Tools for Safety Management: Considerations for the Design ......Tools for Safety Management: Considerations for the Design of Occurrence Data Maury Hill Manager, Macro Analysis Transportation

Tools for Safety Management:Tools for Safety Management:Considerations for the DesignConsiderations for the Design

of Occurrence Dataof Occurrence Data

Maury HillManager, Macro Analysis

Transportation Safety Board of Canada

ACCIDENT INVESTIGATIONACCIDENT INVESTIGATIONTraditional ApproachTraditional Approach


u Focussed on proximate cause...(often unsafeacts by operator)



u Attached blame for failure to assess risks




u Accident reports depicted:





WHAT?WHAT? WHEN?WHEN? WHO?WHO?

WHY?WHY? HOW?HOW?






WHY?WHY? HOW?HOW?

u Accident reports seldom depicted:






WHY?WHY? HOW?HOW?

u Accident reports seldom depicted:

Applied to data collection as well Applied to data collection as well

TSB APPROACHTSB APPROACH


u Advance Safety through the identification andvalidation of Safety Deficiencies that are foundthrough the investigation process



u Focus is on Why and How




u Communicate to the authorities who can besteffect change such as:

• the regulator

• the transportation industry





• the regulator


u





• the regulator


u

Changes to database

OccurrenceAssessmentMacro

Analysis

Why Collect?Why Collect?Why Collect?Why Collect?


Analysis



Analysis

Why Collect?Why Collect?

OccurrenceAssessment

Source of Data

MacroAnalysis

By Regulation

By Regulation


Source of Data

MacroAnalysis

By Regulation


Source of Data

MacroAnalysis

By Regulation

Investigation


Source of Data

MacroAnalysis

By Regulation

Investigation


Source of Data

MacroAnalysis

By Regulation

Investigation



u data are required to assess problem size andcharacteristics, to establish trends, and todecide between and evaluate risk controloptions.



u data are required to assess problem size andcharacteristics, to establish trends, and todecide between and evaluate risk controloptions.

u a reporting system can provide a bank of datasufficient to establish broad accident categoriesand provide detailed information on accidentcausation.



u Occurrence most often have happened before





• Herald of Free Enterprise




• L1011 O-Rings - 11 in past 2 years




• L1011 O-Rings - 11 in past 2 years

• Three Mile Island

What to CollectWhat to CollectWhat to CollectWhat to Collect

What to CollectWhat to Collect

u “... Data held for any purpose or purposes shallbe adequate, relevant and not excessive inrelation to that purpose or those purposes.”

Data Protection Act, United Kingdom

VOLTAIREVOLTAIRE

VOLTAIREVOLTAIRE

“There are no such things as accidents.

VOLTAIREVOLTAIRE

“There are no such things as accidents.

What we call by that name is the effectof some cause which we do not see.”

DefinitionsDefinitions


u Restrictive definitions of reportable occurrenceshave a profound impact on our work.


u Restrictive definitions of reportable occurrenceshave a profound impact on our work.

u All definitions are of necessity restrictive:- simple expediency- expressions of limited professional interest

Accident causation is layeredlike an onion…….

• Individual performance• Crew performance• Design & Operating Standards• Supervision and training• Company safety management• Regulatory compliance


Accident causation is layeredlike an onion…….


Each layer representsa set of safety conditions.

