As systems become increasingly interconnected, we talk more and more about the importance of data and, more specifically, the need to get data to the right people, in the right format, at the right time, wherever they may be. This initiative has become even more imperative as operational technology (OT) and information technology (IT) converge. No longer are OT assets siloed and air-gapped by default. Today, OT systems need to operate much more similarly to IT infrastructure, with access to internet, cloud, SaaS, and more.
Nowhere is this shift more obvious than in the life sciences sector, where data is of critical value. In a recent article in EuroLab, Michalle Adkins shared how life sciences companies are looking for ways to merge and move data across the IT/OT convergence for nimbler operation and faster speed to market.
Context is key
One of the key complexities of data management across the IT/OT divide is that OT data—especially in the life sciences—must maintain its context to be valuable. Michalle explains,
“This bubbling up of data—or giving it contextual meaning—can be very useful in a number of scenarios.”
For example, the move toward real-time release relies heavily on contextualized data. Teams cannot release products quickly if they cannot accurately collate data from all the systems involved in production. They need contextualized data that is easy-to-access to ensure batches are successful and safe for release.
However, while modern technologies like data lakes make it possible to contain all sorts of data from a wide variety of different systems, just throwing data into a big repository without a plan quickly turns a data lake into a data swamp. Such data is hard to use, and certainly makes it harder to perform key tasks like technology transfer and tracing batch issues back to their root to identify production problems.
Modern technologies like those in the DeltaV™ automation platform make it easier to maintain context alongside critical data. Within the control system, data is contextualized at every stage, providing insights that make the data valuable to cross-functional teams. In addition, that context can be maintained as data moves across any of the technologies that seamlessly integrate with DeltaV solutions, from the field to the edge, and into the enterprise cloud. This democratization of contextualized data helps eliminate the data silos that are anathema to pipeline acceleration.
Easy access to contextualized data is also helping life sciences companies achieve other critical goals. For example, as more companies pursue net zero initiatives, they find that maintaining sustainable operations requires deep insight into the efficiency and performance of their processes. Highly contextualized data helps them track and trend key variables such as energy use, emissions, and waste to help meet these goals.
Connectivity counts
It isn’t just the control system that needs contextualized data. The best automation systems preserve context even as they move data up the chain to enterprise systems. Applications like AspenTech’s Inmation™ and Mtell® help preserve the context of data from the DeltaV distributed control system as it moves into the cloud and high-level analytics systems to further increase performance.
Ultimately, in the life sciences industry, data mobility is not just about moving data between IT and OT stacks. It is also critical for preserving as much context as possible to drive innovation and support the cross-functional teams trying to get treatments in the hands of patients as safely and quickly as possible. As modern medicine continues to evolve, this seamless access to data will only become more important. As a result, there is no time like the present to begin building an automation foundation to support the data democratization that drives competitive advantage.
