Management and Regulations: Imposing Order on Disorder  \u003c\/p\u003e\u003cp\u003e The Risk of Losing a Ship  \u003c\/p\u003e\u003cp\u003e Distribution Functions  \u003c\/p\u003e\u003cp\u003e The Most Probable and Minimum Error Rate  \u003c\/p\u003e\u003cp\u003e Learning Rates and Experience Intervals: The Universal Learning Curve  \u003c\/p\u003e\u003cp\u003e Reducing the Risk of a Fatal Aircraft Accident: the Infl uence of Skill and Experience  \u003c\/p\u003e\u003cp\u003e Conclusions: A New Approach  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e6 Risk Assessment: Dynamic Events and Financial Risks\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Future Loss Rate Prediction: Ships and Tsunamis  \u003c\/p\u003e\u003cp\u003e Predicted Insurance Rates for Shipping Losses: Historical Losses  \u003c\/p\u003e\u003cp\u003e The Premium Equations  \u003c\/p\u003e\u003cp\u003e Financial Risk: Dynamic Loss and Premium Investments  \u003c\/p\u003e\u003cp\u003e Numerical Example  \u003c\/p\u003e\u003cp\u003e Overall Estimates of Shipping Loss Fraction and Insurance Inspections  \u003c\/p\u003e\u003cp\u003e The Loss Ratio: Deriving the Industrial Damage Curves  \u003c\/p\u003e\u003cp\u003e Making Investment Decisions: Information Drawing from the Jar of Life  \u003c\/p\u003e\u003cp\u003e Information Entropy and Minimum Risk  \u003c\/p\u003e\u003cp\u003e Progress and Learning in Manufacturing  \u003c\/p\u003e\u003cp\u003e Innovation in Technology for the Least Product Price and Cost: Reductions During Technological Learning  \u003c\/p\u003e\u003cp\u003e Cost Reduction in Manufacturing and Production: Empirical Elasticity ‘Power Laws’ and Learning Rates  \u003c\/p\u003e\u003cp\u003e A New General Formulation for Unit Cost Reduction in Competitive Markets: the Minimum Cost According to a Black-Scholes Formulation  \u003c\/p\u003e\u003cp\u003e Universal Learning Curve: Comparison to the Usual Economic Power Laws  \u003c\/p\u003e\u003cp\u003e The Learning Rate \u003ci\u003eb\u003c\/i\u003e-Value ‘Elasticity’ Exponent Evaluated  \u003c\/p\u003e\u003cp\u003e Equivalent Average Total Cost \u003ci\u003eb\u003c\/i\u003e-Value Elasticity  \u003c\/p\u003e\u003cp\u003e Profi t Optimisation to Exceed Development Cost  \u003c\/p\u003e\u003cp\u003e The Data Validate the Learning Theory  \u003c\/p\u003e\u003cp\u003e \u003ci\u003ea) Aircraft Manufacturing Costs Estimate Case\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003eb) Photovoltaic Case\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003ec) Air Conditioners Case\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003ed) Ethanol Prices Case\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003ee) Windpower Case\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003ef) Gas Turbine Power Case\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003eg) The Progress Curve for Manufacturing\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e Non-Dimensional UPC and Market Share  \u003c\/p\u003e\u003cp\u003e Conclusions: Learning to Improve and Turning Risks into Profits  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e7 Safety and Risk Management Systems: the Fifth Echoes\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Safety Management Systems: Creating Order Out of Disorder  \u003c\/p\u003e\u003cp\u003e Workplace Safety: The Four Rights, Four Wrongs and Four Musts  \u003c\/p\u003e\u003cp\u003e Acceptable Risk: Designing for Failure and Managing for Success  \u003c\/p\u003e\u003cp\u003e Managing and Risk Matrices  \u003c\/p\u003e\u003cp\u003e Organisational Factors and Learning  \u003c\/p\u003e\u003cp\u003e A Practical ‘Safety Culture’ Example: The Fifth Echo  \u003c\/p\u003e\u003cp\u003e Safety Culture and Safety Surveys: The Learning Paradox  \u003c\/p\u003e\u003cp\u003e Never Happening Again: Perfect Learning  \u003c\/p\u003e\u003cp\u003e Half a World Apart: Copying the