Managing Risk: The Human Element

Managing Risk: The Human Element......Page 1
Contents......Page 7
About the Authors......Page 15
Preface......Page 17
Acknowledgements......Page 21
Definitions of Risk and Risk Management......Page 23
Risk and Risk Management......Page 31
Defining Risk......Page 32
Managing Risk: Our Purpose, Plan and Goals......Page 34
Power Blackouts, Space ShuttleLosses, Concorde Crashes, Chernobyl, Three Mile Island, and More . . .......Page 36
How Events and Disasters Evolve in a Phased Development: The Human Element......Page 38
Our Values at Risk: The Probable Improvement......Page 40
Probably or Improbably Not......Page 41
How This Book Is Organised......Page 42
References......Page 44
Defining the Past Probability......Page 45
Predicting Future Risk: Sampling from the Jar of Life......Page 46
A Possible Future: Defining the Posterior Probability......Page 51
The Engineers have an Answer: Reliability......Page 52
Drawing from the Jar of Life: The Hazard Function and Species Extinction......Page 53
Experiencing Failure: Engineering and Human Risk and Reliability......Page 55
Experience Space......Page 57
Managing Safely: Creating Order Out of Disorder Using Safety Management Systems......Page 59
Describing the Indescribable: Top-Down and Bottom-Up......Page 60
What an Observer Will Observe and the Depth of Our Experience......Page 61
References......Page 63
Predicting Tragedies, Accidents and Failures: Using the Learning Hypothesis......Page 65
The Learning Hypothesis: The Marketplace of Life......Page 67
Learning in Homo-Technological Systems (HTSs): The Way a Human Learns......Page 69
Evidence of Risk Reduction by Learning......Page 71
Evidence of Learning from Experience: Case Studies......Page 72
Evidence of Learning in Economics......Page 73
Evidence of Learning in Engineering and Architecture: The Costs of Mistakes......Page 74
Learning in Technology: The Economics of Reducing Costs......Page 76
Evidence of Learning Skill and Risk Reduction in the Medical Profession: Practice Makes Almost Perfect......Page 78
Learning in HTSs : The Recent Data Still Agree......Page 80
The Equations That Describe the Learning Curve......Page 82
Zero Defects and Reality......Page 84
Experience Space: The Statistics of Managing Safety and of Observing Accidents......Page 85
Predicting the Future Based on Past Experience: The Prior Ignorance......Page 87
Future Events: The Way Forward Using Learning Probabilities......Page 88
The Last, First or Rare Event......Page 89
Conclusions and Observations: Predicting Accidents......Page 90
References......Page 91
Power Blackouts, Space Shuttle Losses, Concorde Crashes, and the Chernobyl and Three Mile Island Accidents......Page 93
The Combination of Events......Page 94
The Problem Is the Human Element......Page 95
The Four Echoes Share the Same Four Phases......Page 96
The First Echo: Blackout of the Power Grid......Page 97
Management’s Role......Page 99
The First Echo: Findings......Page 101
Error State Elimination......Page 103
The Second Echo: Columbia/Challenger......Page 105
The Results of the Inquiry: Prior Knowledge......Page 106
The Second Echo: The Four Phases......Page 109
Management’s Responsibility......Page 110
Error State Elimination......Page 112
The Third Echo: Concorde Tires and SUVs......Page 113
Tire Failures: The Prior Knowledge......Page 114
Error State Elimination......Page 117
An Echo of Three Mile Island......Page 118
Echoes of Three Mile Island......Page 122
The Causes......Page 123
Error State Elimination......Page 124
Regulatory Environment and Practices......Page 125
a) Regulations Development......Page 126
c) Accident Investigation......Page 127
Addressing Human Error......Page 128
Designing to Reduce Risk and the Role of Standards......Page 129
Conclusion and Echoes: Predicting the Unpredictable......Page 131
References......Page 133
Learning from Near Misses and Prior Knowledge......Page 135
Problems in Quantifying Risk: Predicting the Risk for the Next Shuttle Mission......Page 137
Estimating a Possible Range of Likelihoods......Page 142
