4 Things to Know About EHS Data & Advanced Analytics
If you’re hesitating whether you should spend time to view the webinar, continue reading this post to have a preview of what to expect. The webinar presented a wealth of information, including four important things that all professionals should know about EHS data and advanced analytics.
1) Ineffective Data Management Inhibits EHS Performance
During the webinar, Pete Bussey, Lead Research Analyst for EHS at LNS Research, made a compelling case about the high priority that effective data management should have for EHS professionals. These startling statistics from an LNS Research survey should be a wake-up call about the need to improve data management and eliminate data silos:
- 49% of organizations identify “disparate systems and data sources” as a top challenge to EHS performance improvement.
- Only 19% of companies have real-time visibility to EHS metrics.
If organizations want to leverage advanced analytics, they should start by improving EHS data management.
2) Digital Transformation is Real and it’s Here to Stay
It’s easy to get comfortable with the status quo and resist change, including the technological changes brought by digital transformation. But the floodgates have already opened, and digital transformation is happening right now. Consider these statistics that Pete shared from the same LNS Research survey:
- 40% of companies have a digital transformation initiative in place.
- 24% of companies will start one this year.
The message for EHS professionals is clear: Digital transformation is real and it will change EHS. You can either embrace the change and benefit from it, or be left behind.
3) Data Collection and Data Quality Go Together
Leveraging advanced analytics starts with data collection. During the webinar, Martin Vauthier, Product Manager for Enablon’s Analytics and Reporting solutions, explained in detail how increased data collection can create inaccuracies and data quality issues. Traditionally data has been collected through software user interfaces, and more data means more room for inaccuracy. But there are ways to improve data quality. New technologies connected through the IIoT (e.g. drones, smart PPE, sensors) help improve data quality by collecting real-time data at the source, including data not previously accessible. Also, data quality checks (e.g. anomaly detections, standard deviations) can be applied to ensure quality.
4) Data Science Can Help Answer Key Questions
The ultimate goal of big data and advanced analytics should be to help EHS leaders answer key questions that improve EHS performance. EHS leaders want to predict incidents, improve worker safety, and decrease incident-related costs. Data science is here to help! Here’s a sample of questions that data science can help answer, and which were shared by Martin during the webinar:
- What are the leading indicators that impact safety?
- What is the estimated incident rate next month?
- What controls can be applied to reduce a particular risk?
Click on the image below to view the full recording of the webinar and learn more about the topics covered in this post, and much more: