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The Ethos of Error: Analyzing Investigations of Industrial Events
University of Alberta
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Name of Author: Douglas Elliott Sweeney
Title of Thesis: The Ethos of Error: Analyzing Investigations of Industrial Events
Degree: Master of Science
Year this Degree Granted:
Permission is hereby granted to the University of Alberta Library to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only.
The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatever without the author's prior written permission.
Douglas Elliott Sweeney
188 Whiteshield Crescent, Kamloops,
British Columbia, Canada, V2E 1H3
Within the environmental, health and safety disciplines, there is a growing unease in terms of the quality control of event investigations. This thesis proposes a theoretical basis for the analysis of investigations of industrial events, a methodology and a method by which investigative processes can be evaluated. It will be shown that the evaluation of event investigation can reveal insight as to the culture of error - indeed the ethos of error within an organization.
The theory (Decision Errors) is that decisions found to be determinants in industrial events fall in one of three exclusive categories: errors of commission, errors of omission and errors of mistaken belief. The methodology (Cognitive Patterning) asserts that a connection exists between erroneous decisions and the cognitive context within an organization, as a precursor. The method (Boundary Conditions and Decision analysis) establishes the rules and principles behind classifying decision errors.
Table of Contents
Energy and Barrier Analysis.
Management Oversight and Risk Tree (MORT)
Root Cause Analysis.
Event and Causal Factors Analysis.
Chapter 5: Event Causation.
The Present Outlook.
The Propositional Calculus of Causation.
The Language of Causation.
The Symbolism of Causation.
Typology of Decision Events.
Errors of Commission.
Errors of Omission.
Errors of Mistaken Belief
Contemporary Comparative Theories.
Analysis of Investigations – Decision Errors theory.
Analysis of Investigations – A Methodology.
Investigation Analysis – Boundary Condition and Decision Analysis.
Organizational Cognitive Context for Decision Errors.
Chapter 6: Audit Design.
Chapter 7: Audit Protocol
Section 1: Tests for Existence of Process.
The Causal Record.
Section 2a: Tests for Veracity of the Causal Record.
Section 2b: Evaluating the Causal Record.
Section 2c: Boundary Condition and Decision Analysis.
Section 3: Efficacy of the Investigation.
Section 3a: Investigation Methodology Audit Elements:
Section 3b: Investigation Method Audit Elements:
Chapter 8: The Audit Instrument
The Existence of Investigative Process.
The Veracity of Investigative Process.
Evaluating the Efficacy of the Method.
Evaluating the Efficacy of Methodology.
Graphical Aid for The Audit of Causal Records.
Charts for Boundary Condition and Decision Analysis.
Ternary Charts for the Cognitive Patterning Model
Audit Scoring Scheme.
Chapter 9: Discussion.
Event Boundary Condition and Decision Analysis: A Case Study.
A Glimpse of Organizational Culture.
Chapter 10: Field Trial of the Audit and Analysis.
Comments Concerning the Veracity of the Causal Record.
Comments Concerning the Efficacy of Investigations.
Boundary Condition and Decision Analysis.
Chapter 11: The Ethos of Error.
Gemini VIII Mission.
Three Mile Island.
Profile of a System Failure.
What is to be done?.
Summary of System Failure Characteristics (Perrow, 1999f)
Error Inducing Systems.
Decision Error theory as a Predictive Model
The Socialization of Risk.
Human Factors Penalty.
Chapter 12: Conclusions.
Opportunities for Further Research.
Appendix I: Supportive Documents.
Appendix I(a): Investigative Technique Analysis by Livingston, 2001.
Appendix I(b): Investigative Methodology Analysis by Benner
Appendix I©: Investigative Model Analysis by Benner
Appendix II: Completed Field Trial Audit Work Sheet
BCD Analysis: Tailings Line Sanding Incident: July, 2003.
BCD Analysis: Discharge Spool Failure: July, 2003.
BCD Analysis: Electrical Contactor/Switch Explosion: Oct, 2000.
- Chapter 1: Introduction.
- Problem Definition.
- Statement of Significance.
- Chapter 2: Goals and Objectives.
- Chapter 3: Investigation Methodology.
- The Loss Control System Model
- Review of Contemporary Literature.
- The Work Of Livingston et al.:
- The Work Of Benner:
- The Work of Munson:
- The Work of Sklet:
Chapter 4: Event Analysis Models.
Event Causation Models.
Fault Tree Analysis (FTA)
Sequential Timed Event Plotting (STEP)
List of Figures
Figure 1.1: Abstraction illustrating the determinacy existing between accident investigation and operational integrity- - .. 5
Figure 1.2: Abstraction illustrating a feedback mechanism existing between accident investigation and operational integrity- - - 6
Figure 1.3: Schematic illustrating the role of methodology in promoting formalized approaches to accident investigation (Hanks et al., 2003)- . 7
Figure 1.4: Flow chart illustrating the methodology of this thesis- 11
Figure 3.1: Simplification of the Loss Causation model (Bird and Germain, 1986)- - - . 14
Figure 4.1: Conceptualized Fault Tree diagram (Livingston et al., 2001). 27
Figure 4.2: Conceptualized illustration of a Sequential Timed Event Plot diagram (Livingston et al. 2001)- - - 29
Figure 4.3: Typical checklist type query from the Procedures Basic Cause category of a TapRoot analysis (System Improvements Inc., 2004)- - - 30
Figure 4.4: Example from Energy and Barriers Analysis worksheet (DOE 2003)- - - 32
Figure 4.5: Conceptualized illustration of a Management Oversight Risk Tree diagram (DOE, 2003)- - .. 34
Figure 4.6: Conceptualized illustration of an Events and Causal Analysis chart (DOE, 2003)- - - - 37
Figure 4.7: Characterization of investigation analysis models with respect to time- - - .. 38
Figure 4.8: Schematic illustration of the interdependencies between the established ‘system’ analytic models and the more simplex methods- .- - 40
Figure 5.1: Venn diagram illustrating that, D Ç D¢ = f and that,
D È D¢ = S- - - 51
Figure 5.2: Venn diagram illustrating that, D1 Ç D2 = f and that,
D1 È D2 = S- - 52
Figure 5.3: Venn diagram illustrating that, d1 Ç d2 = f and that,
d1 È d2 = S- - . 53
Figure 5.4: Schematic illustrating the nature of decision events on the part of a driver on the verge of exceeding the speed limit and an incipient critical event. - - - 54
Figure 5.5: The Swiss Cheese accident causation model popularized by Reason (1999a)- - .. 60
Figure 5.6: A summary of varieties of unsafe acts as posited by Reason (1999c)- - - 61
Figure 5.7: Cognitive Patterning Model illustrating the inter-relationships of events, their investigation and subsequent analysis- 64
Figure 5.8: Boundary Condition and Decision analysis indicating condition equal potential rings, critical event epicenter, decision traces and condition boundaries- - - .. 65
Figure 5.9: Boundary Condition and Decision analysis illustrating the decisions of one actor as having been determined by process of investigation- - - 66
Figure 5.10: Boundary Conditions and Decision analysis illustrating a fully populated schema of decisions- - - 68
Figure 5.11: Ternary diagram illustrating cognitive dissent, deferral and deficit. The ‘camps’ are arbitrarily demarcated at 50%- .. 70
Figure 5.12: Ternary diagram illustrating an organization having a mixed characterization with respect to decision errors- - 72
Figure 6.1: Tripartite model of the event causation phases- .. 75
Figure 6.2: Minimum structure for investigation reports as required by many regulatory authorities and agencies- .- - 75
Figure 6.3: A model of effort presented against time for the three principle phases of the investigation process- - . 76
Figure 6.4: The blue print or framework for conducting an audit of industrial event investigations- - - 77
Figure 7.1: Sequence of fact-finding phase of the investigative process (Ferry, 1988)- - - .. 94
Figure 7.2: Bead diagram illustrating of the convergence patterns between evidence, data, facts, determinants and recommendations- .. 97
Figure 7.4: An example bead diagram illustrating the one to many relationships of the determinants to its precursors- - 105
Figure 7.5: Unpopulated radar diagram illustrating an event in which eight actors or participants were present- - .. 107
Figure 9.1: Populated radar diagram illustrating which the actors made decisions in error that contributed to the event scenario- - 128
Figure 9.2: Ternary diagram illustrating the distribution of decision errors in the case study (Note that this particular workplace falls marginally within the norm). - - 131
Figure 10.1: Ternary diagram illustrating bi-polar distribution of decision errors. - - 135
Figure 11.1: A schematic illustrating the degree of coupling and interaction across various industry sectors (Perrow, 1999b)- .-. 148
List of Tables
Table 3.1: Conceptualized classification scheme tabulating analytical system against twelve attributes, from (Livingston et al, 2001). Data intentionally omitted. - - 16
Table 3.2: Conceptualized classification scheme tabulating investigative models against ten ranking criteria, from (Benner, 1985). Data intentionally omitted. - - - 17
Table 3.3: Conceptualized classification scheme tabulating investigative methodology against ten ranking criteria, from (Benner, 1985). Data intentionally omitted- - - 18
Table 3.4: Conceptualized classification scheme tabulating investigative methods against six distinguishing characteristics. Data intentionally omitted. - - -21
Table 3.5: Conceptualized classification scheme tabulating analytical methods against six distinguishing characteristics. Data intentionally omitted. - - - 22
Table 5.1: A summary of the three error types, and their defining characteristics- - - .. 62
Table 7.1: A classification scheme based upon varying organizational imperatives respecting accident investigation- - - 84
Table 7.2: List of recognized methodologies used to date (Ferry, 1988). - - - 109
Table 9.1: A table indicating the distribution of error ‘types’ as produced by the Boundary Condition and Decision analysis- - .- 130
Table 11.2: Table summarizing the event characteristics of system failures (Perrow, 1999e)- - .- 155
Table 11.3: Complex versus linear and tight versus loose coupling parameters, (Perrow, 1999f)- - - . 156