The great chasm between information technology (IT) and operational technology (OT) has been well documented in recent years, especially as digital transformation efforts gathered momentum over time.
OT has traditionally been focused on monitoring and controlling processes. For example, in a factory or warehouse, the OT team will continuously monitor the feedback from different equipment and compare the input with its normal range. If the input is outside of its normal range, an exception-handling process will kick in to manage this anomaly. Over the years, they often build up legacy equipment and technology, making them all work together in a heterogeneous environment. The objective of OT is more focused on the output yield rather than the system that generates the output itself.
The opposite is often true in the IT environment, which is usually more homogeneous, and the focus of IT is on the system and its management. IT teams often make use of data to create business value while also ensuring that the data is well protected in its domain.
Both sides, however, feel the issues of resource constraints, and they both want to solve enterprise-level problems, from sustainability to productivity.
With each having a different focus, IT/OT convergence is still very much a work in progress for many businesses, but it is an inevitable direction of the future.
Cybersecurity risks could be one reason why IT/OT convergence has not advanced more quickly. Other issues include technical complexities, cultural and organizational barriers and even a perceived lack of clear business value.
These obstacles need to be overcome as a business proceeds along its transformation journey. The IT and OT teams have to integrate more closely, combining both the data-rich IT expertise and domain and process knowledge of OT to the table in solving this complex problem.
Trying to digitalize without the best of both sides is like tying up one arm behind the back while competing in a race. The best way forward is through IT/OT convergence, which will help a business drive efficiency, productivity and profitability.
Finding common ground
In driving IT/OT convergence, edge computing is the “common playground” or unified platform for both teams to work on. It could play a central role in bridging the divide and ensuring that the resulting solution meets both external and internal requirements.
By having sufficient computing performance at the edge, businesses can make use of big data and IT tools to create practical solutions to overcome problems. Using the industry and local data that OT can provide will help such efforts to succeed.
Edge computing provides a standardized IT toolset to solve many OT problems today. Whether you are thinking of building management or manufacturing, the use of Industrial Internet of Things (IIoT) sensors and data analytics has enabled predictive maintenance and improved quality control.
Crucially, edge computing allows for data to be collected, processed and analyzed on-site so that real-time data-driven decisions can be made to optimize output yield and operation performance continuously.
Advanced video analytics, for example, could detect quality issues in production, and a manufacturer can quickly fine-tune its processes to improve. Not only does this boost quality, but it could also reduce the wastage of resources used.
With artificial intelligence (AI) and machine learning algorithms built into the infrastructure, edge computing can bring other real tangible benefits.
In remote locations, say, an offshore oil rig that depends on a satellite link, an edge computing system can do the heaving lifting of data analytics instead of sending the data offsite to the cloud, which not only adds to bandwidth costs but takes time to return with a result.
At the same time, edge computing allows for more streamlined operations. The use of IIoT and digital twins, for example, leverages the technology and expertise from both IT and OT to gain increased visibility and control over operational processes, lower inefficiencies and reduce errors. Any modification of the process could be tested in digital twin, and the impact on output yield could be projected easily. Many optimization ideas could be simulated in digital twin, and businesses will have the capability to select the best idea without physically building the costly modifications. Again, these bring tangible benefits that both IT and OT teams can measure.
Running close to the redline
What these advancements mean is that a business can run closer to its optimal level, much like how a car’s revolutions per minute (RPM) can be pushed close to the red line while operating safely.
This is only possible with a convergence of IT and OT, which offers real-time visibility of what is happening. With this, a business can keep fine-tuning its operations by turning incoming operation data into insights to better calibrate and improve over time.
So, data from a shopfloor is fed by OT systems to IT systems that convert it into insights, which are then used to further optimize operations on the shopfloor again. In other words, a positive feedback loop could recursively optimize the parameters for maximum output yield.
To be sure, not all edge solutions are able to tick all the relevant boxes. To overcome technical challenges, an ideal solution should be simple and reduce cost. For example, by using virtualization to consolidate workloads vs. running several systems in parallel. It should reduce the IT footprint, especially in constrained environments.
The solution should also reduce risk by being highly reliable and easy to service and maintain. It should be purpose-built for the OT environment and engineered to be fault tolerant. In a post-pandemic world, they are expected to improve resilience.
For successful IT/OT convergence, yet another important consideration is cybersecurity. IT security must be baked into every application in the OT environment. Think of intrusion detection, encryption, and secure remote access as some of the requirements needed for a new digital system to be running securely.
Edge computing systems can serve as an additional security layer between IT and OT as well. With built-in intrusion detection capabilities, they can uncover cyberattacks. By running tasks on one system, an edge computing system also reduces the data transmitted between IT and OT networks, thus reducing the potential for an attack.
A way forward
Today, IT/OT convergence often determines the success of many a digital transformation effort. In this, edge computing provides a platform for both teams to bring their expertise to solve business issues and demonstrate value.
One way forward is to start an IT/OT project on a small scale, then gradually grow it based on the result one gets. This incremental approach can help manage costs and show positive outcomes over time.
The good news is that these results can be shown in measurable KPIs. Even a small 1% improvement in efficiency, for example, could mean reducing costs, thus protecting profit margins in a competitive market.
The same can be said for sustainability efforts. By running more efficiently, thus using fewer resources to produce the same amount of product, a business can move closer to its environmental goals.
These tangible outcomes will be the best encouragement a business needs to accelerate IT/OT convergence. Using a common platform in edge computing, they can overcome well-known challenges and achieve breakthrough benefits that could make a big difference over time.