Occurrence

Initial Assessment

Investigation Methodology

Investigate

Occurrence Inadequate Defence

Unsafe ActPreconditions

L.M Deficiencies

Fallible Decisions


Investigate



L.M Deficiencies

Fallible Decisions

Occurrence

Initial Assessment


Investigate



L.M Deficiencies

Fallible Decisions

Data Collection



L.M Deficiencies

Fallible Decisions

Occurrence

Initial Assessment


Investigate



L.M Deficiencies

Fallible Decisions

Data Collection

Occurrence

Initial Assessment

Data Collection

Occurrence EventsEvents & Factors Analysis

Integrated Investigation Process


Investigate

D C

UnsafeC o n d i t i o n

Lapse

A d a p t a t i o n

Slip

Mis t ake

UnsafeCond i t i on Analysis

E v e n t

Bas ic E r ro r T y p e s

At ten t ion& M e m o r yFa i lu re s

Ski l l -based

UnsafeCondi t ions /U n d e r l y i n gFac to r s

U n s a f e A c t /Dec i s ion

B i a s e sHeuris t ics

Ina t ten t ionOvera t t en t ion

Misapp l i ca t iono f G o o d R u l e sA p p l i c a t i o n o fB a d R u l e s

K n o w l e d g e -b a s e dAdapta t ionsRou t ine &Excep t iona l

Ru le -based&

K n o w l e d g e -b a s e dMis takes

Unin ten t iona lA c t i o n

D C = D e c i s i o n C r i t e r i a

In ten t iona lA c t i o n



Investigate

D C


Lapse

A d a p t a t i o n

Slip

Mis t ake


E v e n t



Ski l l -based







Ru le -based&





Occurrence

Initial Assessment

Data Collection

Occurrence EventsEvents & Factors Analysis



Investigate

D C


Lapse

A d a p t a t i o n

Slip

Mis t ake


E v e n t



Ski l l -based







Ru le -based&





Unsafe Acts/Conditions

Integrated InvestigationIntegrated InvestigationProcessProcess

DC

UnsafeCondition

Lapse

Adaptation

Slip

Mistake

UnsafeCondition Analysis

Event

Basic Error Types

Attention& MemoryFailures

Skill-based

UnsafeConditions/UnderlyingFactors

Unsafe Act/Decision

BiasesHeuristics

InattentionOverattention

Misapplicationof Good RulesApplication ofBad Rules

Knowledge-basedAdaptationsRoutine &Exceptional

Rule-based&

Knowledge-basedMistakes

UnintentionalAction

DC = Decision Criteria

IntentionalAction


DC

UnsafeCondition

Lapse

Adaptation

Slip

Mistake


Event

Basic Error Types


Skill-based


Unsafe Act/Decision

BiasesHeuristics




Rule-based&


UnintentionalAction


IntentionalAction


DC

UnsafeCondition

Lapse

Adaptation

Slip

Mistake


Event

Basic Error Types


Skill-based


Unsafe Act/Decision

BiasesHeuristics




Rule-based&


UnintentionalAction


IntentionalAction


DC

UnsafeCondition

Lapse

Adaptation

Slip

Mistake


Event

Basic Error Types


Skill-based


Unsafe Act/Decision

BiasesHeuristics




Rule-based&


UnintentionalAction


IntentionalAction

Need for TaxonomyNeed for Taxonomy


u Should be founded in science - have constructvalidity, not just face validity



u Should be able to give insight into accidentcausation



u Should be able to give insight into accidentcausation

u Need for taxonomies for error and underlyingfactors

Accident PreventionAccident Prevention

IdentifyIdentifyUnsafe Cond’nsUnsafe Cond’ns

MonitorMonitorProgressProgress

TakeTakeActionAction

RiskRiskCommunicationCommunication

ControlControlOptionsOptions

AssessAssessRiskRisk

ProcessProcess





ProcessProcess

Accident PreventionAccident Prevention

IdentifyIdentifyUnsafe Cond’nsUnsafe Cond’ns

MonitorMonitorProgressProgress





ProcessProcess

Results?Results?

Maybe?Maybe?Maybe?Maybe?

Results?Results?

Maybe?Maybe?

Our commitment to improving aviation safety data

through human factors initiatives will pay a safety dividend?

u “... it is impossible, while designing a database,to anticipate every type of data analysis thatmight be required in the future, (therefore) it isto be anticipated that any database will belacking with respect to its ability to supportmacro analysis projects. The implication of thisis that for most macro analysis projects, itshould be anticipated that some data collectionwill be required.”

u data quality issues

u currency of data

u etc., etc., ….

“Out of this nettle, danger,we pluck this flower, safety.”

William Shakespeare

Documents

Tools for Safety Management: Considerations for the Design ......Tools for Safety Management: Considerations for the Design of Occurrence Data Maury Hill Manager, Macro Analysis Transportation