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95% of Industrial Asset Data is Unusable: It's Time to Change That

Some tools just aren’t cut out for certain jobs. For example, you wouldn’t use a spread sheet to stand up your enterprise financial planning and analysis processes, any more than you might choose a screwdriver to seal a bad actor in a chemical plant. So why do so many industrial organizations continue to think that a spreadsheet can solve their OT data challenges?

OT data is fundamentally different. Time-series and other OT data collected from assets is spread across many plant sites, locked up in legacy systems at the plant and in engineer’s spreadsheets. OT data has notoriously demonstrated low quality – attributed to a lack of metadata to provide context to the OT data – and no standardization because of poor and inconsistent data labeling. OT data is some of the most ungoverned, and ungovernable data.

As a result, currently as much as 95% of industrial data goes unused – or, at best, it’s leveraged at a local level and via homegrown solutions that can’t scale to meet the universal needs of a large-scale industrial company.

Standardizing industrial data is critical so that you can make apples-to-apples comparisons of like equipment types, as well as deliver context for decision making. The relationships, or connections, between the data, are as or more important to represent as the data itself.

Standardization also organizes assets into hierarchical or process-oriented relationships to create the “graph” of your industrial operations. But, to date, the effort to create some sort of actionable industrial graph has been manual and laborious, often requiring months, or even years of human effort working off of spreadsheets, or teams cobbling together point products. This antiquated approach doesn’t scale, and is very error prone, causing quality, scalability and security to take a back seat, and resulting in excessive costs and a high level of failure.

At Element, we believe that this OT data purgatory cannot continue. The demands for productivity, resiliency, reliability and cost savings are too great for OT to persist down the path it has been on for decades. It’s time for a better way of harnessing data and making it actionable in order to:

  • Make OT data reliable, scalable and secure
  • More efficiently and productively execute on analytics, maintenance, and health and safety applications
  • Reduce friction and the costs of getting projects delivered
  • Optimize environmental impacts to create cleaner, healthier and more profitable operations
  • Enable a more agile and sustainable enterprise where OT and IT counterparts can come together for more adaptive and resilient decision making

We’re ready to help make that change. Introducing Element Unify™.

Today I’m proud to share that we’ve introduced Element Unify™, a cloud software solution that automates the integration, contextualization, and governance of OT/IT metadata. Unify for the first time enables simplified analytics, accelerates time to analytical value and keeps data synced and evergreen across IT/OT systems of record.

Importantly, Element is not a “rip and replace” solution – it integrates easily with existing IT and OT systems, as well as the AWS and Microsoft Azure IIoT service stacks, solving the data problem through a unique “data fabric / data hub”system of record approach that connects to all data sources and feeds all consumers in a seamless manner. With Unify, industrial organizations can:  

  • Integrate: Easily connect legacy OT and IT systems to modern data architectures, supporting improved analytical workloads in both legacy systems, like the PI System, as well as in cloud-based systems. Data preparation is fast and automated using no-code data pipelines and purpose-built transformations.

    This makes it easy for IT and OT to collaborate because subject matter experts who know the data can work directly in Unify without the need for an IT resource and without knowing Python. Speeding time to analytical value saves companies millions in data preparation and maintenance costs
  • Contextualize: Easily create a unified environment with data transformations purpose-built to handle the complexities of OT data. Enable low code/no code data engineering for rapid integration and contextualization of OT/IT metadata – and support self-service apps and analytics.

    Connected metadata stored in the Element Graph makes it easy and flexible to build and deploy analytical applications at scale, resulting in hundreds of millions of dollars in value across use cases likeOEE, predictive maintenance and safety. With Unify, OT can develop their own analytics without drawing on IT resources in a way that provides IT with governance over a sustainable architecture. It’s a best of all worlds scenario.
  • Govern: Governance of proliferating IT/OT data and analytical silos has never been more important, requiring organizations to manage semantically consistent data and data models across the enterprise. Element Unify's Data Catalog tracks data lineage (complete chain from source to use), utilizes templates for fine-grained semantics control – and persists data keeping it synchronized across all systems. This builds trust in data, accelerating adoption of analytic apps.

I invite you to see for yourself. Contact our team to request a demo. I also recommend you checkout our new eGuide, "How to Talk to IT and the C-Suite to Get the Green light on Transformation."

With the call for healthier, safer, more productive operations echoing louder than ever before, we must more fully exploit the power of our OT data. Now is the time. And I firmly believe that Element Unify is the solution our industry needs to move forward.