Why The EHS Industry Is Looking To Fabric As The Future
Introduction:
When you ask EHS professionals what they’ve seen as the biggest challenge for the EHS industry over the last 20 years. They’ll probably say something along the lines of “the goal posts keep changing”.
Today’s EHS data management faces multifaceted challenges. Firstly, the volume of data that companies must manage has skyrocketed. This includes not just traditional environmental and safety data but also extends to newer forms like ESG (Environmental, Social, and Governance) metrics and data from wearables tracking employee health in real-time.
Secondly, the diversity of data sources further complicates matters. Data comes in various formats and from disparate systems, making it hard to consolidate and analyze effectively. Additionally, there’s an increasing demand for real-time monitoring and reporting, which many existing systems are ill-equipped to handle.
Lastly, compliance requirements are becoming more stringent and complex. Companies must not only gather and store data but also ensure it adheres to various local and international regulations. Failing to do so can result in significant legal and financial repercussions.
The Problem:
All of these pain points come back to the same root. All EHS functions are derived from risk, safety does so much because managing risk effectively requires all data to be tied together in a way that makes it usable. There’s a reason why you don’t buy a new car disassembled or buy one part of your house from one company and one from another.
We, as humans, process most things from some kind of hierarchical, relational or holistic structure. Its how our brains manage information. Everything from reading the newspaper to analyzing a chart requires the material to be organized in a way that our brains can understand the relationship between piece of information A and piece of information B and how they both relate to piece of information C.
That’s the challenge for all organizations today. Data is messy, disheveled, fragmented and difficult to process in its raw form and that creates a barrier for those trying to do something with it. A survey conducted by Qlik and Accenture found that only about one in five people are confident in their data literacy skills, and 74% of employees actually feel overwhelmed when working with data.[1]
Where Fabric Fits In:
Enter stage left, Microsoft Fabric. It offers a unified platform for integrating diverse EHS data sources. Its key features include:
- Data Integration: Fabric can aggregate data from various sources, including IoT devices, wearables, and existing EHS systems, into a cohesive framework.
- Real-Time Analytics: With advanced analytics capabilities, Fabric enables real-time monitoring and analysis of EHS data.
- Compliance Management: The platform is designed to stay updated with the latest regulatory requirements, easing the compliance burden.
- Scalability: Fabric’s cloud-based architecture ensures scalability, allowing businesses to manage growing data volumes without compromising performance.
Compared to traditional EHS data management systems, Fabric stands out for its integration capabilities, real-time analytics, and compliance features. Its use of cloud technology ensures scalability and accessibility, crucial for modern businesses. Additionally, being a Microsoft product, it benefits from continuous updates and support, ensuring it stays ahead of the curve in both technology and regulatory compliance.
These features are nothing new, integrating IoT, business and operations data has been a problem that organizations have been working to tackle for some time now. The issue in creating a solution mainly revolved around:
- Tool incompatibility: with so many data, analytics and reporting solutions offered under every major ecosystem (Azure, AWS, Google, etc.), integrating the information required an army of data and software engineers just to point the flow to one central location.
- Usability: If an organization was able to make it over this first hurdle, they faced an even tougher challenge. What to do with the information and how to make it valuable. This also required a massive team of reporting specialists and data scientists. The even tougher challenge with this requirement is that people with this skillset are in very limited supply since data has only become a business imperative within the last 10-15 years.
What Fabric offers that solves both of these problems in one foul swoop is its end-to-end design. To understand what is meant by this, here is an illustration of the most prominent data, analytics and AI tools available in the market today:
And Here is the Service Architecture of Fabric
The design of Fabric serves the purpose of creating native, interoperable-by-design services for the main data tasks:
- Collection
- Organization
- Storage
- Interpretation & Analysis
- Action
- Monitoring
- Visualization
The greater key to this architecture: you do not need a degree in mathematics, statistics or data/computer science to use any or all of these offerings.
Moreover, the end-to-end approach solves the biggest data problem of the last 25 years: centralization. With the ability to conduct all parts of the data lifecycle in the same place, it is far easier to mesh external data sources and any other key data collection system with one that has the full package than one that can do 2,3 or 4 out of the 7 phases that Fabric supports.
Finally, if you’re still not convinced in Fabric being the future of your organization’s data infrastructure, think of this.
Quality, impactful and effective AI requires quality, impactful and effective data. More importantly, it requires that data to be in the right place, right form at the right time. Does this not seem 10x more achievable if that data is sitting in one center and curated in a way that makes it usable?
Microsoft seems to think so. In an article published on their Fabric blog, they identify that in Azure AI Studio (Microsoft’s AI platform), developers can run models against data from OneLake and any other data supported by Fabric shortcuts, including Azure Data Lake Storage Gen2 and Amazon S3. Azure AI Search can store, index, and retrieve data, including vector embeddings, from any of these sources through OneLake. [2]
Conclusion:
There you have it, Fabric offers the best solution to date for the hardest problem in EHS: collecting, organizing, interpreting and acting on safety data that can and will help make better decisions when it comes to organizational risk.
Moreover, it doesn’t just offer a solution now. It offers a solution for next year and potentially 5 years from now. The platform’s cloud infrastructure and end-to-end design creates a level of scalability that can only result in a data & AI infrastructure that is truly built to last.
For future insights into Fabric, and more on the role of AI in Environmental, Health, and Safety (EHS) management and to connect with like-minded professionals, join our AI community. And if you have any questions or are ready to start your journey with Fabric and ITRAK 365 check out our Partner Center to get the conversation started.