Friday, May 5, 2017

Risk Management Differently

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.

Improvements begins outside the box.
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.

Performance factor most critical days are days 60-80.
The 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