Data lies at the heart of the 4th industrial revolution. Automation, connectivity, smart technology, and efficiency, and all the promises behind this new paradigm include data and analytics.
The current landscape, with an increasing number of sensors, embedded systems, and connected devices, as well as the uprising horizontal and vertical networking of value chains, is resulting in a vast, continuous data flow.
The industry sector understands that it is critical to have data analytic capabilities to drive digital transformation successfully. However, there is still a long way to go before we reach the level of sophistication needed to drive industry 4.0 applications.
Gathering the Operational Data
One of the main challenges the industry is still facing is accessing the quality data they need to run accurate analysis and support strategic decisions that may improve their operational efficiency and reduce costs. This is happening because there is a vast amount of data that is hidden, inaccessible, and unstructured; so cannot be leveraged. And one of the main reasons why this happens is the OT/IT gap.
Gartner defines IT/OT integration as the end-state sought by organizations (most commonly, asset-intensive organizations), where instead of a separation of IT and OT as technology areas with different areas of authority and responsibility, there is an integrated process and information flow.
Historically, operational technology (OT) departments have been responsible for keeping their plants running smoothly. OT encompasses machinery, physical plant equipment, PLCs, SCADA, etc. On the other side, information technology (IT) departments were responsible for managing business applications. IT professionals are experts in networking technologies, Cloud infrastructures, web-based deployments, etc.
Both worlds have existed for many years on separate planes, which provoked a deep OT/IT gap. Industry 4.0 and digital transformation projects' understanding that the plant is a connected environment, and aims to switch from a siloed structure to a "data-lake" approach, is becoming more evident.
The fact is that some of the best Industrial Internet of Things (IIoT) practices have already clearly demonstrated how powerful the integration of OT and IT worlds could be, allowing companies to improve their decision-making, have access to a greater quantity and high-quality data, but also to reduce costs, optimize processes, and lower risks.
Let's consider the production line, which is one of the most crucial areas in a factory and represents an incredible array of assets, sensors, and machines, all of them being a huge source of data. Information is an asset traditionally under the domain of IT, but in the case of the information captured by sensors on the production line, information falls under the OT domain.
The OT/IT gap affects almost all manufacturing companies. We are still far from the promising future of the connected factory.
The impact from the OT legacy
Managing OT and IT as separate organizational silos have generated unreliable outputs over the past few decades, and the significant benefits of convergence, such as insight into security risks and enhanced performance, demand attention across the technology landscape.
All the latest progress that OT has made has been in proprietary systems, which are difficult to scale across multiple technologies and providers. To reduce development and support costs and reduce time to market, OT vendors have integrated many IT-derived features and will continue to do so, but the path is uncertain, and the potential impact of missteps is tremendous.
A consequence of these segregated OT and IT environments, the OT/IT gap, is a lack of communication between IT and OT systems, which prevents enterprises from using control data in BI applications.
The increasing need to converge OT/IT worlds is clear for the industry. The challenge now is to find the best strategy and make the most intelligent decision. Partnering with innovative technology vendors and conducting pilot tests is one of the best approaches to ensure that a big deployment project may be successful, affordable, and efficient.