1. Human Factors in Accident Investigation

2. Introduction
‘To say accidents are due to human failing is like saying falls are due to gravity. It is true but it does not help us prevent them’ Trevor Kletz
Aim today is to present methods that are known to help identify human failure in accident investigation and prevent reoccurrence
Not a black art, a pragmatic and robust process

3. What we expect
Methodical process for gathering information, analysing what went wrong (and right), and learning lessons in order to:
Manage risk
Prevent reoccurrence
Retrospective tool, but can be powerful in promoting change

4. Accident reports What happened Who to When How it happened But not why
Technical myopia
Failure to consider human factors

5. Significance of human factors
Up to 90% of accidents attributable to some degree to human failures
Proportion and significance increasing as technical safety measures improve

6. Human failure taxonomy
Human failures
Intended actions
Unintended actions
Violation - Intended consequences
Errors - Unintended consequences
Mistakes
Lapses
Slips
When the person decided to act without complying with a known rule or procedure
When the person does what they meant to, but should have done something else
When the person forgets to do something
When the person does something, but not what they meant to do

7. Slip, lapse or mistake? Involuntary or non-intentional action No
Was there intention in the action?
Was there prior intention to act? No
Spontaneous or subsidiary action
Yes
Yes
Did the actions proceed as planned?
Unintentional action (slip or lapse) No
Yes
Did the actions achieve their desired end?
Intentional but mistaken action No
Yes
Successful action

8. How to apply Create timeline Identify significant behaviours
Analyse behaviours
Identify effective measures to prevent reoccurrence
Record

9. Errors
Slip
When a person does something, but not what they meant to do
Lapse
When a person forgets to do something
Both are unintended actions with unintended consequences

10. Mistakes
When a person does something they intended to do, but should have done something else
Rule based – choosing a standard solution for a known problem – the maintenance worker who selects the wrong isolation procedures
Knowledge based

11. Mistakes
Because the action is intended, mistakes are much harder to detect at the individual level
People believe what they are doing is right and often dismiss evidence to the contrary
Bias
Tunnel vision

12. Violations
Violation
When a person decides to act without complying with a known rule or procedure
Note that, in this context, there must be an known rule or procedure
This is not a moral or ethical judgement

13. Violations

14. Violations
Note that we all integrate rule violation into our day to day lives so the identification of a violation should not be regarded as a precursor to discipline
Indeed, we tend to like those who break the rules

15. Violations

16. Violations Types of violations Routine Exceptional Acts of sabotage
The key to the effective analysis of violations is to understand why
What antecedents were present?
What behaviour was observed?
What consequences resulted?

17. Performance Influencing Factors
Defined as ‘the characteristics of the job, the individual and the organization that influence behaviour’
Considered during behavioural analysis, often at the end of the process
Very broad topic including a range of factors e.g. fatigue, group effects, design of equipment, mental wellbeing, task knowledge/complexity
Often have a critical role in error causation but equally often overlooked.

18. Common issues Failure to correctly specify behaviour
The individual involved
The task they were engaged in at the time
What they did (or did not do)
What the outcome was
Making early decisions and sticking to them
As information becomes available, a mistake can become a violation
Failure to identify the multiple behaviours contributing to an accident or incident
Timeline critical

19. Why bother with any of it?
Each failure type has a different set of solutions designed to prevent their reoccurrence. For example (not exhaustive):
Slip/Lapse
NOT training
Hardware solutions
Cross checks
PIFs
Error
Training e.g. scenarios
Group support
Challenge
Violations
Behaviour modification
Culture improvement

20. What to remember
Human behaviour can be predicted with reasonable accuracy
Correctly integrating HF into your accident investigation process will reap rewards – just look at the contemporary causation figures
Separating error, mistake and violation represents a highly valuable first step

21. A final thought
The most powerful influence on human behaviour is outcome
Therefore managing human failure requires a high degree of corporate honesty:
What behaviour is really rewarded?
Are we willing to look at organizational factors, especially when we see rule breaking?
Are we willing to make the investments that are likely to prevent reoccurrence?
Are we willing to strive for objectivity and pragmatism?

22. Thanks
"Don't fix the blame, fix the problem!"