Data Analytics: Importance of capturing human factor analytics and how it can be extended to become predictive and help in safety initiatives.



Maritime accidents cause severe damage to the environment and property, affecting both human and marine environments. Despite the availability of modern bridge equipment, new technologies, and advanced safety measures, maritime accidents still occur. Of course, there are many reasons for disasters such as mechanical failures, adverse weather conditions, and traffic density, but human factor attributes to a majority of those accidents. It thus becomes imperative to capture and analyze the human factor to take preventive measures to safeguard life, property, and the environment at sea. Predictive data analytics can help in extensively reduce the number of maritime accidents.

Case Study:

The importance of capturing human factor analytics can be understood by the following example. A few years ago, an electrical contractor in Alberta used predictive analytics software to improve their company’s safety performance. In a few years, the company found that employee participation in identifying risks had increased, and as a result, the number of unwanted incidents had reduced. The employees started identifying 10,000 to 15,000 hazards annually with the new program.
This proves that predictive analytics can help in significantly reducing incidents. Adopting this approach can be beneficial to the maritime industry because the industry has an immense focus on safety. Capturing the human factor element for predictive analysis helps in making informed decisions. For example, if a worker, who is usually alert in his work every day, falls sick or is disoriented someday, his behavior and activities might be little different from normal days. The safety team can observe his behavior through inputs from other employees or predictive software to take preventive measures.

Predictive models

A detailed analysis of the human factor helps in identifying the strongest driver for a particular outcome. These drivers help in making predictive models for practical recommendations and future interventions. A few predictive models based on work pressure, fatigue, job security, sleep problems, and so on are discussed below.

Predicting Safety Culture

Studies show that when organizations value safety and welfare over operational charge, operation schedule, and loss of goods and ship, safety culture is expected to be more mature. Interventions that advance crew strength and safety-focused leadership of supervisors are liable to deliver optimistic effects for safety culture on board ships.
Predicting Seafarers’ Psychological Wellbeing
The psychological wellbeing of a seafarer is reduced by work-related pressures, fatigue, and sleep problems. It reduces psychological feeling and functioning. On the other hand, a good social environment where there is a high level of trust in co-workers, supervisors are highly focused about their team’s safety, and supervisors encourage new ways of thinking about safety result in improved psychological wellbeing of seafarers.
Predicting Symptoms of Mental Ill Health
The symptoms of mental ill health (e.g., depression and anxiety) can be a result of high vigilance demands at work along with sleep problems and chronic fatigue. Therefore, the impact of vigilance demands and other work structures require consideration, especially when there is a tendency to consider deep-sea sailing periods as opportunities for recovery.
Predicting Sleep Problems At times the increased work pressure results in sleep problems. This can be reduced by job security and a supervisor’s safety leadership. The supervisors that are alert and guide safe behaviors can lessen the probability of sleep problems with a better dedication to work and rest requirements.
Predicting Acute Fatigue
It is possible for seafarers not to feel fatigued either at the end of a duty period or workday when
• they have the authority to use personal judgment in carrying out work
• their immediate supervisors’ top priority is their team’s safety
• seafarers have faith in their supervisors to look after their safety
• their job security has high levels
• they are not assigned work in environments that present difficulties such as small workspace, dirty working environment, hazardous equipment, and material

Predicting Chronic Fatigue
Work pressure, impaired recovery, lack of job security, and acute fatigue also help in assessing the risk of seafarers developing chronic fatigue. Focused attention must be given in this case for effective recovery during work periods.

Predicting Seafarers’ Need for Recovery
When constantly faced with operational uncertainty and tasked with maintaining high levels of vigilance, seafarers are more likely to feel that they lack sufficient recovery between duty periods. Job security, co-worker support, and safety leadership help in the better recovery of seafarers. In addition, it seems that seafarers whose supervisors handle the team to detect unsafe actions are more likely to get rest between duty periods, possibly because of increased devotion to rest and work guidelines and schedules.
Any decision by shipmasters and officers determine the fate of people, ships, and their environment during their careers and incorrect decisions can lead to accidents. Therefore, it is very important to analyze the causes of accidents and capture the data on the human factor for taking safety measures.

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