Data analytics
環境、社会、ガバナンス21 11月, 2024

Insights from EHS data: Don't miss the big picture

Today’s EHS professionals have unprecedented access to massive data volumes that allow them to generate more and better insights and move their organizations to proactive risk management. But with such tremendous capability and data volumes, it’s easy to miss important lessons if you don’t dig deep enough.

Centralizing data creates a single source of truth

It all starts with consolidation. Among the many good reasons for a single, centralized, cloud-based EHS software platform throughout an entire organization is having all EHS data in one place. A centralized data repository provides:

  • A single, unified source for all data, ensuring consistency across the organization since everyone uses the same data
  • An easier way to integrate data from different sources or departments
  • Governance and control mechanisms to ensure data is clean, accurate, and up to date
  • Easier access to data without the need to search multiple systems
  • A more streamlined way to gather data, reducing the time to locate and extract information, and a way to accelerate analysis and decision-making

Data gives organizations greater visibility across their operations and the potential to quickly detect patterns and trends, as well as logical connections between elements, helping them identify risks and opportunities. It all leads to improved worker safety, superior EHS performance, and operational excellence.

Be sure to see the big picture

But there are challenges associated with an overabundance of data, including information overload where there’s too much data or too much irrelevant data. It can be overwhelming and make it difficult to prioritize actionable insights.

Even with insights generated from data, there is the possibility that decision-makers may be swamped by the sheer number of insights available, or they may not recognize important insights beyond those that are most obvious.

Consider these three examples below that show how an initial data analysis may not reveal everything.

1) Field reporting of near misses and observations


What the data shows
: After launching a near-miss reporting program with a centralized system and mobile apps, the number of reported near misses and observations of unsafe conditions and behaviors has fallen.

What you may conclude: Safety is improving because the total number of reported near misses and observations has fallen.  

What you may have missed: When a field reporting program is implemented, there’s an initial and often significant rise in the number of reported near misses and observations, since workers are proactively identifying issues that already exist. As time goes on, there could be a drop in the number of near misses and observations reported after that initial bump, leading to a conclusion that safety is improving, which may or may not be the case. Also, a decline in reported near misses and observations may suggest another issue – one of diminishing employee engagement and a weakening safety culture. It would be a mistake then to assume safety is improving simply because reported near misses and observations are dropping.

2) Near misses and potential SIFs


What the data shows
: The number of near miss events is falling, and the number of incidents is stable or also declining. An organization feels it is moving in the right direction.

What you may conclude: The lower number of near misses indicates safety is improving and risks are diminishing.

What you may have missed: While there are fewer total near misses, perhaps the number of near miss events with a potential for a serious injury or fatality (SIF) is actually increasing. Suppose there were 100 quarterly near misses, of which 20 were potential SIFs. Now, near misses total 80 each quarter, but 30 have a SIF potential. The overall drop in near misses is misleading at first glance since there is an increasing and disturbing rise in potential SIFs that can lead to more actual SIFs.

3) Benchmarking plants or facilities


What the data shows
: By centralizing all data, a company can compare the safety metrics and performance of individual plants or facilities, allowing for benchmarking.

What you may conclude: Plants or facilities observed with poorer safety performance should receive extra training and be targeted for awareness campaigns.

What you may have missed: Is safety training and awareness the only problem? Perhaps some plants perform poorly on safety because they were built before the 1970s or 1980s and incorporate fewer inherently safer design principles than plants built more recently. Is it necessary to apply inherently safer design concepts to existing facilities? Additional training or awareness campaigns could help but may not address the primary flaws and may only tell part of the story. In this case, a bigger picture analysis could be needed to recognize that more engineering controls are required in older plants.

Dig deeper for more valuable insights

EHS professionals need help in digging more deeply into data to reveal important insights. There has never been more data available and while insights can make organizations more proactive in minimizing risks and reducing incidents, data volumes can be massive.

Today, advanced analytics and artificial intelligence are assisting professionals in many industries in processing data and revealing insights that they may otherwise miss. Analytics are now an important part of improving safety performance and helping human experts drive even deeper data analysis to ensure nothing gets missed.

Learn more about Enablon Open Insights and discover how to simplify your data management with an advanced cloud native analytics solution.

Content Thought Leader - Wolters Kluwer Enablon
Jean-Grégoire Manoukian is Content Thought Leader at Wolters Kluwer Enablon. He’s responsible for thought leadership, content creation and the management of articles and social media activities. JG started at Enablon in 2014 as Content Marketing Manager and has more than 25 years of experience, including many years as a product manager for chemical management and product stewardship solutions. He also worked as a product marketing manager in the telecommunications industry.
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