How OT Context Can Help Drive Digital Transformation

Gaining OT context

According to Gartner

, OT is the “hardware and software that detects or causes a change through the direct monitoring and/or control of physical devices, processes and events in the enterprise”. Implicit in this definition is the integration of the physical and virtual worlds. OT systems are becoming more like IT and are increasingly sharing fundamental core technologies, such as OS and communications stacks based on an ISA-95 framework. The convergence of these two conventionally disparate worlds is therefore now a critical component of a connected industrial IoT environment.

The drive towards automation in the IT world is well advanced. Process technologies such as Robotic Process Automation are well-established means for increasing efficiency and reducing the risk of human error. Focus is now shifting towards bringing the same level of efficiency to the operational world, in turn developing an integration between these two sides through IoT platforms and digital processes.

Using OT context to connect the digital thread

Integrating OT data into business decision-making is crucial for improving processes and controlling variability in highly complex, multi-variant environments. Data can mean different things depending on the recipient’s role and functions, and so it’s important that the information drawn from production systems is contextualized based on the specific needs of the person using it.

By establishing greater contextualization at an OT level, all systems that depend on this data can be integrated by a seamless digital thread. A digital thread seeks to create homogeneous and universally accessible data standards across different businesses processes and functions. The OT data from each part of that process can bring value to other parts of the chain, like aiding in the design and development of new products, or servicing products in-market.

Organizations will always want to be more agile. They want to avoid down time, be more efficient, and reduce their time to market as much as possible. By taking a data-driven approach to manufacturing operations, decision makers can structure improvements into their processes over time, not only helping increase the consistency and predictability of production but also provide better delivery to customers at an optimized cost.

From the early discovery phases of a product, through development, manufacturing, and then in-market, improving the quality and integration of data leads to better decision making at all stages. Business continuity is highly valued and so for C-level executives and other decision makers, having access to the right data from across the supply chain and production operations makes the task of identifying bottlenecks and sources of inefficiency far easier.