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In the modern world, it's been increasingly well understood that two cultures of technology craftsmanship have emerged and are learning from each other. We have the practice of IT, and the application of computing technology in the general business world. This type of technology practice supports the front and back office functions of companies worldwide. IT is supported by a wide and thriving network of software and vendors. The entire world essentially runs on IT infrastructure. 

But there is another equally important technology culture in the world of manufacturing, commercial infrastructure, utilities, logistics and other mission-critical and high performance arenas. It is called operational technology, or OT, and it has a variety of different cultural aspects from IT. 

There has been a lot of speculation about how these two cultures will come together and learn from each other. In our view, the first major victory will occur when the data and analytics technology from IT is applied, even more, in the OT world. Here's how we think OT will benefit from data and analytics from IT.

First, understand the differences

In order to understand how OT can benefit from IT data and analytics, it’s important to understand the differences between the two spaces. Requirements and goals are often different in OT and IT, and those who work in one of the areas may not understand those who work in the other.

Generally, in OT, priorities are focused on machine uptime, production output, quality, safety and security, while IT is typically centered on driving business innovation, productivity and cost savings supported by agile software delivery.

The differences can be quite significant, so in order for OT and IT to work effectively together, there has to be ongoing collaboration to make sure the two worlds understand their differing objectives. For instance, the purposes of OT and IT are different, with OT focused on managing assets, performance and plant processes, whereas IT is founded on the management of information and automating business processes. IT centers on availability and ensuring the integrity of systems, whereas OT hones in on safety and reliability. 

The roles in IT and OT differ as well. IT has a CIO and infrastructure, operations and apps professionals. OT has plant managers, supervisors, engineers and technicians. These groups view the world differently, with those in IT pushing for new technology and upgrades, and those in OT being slower to adopt new technology because of potential risks and higher costs of machinery and plant equipment, with the overarching needs of safety and reliability being paramount. IT often uses more predictive analytics, whereas those in OT are focused not so much on what will happen, but what is happening now. OT hasn’t traditionally had the same analytic tools as IT or the same access to data, so learning how to work with advanced analytics will take understanding and adjustment in both places.

Bringing both worlds together

For OT and IT to converge, IT has to gain the trust of OT. Often, those in OT view IT staff as being blasé about safety and reliability, which is understandable given that the stakes are higher in OT, as problems can mean not just machine or plant failures, but imperiling the lives of those who work with machinery. Something as simple as updating an operating system can lead to slowdowns that could disrupt OT operations. 

OT will need to see concrete benefits of AI/ML tools and advanced analytics in order to embrace them and trust the results of, say, predictive maintenance over existing preventative schedules. In this sense, OT is part of a larger call for explainable AI, where the rationale for predictions is clearly laid out.

But with enough effort and dedication, these challenges can be overcome. And a first sign that convergence is occurring is when both OT and IT begin to work together more closely and learn to speak each other’s language. IT should spend time in the OT environment and become conversant in OT’s use of terms. Such collaboration will be essential to getting the most from OT data, which is diverse and often hard to integrate, blend and contextualize with IT data sources.

Once these cultural obstacles are tackled, to merge IT and OT processes, companies should map out the differences so a common understanding can be achieved. This should incorporate the daily, time-driven schedules of OT and operating machinery with the long-term business goals and focus of IT. 

OT does have access to lots of data, but has not traditionally been able to put it to use because it lacked the increasingly easy-to-use BI and analytic tools of IT. IT will need to mentor OT in managing data at scale and in better preparing and enriching data to serve the ultimate goals of the business. And IT can’t do this without OT: OT has the domain knowledge that is essential to understanding the data, extracting the signal from the noise of machine data. By collaborating with OT, analytics experts can show how AI and ML can be used to give greater insights beyond existing operations intelligence applications. 

Companies will know they’ve succeeded in convergence when technology, processes and people in the OT and IT space are all headed in the same direction.

The easiest path is going to be for OT to start using more IT

As new OT tools emerge, the best way to promote convergence technologically is to connect these tools with existing IT infrastructure. The easiest way to do this is to focus on projects in which technology can be easily integrated and add to what OT is already doing rather than disturbing or replacing existing processes and systems. Therefore, focusing on projects that offer low-hanging fruit is key. Throughout these projects, IT should view OT as a customer to whom they’re trying to deliver results. Ultimately, OT can expand the use of data using IT analytics tools for tremendous benefits for the business. 

What success looks like

What is the upside of IT/OT convergence? A great example comes from the transportation industry, in which a rail company gained an annual savings of $25 million, while improving service and reliability by incorporating IoT analytics and moving from time-based to condition-based maintenance. Dramatic savings and optimizations are possible as companies integrate IT technology at the plant or facility level, while also ensuring that convergence occurs with both OT and IT workers and the cultures they operate in. 

To learn more, please read this E-book on Why we need IT/OT Convergence from Hitachi Vantara.  Also visit https://www.hitachivantara.com/en-us/products/iot/lumada-edge-intelligence.html.