Another gem on SMS from CatalinaNJB
This is a
blog with no relevance to any opinions, facts, research or science, but a
trivial blog written for continuous improvement in safety by thinking beyond
the horizons and outside the box. For continuous safety improvement to be
effective thinking outside the box is vital for the collection of unbiased data
and then bring this data back in the box to be analyzed for safety
improvements. We don’t manage risks; we lead personnel, manage equipment and
validate operational design for improved performance above the bar of
acceptable risk level.
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Improvements begins
outside the box.
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Risk level analysis is
traditionally established by applying likelihood, severity and exposure. In a
risk level analysis, the exposure is always equal 1 for the hazard to become a
risk to aviation safety. Without exposure, there is no risk. Birds is a hazard
to aviation safety. However, birds that are 100 miles away from the flight path
are not a risk to aviation, but still classified as a hazard to aviation.
Traditionally these risk levels are color coded, where green is acceptable,
yellow acceptable with mitigation and red is not acceptable. There is often
little or no scientific data behind these risk levels except for aircraft
performance. Human factors, organizational factors, supervision factors and
environmental factors are not included in these risk assessments. Human factors
may affect the risk level differently one day than another day. Human factor,
or the interaction between software, hardware, environment and crew and other
human interactions are vital to aviation safety.
There are
two elements to human performance: 1) technical knowledge and 2) technical
skills. Knowledge is the theory of operations, while skills is the operations
itself. At the initial licensing of a pilot, the candidate first must pass a
knowledge test, and then a practical flight test. Without passing at an
acceptable risk level, a pilot license cannot be issued. As the pilot is
employed, this concept of refreshing both technical knowledge and technical
skills becomes a concept of operational performance.
Normally a
person’s retention of learning decreases with time when learning is not applied
to operations. Much of the theoretical learning is not applied daily in the
job, but occasionally with the use of checklist. The highest percentage-loss
occurs in the first days and weeks after the leaning is completed and somewhat
levels off after that. Since the learning is being applied in their skills
performance by flying an aircraft daily, there is additional learning occurring
on the job and their performance level of technical skills are improving in the
days and weeks after the learning.
One enterprise
was expecting their pilots to retain a 100% knowledge level one year after the
training and would initiate the refresher course with the knowledge test and
expect all candidates to be as proficient in knowledge as they were 365 days
ago. Since pilots only applied part of
their knowledge regularly in the day to day job and learning was not
encouraged, most of what was learned had been forgotten in 365 days. Since their
jobs were dependent on passing the knowledge test, the candidates would do
their own and personal refresher course the last 2-3 weeks prior to the
official refresher course. When the test was take all candidates passed and the
enterprise could proudly check off the box that their pilots had retained 100%
knowledge in 365 days.
When
assessing risk levels differently an enterprise would assess performance based
on a pilot’s retention of knowledge and skills. Let’s assume the learning
retention loss of knowledge is 20% per day for the first 84 days and from then on,
the retention loss is 2% per day to 365 days. At the end of a year the total
knowledge retention is 20%, or in other words, if the pilot took the test
without studying after 365 days, it would be expected that the test result
would be 20% of last result.
Their technical
skills retention for pilots are not reduced after learning, but their
performance is getting better since they are applying their skill in their day
to day job and additionally being exposed to known and unknown hazards
regularly. At the end of 365 days the pilot retention levels are 180% of what
it was after the previous flight test.
When
applying this data as a combined retention level factor of knowledge and
skills, the pilots are performing at their 100% level after 365 days. After 5
years in the same job they are performing above their 100% initial level.
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Performance factor most
critical days are days 60-80.
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Traditional
risk level model is based on aircraft performance and pilots are expected to
perform at their 100% performance level in both technical knowledge and skills.
In addition, the traditional risk level matrix does only apply recommendations
to accepted risk or rejected risk. A different risk matrix is to apply an action
to the colors which are based on likelihood and severity. These actions are to
communicate (green), monitor (yellow), pause (blue), suspend (orange) or cease
(red) operations. Risk levels orange and red are applicable to aircraft
performance where pilot qualifications does not impact aircraft performance
limitations. When overlaying the knowledge, skills and performance factor
graphs onto the risk matrix, the lowest level of performance represents
knowledge, the highest skills and the middle is their performance level. A
performance level should be above the monitoring (yellow) level for quality
assurance of flight operations.
CatalinaNJB
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