Key challenges in HSE
LR research reveals that depending on industry sector, 50-80% of all incidents are caused by human error – a result of the interplay of human behaviour, the asset they operate and the environment in which they work. Data can provide a deeper understanding about minimising risks – but all too often companies still focus on incident reporting. Which maturity level best describes your organisation?
Most companies are at this stage, using descriptive analytics based on incident reporting to understand what happened
Some companies are taking this approach further, by using diagnostic insights and root cause analysis to establish why accidents happen
Pioneers are starting prescriptive interventions on what needs to happen, in real time, based on predictive and prescriptive analytics
The challenges we see
Our customers approach LR to deliver innovative solutions across a range of critical and complex challenges they face in HSE. A common requirement is the need to extend the processing of near miss and incident reports to include a true root cause analysis based on diagnostics, typically of many thousands of data points. Customer requests can also be very specific to their operating environment, asking for solutions to address staff fatigue and wellbeing, or for body condition monitoring via temperature tracking in extreme working conditions, and location recognition for “man-down” scenarios. Others want simple tailored training solutions to help staff improve situational awareness when working at height, lifting heavy goods or operating machinery.
The capabilities we leverage
LR is at the forefront of understanding the application of new science and technology to future-proof client businesses, harnessing and analysing data to provide our customers with rich management information and innovative decision-making tools. Through our analytics platform, Connected Assets, LR can process vast quantities of data and reference its own benchmarks. The combination of big data and natural language processing allows us to infer new patterns and identify heightened risk – produced as heat maps and tailored management recommendations.
LR also draws from collaboration with best in class technology providers in wearables and video analytics to assemble integrated solutions around fatigue monitoring and risk tracking.
To provide safety critical training in a safe environment, LR was first to market with its award winning AR & VR safety simulation and risk recognition technology, which can be deployed in client classrooms or used in-situ at one of LR’s many training facilities around the globe.
The approach we take
LR takes an agile and collaborative approach to innovation, using pilot projects to prove the potential of new technology and operationalising processes before scaling solutions globally. We call it innovation partnership.
The initial engagement typically starts with a workshop between clients and LR to understand opportunities, challenges and constraints – referencing the art of the possible with the LR experts.
If specific goals and benefits can be identified, LR will provide a proposal for a pilot, which outlines deliverables, success criteria and ways of working. Many projects grow beyond a pilot stage, based on detailed commercial statements of work – spanning different technologies territories and touch points across the client’s organisation.
As part of all our work we respect and protect the privacy of individuals, and the personally identifiable data that is collated from them.
LR’s independence means that we can provide reliable, impartial and informed advice that its customers can trust - free from compromise, free from prejudice.
Have a challenge for us?
Are you ready to explore and co-create the solution, and test the outcome with a pilot study? We offer our clients a workshop environment to explore and develop the program of work that will ultimately result in a pilot that not only demonstrates the solution, but will also form the business case for moving into full deployment. Interested?
Who we work with
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