Same Factors  \u003c\/p\u003e\u003cp\u003e Using a Bucket: Errors in Mixing at the JCO Plant  \u003c\/p\u003e\u003cp\u003e Using a Bucket: Errors in Mixing at the Kean Canyon Explosives Plant  \u003c\/p\u003e\u003cp\u003e The Prediction and Management of Major Hazards: Learning from SMS Failures  \u003c\/p\u003e\u003cp\u003e Learning Environments and Safety Cultures: The Desiderata of Desires  \u003c\/p\u003e\u003cp\u003e Safety Performance Measures: Indicators and Balanced Scorecards  \u003c\/p\u003e\u003cp\u003e Safety and Performance Indicators: Measuring the Good  \u003c\/p\u003e\u003cp\u003e Human Error Rates Passing Red Lights, Runway Incursions and Near Misses  \u003c\/p\u003e\u003cp\u003e Risk Informed Regulation and Degrees of Goodness: How Green is Green?  \u003c\/p\u003e\u003cp\u003e Modelling and Predicting Event Rates and Learning Curves Using Accumulated Experience  \u003c\/p\u003e\u003cp\u003e Using the Past to Predict the Future: How Good is Good?  \u003c\/p\u003e\u003cp\u003e Reportable Events  \u003c\/p\u003e\u003cp\u003e Scrams and Unplanned Shutdowns  \u003c\/p\u003e\u003cp\u003e Common Cause Events and Latent Errors  \u003c\/p\u003e\u003cp\u003e Performance Improvement: Case-by-Case  \u003c\/p\u003e\u003cp\u003e Lack of Risk Reduction: Medical Adverse Events and Deaths  \u003c\/p\u003e\u003cp\u003e New Data: Sentinel Events, Deaths and Blood Work  \u003c\/p\u003e\u003cp\u003e Medication Errors in Health Care  \u003c\/p\u003e\u003cp\u003e Organisational Learning and Safety Culture: the ‘\u003ci\u003eH\u003c\/i\u003e-Factor’  \u003c\/p\u003e\u003cp\u003e Risk Indicator Data Analysis: A Case Study  \u003c\/p\u003e\u003cp\u003e Meeting the Need to \u003ci\u003eMeasure\u003c\/i\u003e Safety Culture: the Hard and the Soft Elements  \u003c\/p\u003e\u003cp\u003e Creating Order from Disorder  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e8 Risk Perception: Searching for the Truth Among all the Numbers\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Perceptions and Predicting the Future: Risk Acceptance and Risk Avoidance  \u003c\/p\u003e\u003cp\u003e Fear of the Unknown: The Success Journey into What We Do or Do Not Accept  \u003c\/p\u003e\u003cp\u003e A Possible Explanation of Risk Perception: Comparisons of Road and Rail Transport  \u003c\/p\u003e\u003cp\u003e How Do We Judge the Risk?  \u003c\/p\u003e\u003cp\u003e Linking Complexity, Order, Information Entropy and Human Actions  \u003c\/p\u003e\u003cp\u003e Response Times, Learning Data and the Universal Laws of Practice  \u003c\/p\u003e\u003cp\u003e The Number and Distribution of Outcomes: Comparison to Data  \u003c\/p\u003e\u003cp\u003e Risk Perception: Railways  \u003c\/p\u003e\u003cp\u003e Risk Perception: Coal Mining  \u003c\/p\u003e\u003cp\u003e Risk Perception: Nuclear Power in Japan  \u003c\/p\u003e\u003cp\u003e Risk Perception: Rare Events and Risk Rankings  \u003c\/p\u003e\u003cp\u003e Predicting the Future Number of Outcomes  \u003c\/p\u003e\u003cp\u003e A Worked Example: Searching out and Analysing Data for Oil Spills  \u003c\/p\u003e\u003cp\u003e Typical Worksheet  \u003c\/p\u003e\u003cp\u003e Plotting the Data  \u003c\/p\u003e\u003cp\u003e Fitting a Learning Curve  \u003c\/p\u003e\u003cp\u003e Challenging Zero Defects  \u003c\/p\u003e\u003cp\u003e Comparison of Oil Spills to other Industries  \u003c\/p\u003e\u003cp\u003e Predicting the Future: the Probability and Number of Spills  \u003c\/p\u003e\u003cp\u003e Observations on this Oil Spill Case  \u003c\/p\u003e\u003cp\u003e Knowing What We Do Not Know: Fear and Managing the Risk of the Unknown  \u003c\/p\u003e\u003cp\u003e White and Black Paradoxes: Known Knowns and Unknown Unknowns  \u003c\/p\u003e\u003cp\u003e The Probability of the Unknowns: Learning from What We Know  \u003c\/p\u003e\u003cp\u003e The Existence of the Unknown: Failures in High Reliability Systems  \u003c\/p\u003e\u003cp\u003e The Power of Experience: Facing Down the Fear of the Unknown  \u003c\/p\u003e\u003cp\u003e Terrorism, Disasters and Pandemics: Real, Acceptable and Imaginary Risks  \u003c\/p\u003e\u003cp\u003e Estimating Personal Risk of Death: Pandemics and Infectious Diseases  \u003c\/p\u003e\u003cp\u003e Sabotage: Vulnerabilities, Critical Systems and the Reliability of Security Systems  \u003c\/p\u003e\u003cp\u003e What Is the Risk?  \u003c\/p\u003e\u003cp\u003e The Four Quadrants: Implications of Risk for Safety Management Systems  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003e9 I Must Be Learning\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Where We Have Come From  \u003c\/p\u003e\u003cp\u003e What We Have Learned  \u003c\/p\u003e\u003cp\u003e What We Have Shown  \u003c\/p\u003e\u003cp\u003e Legal, Professional and Corporate Implications for the Individual  \u003c\/p\u003e\u003cp\u003e Just Give Me the Facts  \u003c\/p\u003e\u003cp\u003e Where We Are Going  \u003c\/p\u003e\u003cp\u003e Reference  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eNomenclature\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eAppendices:\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Appendix A: The ‘Human Bathtub’: Predicting the Future Risk  \u003c\/p\u003e\u003cp\u003e The Differential Formulation for the Number of Outcomes  \u003c\/p\u003e\u003cp\u003e The Future Probability  \u003c\/p\u003e\u003cp\u003e Insuffi cient Learning  \u003c\/p\u003e\u003cp\u003e Appendix B: The Most Risk, or Maximum Likelihood, for the Outcome (Failure or Error) Rate while Learning  \u003c\/p\u003e\u003cp\u003e The Most or Least Likely Outcome Rate  \u003c\/p\u003e\u003cp\u003e The Maximum and Minimum Risk: The Two Solutions  \u003c\/p\u003e\u003cp\u003e Low Rates and Rare Events  \u003c\/p\u003e\u003cp\u003e The Limits of Maximum and Minimum Risk: The Two Solutions  \u003c\/p\u003e\u003cp\u003e Common Sense: The Most Risk at the Least Experience and the Least Risk as the First Outcome Decreases with Experience  \u003c\/p\u003e\u003cp\u003e Typical Trends in Our Most Likely Risk  \u003c\/p\u003e\u003cp\u003e The Distribution with Depth of Experience  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e Appendix C: Transcripts of the Four Echoes  \u003c\/p\u003e\u003cp\u003e Power Blackout, Columbia Space Shuttle loss, Concorde Crash and Chernobyl Accident  \u003c\/p\u003e\u003cp\u003e The Combination of Events  \u003c\/p\u003e\u003cp\u003e The Four Echoes Share the Same Four Phases  \u003c\/p\u003e\u003cp\u003e Appendix. Blackout Chronology and the Dialog from Midday 14 August 2003  \u003c\/p\u003e\u003cp\u003e The Second Echo: Columbia\/Challenger  \u003c\/p\u003e\u003cp\u003e Appendix: Shuttle Dialog and Transcripts  \u003c\/p\u003e\u003cp\u003e The Third Echo: Concorde Tires and SUVs  \u003c\/p\u003e\u003cp\u003e Appendix: Dialog for the Concorde Crash  \u003c\/p\u003e\u003cp\u003e The Fourth Echo: TMI\/Chernobyl  \u003c\/p\u003e\u003cp\u003e Appendix: Chronology and Transcripts of the Chernobyl Reactor Unit 4 Accident  \u003c\/p\u003e\u003cp\u003e Conclusion and Echoes: Predicting the Unpredictable  \u003c\/p\u003e\u003cp\u003e Appendix D: The Four Phases: Fuel Leak Leading to Gliding a Jet in to Land without any Engine Power  \u003c\/p\u003e\u003cp\u003e The Bare Facts and the Sequence  \u003c\/p\u003e\u003cp\u003e The Four Phases  \u003c\/p\u003e\u003cp\u003e Flight Crew Actions  \u003c\/p\u003e\u003cp\u003e \u003ci\u003eInitial Recognition of the Fuel Loss\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003eCrew Reaction to the Fuel Imbalance Advisory (05:33–05:45)\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003eCrew Reaction to the Continued Fuel Loss (05:45–06:10)\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003eCrew Reaction to the (Two) Engine Failures\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e Appendix E: The Four Phases of a Midair Collision  \u003c\/p\u003e\u003cp\u003e The Bare Facts  \u003c\/p\u003e\u003cp\u003e The Four Phases  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e Appendix F: Risk From the Number of Outcomes We Observe: How Many Are There?  \u003c\/p\u003e\u003cp\u003e The Number of Outcomes: The Hypergeometric Distribution  \u003c\/p\u003e\u003cp\u003e Few Outcomes and many Non-Outcomes: The Binomial and Poisson Distributions  \u003c\/p\u003e\u003cp\u003e The Number of Outcomes: In the Limit  \u003c\/p\u003e\u003cp\u003e The Perfect Learning Limit: Learning from Non-Outcomes  \u003c\/p\u003e\u003cp\u003e The Relative Change in Risk When Operating Multiple Sites  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e Appendix G: Mixing in a Tank: The D.D. Williamson Vessel Explosion  \u003c\/p\u003e\u003cp\u003e Errors in Mixing in a Tank at the Caramel Factory: The Facts  \u003c\/p\u003e\u003cp\u003e The Prior Knowledge  \u003c\/p\u003e\u003cp\u003e Another Echo  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e Appendix H: Never Happening Again  \u003c\/p\u003e\u003cp\u003e The Risk of an Echo, or of a Repeat Event  \u003c\/p\u003e\u003cp\u003e The Matching Probability for an Echo  \u003c\/p\u003e\u003cp\u003e The Impact of Learning and Experience on Managing the Risk of Repeat Events  \u003c\/p\u003e\u003cp\u003e The Theory of Evidence: Belief and Risk Equivalence  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e Appendix I: A Heuristic Organisational Risk Stability Criterion  \u003c\/p\u003e\u003cp\u003e Order and Disorder in Physical and Management Systems  \u003c\/p\u003e\u003cp\u003e Stability Criterion  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e Appendix J: New Laws of Practice for Learning and Error Correction  \u003c\/p\u003e\u003cp\u003e Individual Learning and Practice  \u003c\/p\u003e\u003cp\u003e Comparison to Error Reduction Data  \u003c\/p\u003e\u003cp\u003e Comparison to Response Time Data and the Consistent Law of Practice  \u003c\/p\u003e\u003cp\u003e Reconciling the Laws  \u003c\/p\u003e\u003cp\u003e Conclusions  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e Appendix K: Predicting Rocket Launch Reliability – Case Study  \u003c\/p\u003e\u003cp\u003e Summary  \u003c\/p\u003e\u003cp\u003e Theory of Rocket Reliability  \u003c\/p\u003e\u003cp\u003e \u003ci\u003ea) Unknown Total Number of Launches and Failures\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e \u003ci\u003eb) Known Total Number of Launches and Failures\u003c\/i\u003e  \u003c\/p\u003e\u003cp\u003e Results  \u003c\/p\u003e\u003cp\u003e Measures of Experience  \u003c\/p\u003e\u003cp\u003e Comparsion to World Data  \u003c\/p\u003e\u003cp\u003e Predicting the Probability of Failure  \u003c\/p\u003e\u003cp\u003e Statistical Estimates of the Failure Probability for the Very ‘next’ launch  \u003c\/p\u003e\u003cp\u003e Independent Validation of the MERE Launch Failure Curve  \u003c\/p\u003e\u003cp\u003e Observations  \u003c\/p\u003e\u003cp\u003e References  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eIllustrations\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e Pipeline Spill and Fire  \u003c\/p\u003e\u003cp\u003e Train Crash Due to SPAD  \u003c\/p\u003e\u003cp\u003e Space Shuttle Columbia  \u003c\/p\u003e\u003cp\u003e Chemical Explosion  \u003c\/p\u003e\u003cp\u003e Bayes, Laplace and Bernouli  \u003c\/p\u003e\u003cp\u003e Kean Canyon Explosion  \u003c\/p\u003e\u003cp\u003e Boltzmann’s Grave  \u003c\/p\u003e\u003cp\u003e Quebec Overpass  \u003c\/p\u003e\u003cp\u003e \u003cb\u003eIndex\u003c\/b\u003e \u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":51455984337239,"sku":"9780470699768","price":121.46,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470699768.jpg?v=1755033322","url":"https:\/\/bookcurl.com\/products\/managing-risk-9780470699768","provider":"Book Curl","version":"1.0","type":"link"}