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9.1.4 Safety analysis is based on factual information, possibly originating from several sources.
Relevant data must be collected, sorted and stored. Analytical methods and tools suitable to the analysis are
then selected and applied. Safety analysis is often iterative, requiring multiple cycles. It may be quantitative
or qualitative. The absence of quantitative baseline data may force a reliance on more qualitative methods of
analysis.
Objectivity and bias
9.1.5 Consideration needs to be given to all relevant information; however, not all safety information is
reliable. Time constraints do not always permit the collection and evaluation of sufficient data to ensure
objectivity. Intuitive conclusions may sometimes be reached which are not consistent with the objectivity
required for credible safety analysis.
1. See Annex 13 — Aircraft Accident and Incident Investigation.
9-2 Safety Management Manual (SMM)
9.1.6 We are all subject to some level of bias in our judgement. Past experience will often influence
our judgement, as well as our creativity, in establishing hypotheses. One of the most frequent forms of
judgement error is known as “confirmation bias”. This is the tendency to seek and retain information that
confirms what we already believe to be true. Appendix 1 to this chapter provides more information on
understanding bias and how it is relevant to the drawing of conclusions in safety analysis.
9.2 ANALYTICAL METHODS AND TOOLS
There are different methods used in safety analysis; some are automated, some are not. In addition, several
software-based tools (requiring different levels of expertise for effective application) exist. Listed below are
some analytical methods and tools that are available:
a) Statistical analysis. Many of the analytical methods and tools used in safety analysis are based on
statistical procedures and concepts, for example, risk analysis utilizes concepts of statistical
probability. Statistics play a major role in safety analysis by helping to quantify situations, thereby
providing insight through numbers. This generates more credible results for a convincing safety
argument.
The type of safety analysis conducted at the level of company safety management systems requires
basic skills for analysing numeric data, for identifying trends and for making basic statistical
computations such as arithmetic means, percentiles and medians. Statistical methods are also
useful for graphical presentations of analyses.
Computers can handle the manipulation of large volumes of data. Most statistical analysis
procedures are available in commercial software packages (e.g. Microsoft Excel). Using such
applications, data can be entered directly into a pre-programmed procedure. While a detailed
understanding of the statistical theory behind the technique is not necessary, the analyst should
understand what the procedure does and what the results are intended to convey.
While statistics are a powerful tool for safety analysis, they can also be misused and, consequently,
can lead to erroneous conclusions. Care must be taken in the selection and use of data in statistical
analysis. To ensure appropriate application of the more complex methods, the assistance of
specialists in statistical analysis may be required.
b) Trend analysis. By monitoring trends in safety data, predictions may be made about future events.
Emerging trends may be indicative of embryonic hazards. Statistical methods can be used to assess
the significance of perceived trends. The upper and lower limits of acceptable performance against
which to compare current performance may be defined. Trend analysis can be used to trigger
“alarms” when performance is about to depart from accepted limits.
c) Normative comparisons. Sufficient data may not be available to provide a factual basis against
which to compare the circumstances of the event or situation under examination with everyday
experience. The absence of credible normative data often compromises the utility of safety
analyses. In such cases, it may be necessary to sample real world experience under similar
operating conditions. FDA, LOSA and NOSS programmes provide useful normative data for the
analysis of aviation operations. These programmes are discussed in Chapters 16 and 17.
d) Simulation and testing. In some cases, the underlying safety hazards may become evident
through testing, for example, laboratory testing may be required for analysing material defects. For
suspect operational procedures, simulation in the field under actual operating conditions, or in a
simulator may be warranted.
Chapter 9. Safety Analysis and Safety Studies 9-3
e) Expert panel. Given the diverse nature of safety hazards, and the different perspectives possible in
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