Investigating Human Reliability

HiLo is taking maritime risk analysis to the next level. The HiLo Human Reliability model is our latest innovation, currently undergoing proof-of-concept. HiLo’s wide ranging data analysis is growing even further with the introduction of people-related data, leading to the maritime industry’s first ever quantifiable analysis of Human Reliability.

Some of the biggest names in the industry are already sharing their people-related data with HiLo, enabling us to push the boundaries of global safety analysis further than ever. BSM, Shell, Maersk Tankers, Scorpio, Optimum and Zenith (Scorpio Group), Northern Marine, Stolt and Gaslog are contributing their data to the model’s proof of concept.

The more companies that share their data, the more effectively HiLo will be able to analyse the risks posed by human factors within the industry. We are all familiar with the everyday people-related risks at sea, and HiLo is striving to gain a deeper understanding of their effects.

What is Human Reliability

Human reliability is the human contribution to an industry’s risk factors. The safety of every fleet is dependent on the reliability of the people working on its vessels. No matter how professional or experienced they are, all crew members can be impacted by factors beyond their control.

There are many different human factors that can lead to incidents at sea, and their consequences can be catastrophic. These include (but are not limited to):

  • Weak procedures
  • Inadequate training
  • Fatigue
  • Environmental conditions

HiLo has developed a Human Reliability model, which is currently under development. The model relies on shipping companies sharing their people-related data (such as shift patterns and audit and inspection data) with HiLo.

HiLo will collect non-identifiable people-related data and build it into our predictive models, achieving a wider view of the human factors that can lead to incidents. HiLo will study the data to understand the drivers and consequences of the risks companies encounter. This will enable us to drill down into how companies are managing their risks and what more can be done to reduce them.

How does it work

HiLo’s subscribers will share their human performance related data regularly. All data will be anonymised, and will include details such as crew matrix, the length of tours and the number of port stops. HiLo will take this data and use their Human Reliability model to look at leading indicators with a focus on human reliability.

HiLo’s experts will analyse the results and create detailed, customised reports highlighting the key risks facing a company’s crew. All information is completely secure, and there are no repercussions or penalisation for sharing data. HiLo’s sole focus is on using shipping data to improve safety at sea.

Why is HiLo’s Human Reliability model unique

HiLo is the only company in the industry to combine statistical analysis with psychological insights into human reliability. That means, for the first time ever, shipping companies will soon be able to pinpoint the human factors that are putting their crew most at risk, and the changes they can make to processes and working environments to minimise issues. Sharing people-related data will enable company leaders to gain an insight into their fleet like never before, with a clear view of areas that can be improved to protect their crew.

HiLo offers companies direct visibility of its people and the way they’re being managed. Customised reports tailored to each vessel enable them to build effective solutions into day-to-day operations. This means companies can combat catastrophes before they take place.

HiLo’s initial Human Reliability Model model has been successfully peer reviewed by experts from a range of industries and is now at the proof-of-concept stage of its journey. We’re leading the way when it comes to global safety analysis, and your data can help us.

If you’d like to be a part of developing our transformative new product, speak to a member of the team today to find out more.

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