Learning from Experience: Maturity Models for Future Space Mission Risk......Page 144
Technology versus Technology......Page 150
Missiles Risks over London: The German Doodlebug......Page 151
Launching Missile Risk......Page 154
The Number of Tests Required......Page 156
Uncertainty in the Risk of Failing to Intercept......Page 158
What Risk Is There of a Missile Getting Through: Missing the Missile......Page 161
Predicting the Risk of Industrial Accidents: The Texas City Refinery Explosion......Page 162
From Lagging to Leading: Safety Analysis and Safety Culture......Page 164
What These Risk Estimates Tell Us: The Common Sense Echo......Page 167
References......Page 168
What We Must Predict......Page 171
The Probability Linked to the Rate of Errors......Page 174
The Definition of Risk Exposure and the Level of Attainable Perfection......Page 176
Comparison to Conventional Social Science and Engineering Failure and Outcome Rate Formulations......Page 177
The Initial Failure Rate and Its Variation with Experience......Page 180
The ‘Best’ MERE Risk Values......Page 183
Standard Engineering Reliability Models Compared to the MERE Result......Page 185
Future Event Estimates: The Past Predicts the Future......Page 187
Statistical Bayesian-Type Estimates: The Impact of Learning......Page 188
Comparison to Data: The Probability of Failure and Human Error......Page 191
Comparison of the MERE Result to Human Reliability Analysis......Page 194
Implications for Generalised Risk Prediction......Page 198
Conclusions: The Probable Human Risk......Page 200
References......Page 201
A General Accident Theory: Error States and Safety Management......Page 203
The Physics of Errors......Page 204
The Learning Hypothesis and the General Accident Theory......Page 206
Observing Outcomes......Page 208
A Homage to Boltzmann: Information from the Grave......Page 211
The Concept of Depth of Experience and the Theory of Error States......Page 214
The Fundamental Postulates of Error State Theory......Page 218
The Information in Error States: Establishing the Risk Distribution......Page 219
The Exponential Distribution of Outcomes, Risk and Error States......Page 222
The Total Number of Outcomes......Page 223
The Observed Rate and the Minimum Number of Outcomes......Page 225
Accumulated Experience Measures and Learning Rates......Page 228
The Average Rate......Page 230
The Influence of Safety Management and Regulations: Imposing Order on Disorder......Page 231
The Risk of Losing a Ship......Page 233
Distribution Functions......Page 235
The Most Probable and Minimum Error Rate......Page 238
Learning Rates and Experience Intervals: The Universal Learning Curve......Page 239
Reducing the Risk of a Fatal Aircraft Accident: The Influence of Skill and Experience......Page 242
Conclusions: A New Approach......Page 245
References......Page 246
6: Risk Assessment: Dynamic Events and Financial Risks......Page 249
Future Loss Rate Prediction: Ships and Tsunamis......Page 251
Predicted Insurance Rates for Shipping Losses: Historical Losses......Page 254
The Premium Equations......Page 255
Financial Risk: Dynamic Loss and Premium Investments......Page 256
Numerical Example......Page 257
Overall Estimates of Shipping Loss Fraction and Insurance Inspections......Page 258
The Loss Ratio: Deriving the Industrial Damage Curves......Page 259
Making Investment Decisions: Information Drawing from the Jar of Life......Page 261
Information Entropy and Minimum Risk......Page 262
Progress and Learning in Manufacturing......Page 263
Innovation in Technology for the Least Product Price and Cost: Reductions During Technological Learning......Page 264
Cost Reduction in Manufacturing and Production: Empirical Elasticity ‘Power Laws’ and Learning Rates......Page 265
A New General Formulation for Unit Cost Reduction in Competitive Markets: The Minimum Cost According to a Black-Scholes Formulation......Page 267
Universal Learning Curve: Comparison to the Usual Economic Power Laws......Page 270
The Learning Rate b-Value ‘Elasticity’ Exponent Evaluated......Page 272
Equivalent Average Total Cost b-Value Elasticity......Page 274
Profit Optimisation to Exceed Development Cost......Page 276
a) Aircraft Manufacturing Costs Estimate Case......Page 277
b) Photovoltaic Case......Page 278
c) Air Conditioners Case......Page 280
d) Ethanol Prices Case......Page 281
e) Windpower Case......Page 282
f) Gas Turbine Power Case......Page 283
g) The Progress Curve for Manufacturing......Page 284
Non-Dimensional UPC and Market Share......Page 286
Conclusions: Learning to Improve and Turning Risks into Profits......Page 289
References......Page 290
Safety Management Systems: Creating Order Out of Disorder......Page 293
Workplace Safety: The Four Rights, Four Wrongs and Four Musts......Page 294
Acceptable Risk: Designing for Failure and Managing for Success......Page 295
Managing and Risk Matrices......Page 299
Organisational Factors and Learning......Page 302
A Practical ‘Safety Culture’ Example: The Fifth Echo......Page 303
Safety Culture and Safety Surveys: The Learning Paradox......Page 308
Never Happening Again: Perfect Learning......Page 310
Half a World Apart: Copying the Same Factors......Page 311
Using a Bucket: Errors in Mixing at the JCO Plant......Page 313
Using a Bucket: Errors in Mixing at the Kean Canyon Explosives Plant......Page 314
The Prediction and Management of Major Hazards: Learning from SMS Failures......Page 316
Learning Environments and Safety Cultures: The Desiderata of Desires......Page 319
Safety Performance Measures: Indicators and Balanced Scorecards......Page 321
Safety and Performance Indicators: Measuring the Good......Page 322
Human Error Rates Passing Red Lights, Runway Incursions and Near Misses......Page 323
Risk Informed Regulation and Degrees of Goodness: How Green Is Green?......Page 324
Modelling and Predicting Event Rates and Learning Curves Using Accumulated Experience......Page 327
Using the Past to Predict the Future: How Good is Good?......Page 329
Reportable Events......Page 330
Scrams and Unplanned Shutdowns......Page 331
Common-Cause Events and Latent Errors......Page 333
Performance Improvement: Case-by-Case......Page 334
Lack of Risk Reduction: Medical Adverse Events and Deaths......Page 335
New Data: Sentinel Events, Deaths and Blood Work......Page 338
Medication Errors in Health Care......Page 343
Organisational Learning and Safety Culture: the ‘H-Factor’......Page 346
Risk Indicator Data Analysis: A Case Study......Page 349
Meeting the Need to Measure Safety Culture: The Hard and the Soft Elements......Page 351
References......Page 354
Perceptions and Predicting the Future: Risk Acceptance and Risk Avoidance......Page 359
Fear of the Unknown: The Success Journey into What We Do or Do Not Accept......Page 363
A Possible Explanation of Risk Perception: Comparisons of Road and Rail Transport......Page 364
How Do We Judge the Risk?......Page 367
Linking Complexity, Order, Information Entropy and Human Actions......Page 368
Response Times, Learning Data and the Universal Laws of Practice......Page 371
The Number and Distribution of Outcomes: Comparison to Data......Page 373
Risk Perception: Railways......Page 375
Risk Perception: Coal Mining......Page 378
Risk Perception: Nuclear Power in Japan......Page 379
Risk Perception: Rare Events and Risk Rankings......Page 382
A Worked Example: Searching Out and Analysing Data for Oil Spills......Page 384
Fitting a Learning Curve......Page 388
Challenging Zero Defects......Page 389
Comparison of Oil Spills to Other Industries......Page 392
Predicting the Future: The Probability and Number of Spills......Page 394
Knowing What We Do Not Know: Fear and Managing the Risk of the Unknown......Page 395
White and Black Paradoxes: Known Knowns and Unknown Unknowns......Page 397
The Probability of the Unknowns: Learning from What We Know......Page 398
The Existence of the Unknown: Failures in High Reliability Systems......Page 400
The Power of Experience: Facing Down the Fear of the Unknown......Page 401
Terrorism, Disasters and Pandemics: Real, Acceptable and Imaginary Risks......Page 403
Estimating Personal Risk of Death: Pandemics and Infectious Diseases......Page 404
Sabotage: Vulnerabilities, Critical Systems and the Reliability of Security Systems......Page 407
The Four Quadrants: Implications of Risk for Safety Management Systems......Page 408
References......Page 410
Where We Have Come From......Page 413
What We Have Learned......Page 414
What We Have Shown......Page 418
Legal, Professional and Corporate Implications for the Individual......Page 419
Just Give Me the Facts......Page 421
Where We are Going......Page 422
Reference......Page 423
Nomenclature......Page 425
Appendices......Page 431
Appendix A: The ‘Human Bathtub’: Predicting the Future Risk......Page 433
The Differential Formulation for the Number of Outcomes......Page 435
The Future Probability......Page 436
Insufficient Learning......Page 438
The Most or Least Likely Outcome Rate......Page 441
The Maximum and Minimum Risk: The Two Solutions......Page 442
Low Rates and Rare Events......Page 443
Common Sense: The Most Risk at the Least Experience, and the Least Risk as the First Outcome Decreases with Experience......Page 444
Typical Trends in Our Most Likely Risk......Page 445
The Distribution with Depth of Experience......Page 447
References......Page 448
The Combination of Events......Page 449
Appendix. Blackout Chronology and the Dialogue from Midday 14 August 2003......Page 450
The Second Echo: Columbia/Challenger......Page 462
Appendix: Shuttle Dialogue and Transcripts......Page 463
The Third Echo: Concorde Tires and SUVs......Page 465
Appendix: Dialogue for the Concorde Crash......Page 466
Appendix: Chronology and Transcripts of the Chernobyl’ Reactor Unit 4 Accident......Page 469
Conclusion and Echoes: Predicting the Unpredictable......Page 474
The Bare Facts and the Sequence......Page 477
The Four Phases......Page 479
Initial Recognition of the Fuel Loss (04:38–05:33)......Page 485
Crew Reaction to the Fuel Imbalance Advisory (05:33–05:45)......Page 486
Crew Reaction to the Continued Fuel Loss (05:45–06:10)......Page 488
Crew Reactions to the (Two) Engine Failures......Page 490
References......Page 493
The Four Phases......Page 495
References......Page 499
Appendix F: Risk from the Number of Outcomes We Observe: How Many are There?......Page 501
The Number of Outcomes: The Hypergeometric Distribution......Page 502
Few Outcomes and Many Non-Outcomes: The Binomial and Poisson Distributions......Page 505
The Number of Outcomes: In the Limit......Page 508
The Perfect Learning Limit: Learning from Non-Outcomes......Page 509
The Relative Change in Risk When Operating Multiple Sites......Page 511
References......Page 512
Errors in Mixing in a Tank at the Caramel Factory: The Facts......Page 513
The Prior Knowledge......Page 514
Another Echo......Page 518
References......Page 520
The Risk of an Echo, or of a Repeat Event......Page 521
The Matching Probability for an Echo......Page 523
The Impact of Learning and Experience on Managing the Risk of Repeat Events......Page 524
The Theory of Evidence: Belief and Risk Equivalence......Page 526
References......Page 527
Order and Disorder in Physical and Management Systems......Page 529
Stability Criterion......Page 530
References......Page 532
Individual Learning and Practice......Page 535
Comparison to Error Reduction Data......Page 536
Comparison to Response Time Data and the Consistent Law of Practice......Page 539
Reconciling the Laws......Page 541
Conclusions......Page 542
References......Page 543
Theory of Rocket Reliability......Page 545
a) Unknown Total Number of Launches and Failures......Page 546
b) Known Total Number of Launches and Failures......Page 547
Results......Page 548
Measures of Experience......Page 549
Comparison to World Data......Page 550
Predicting the Probability of Failure......Page 551
Statistical Estimates of the Failure Probability for the Very ‘Next’ Launch......Page 553
Independent Validation of the MERE Launch Failure Curve......Page 555
References......Page 556
Index......Page 557
Color Plates......Page 571