Trends push IT and OT convergence opportunities and challenges
The use cases that come from IT/OT convergence and the global spread of supply chains, edge computing and 5G might make the effort to overcome convergence challenges worth it.
Many discussions of IT/OT convergence highlight its challenges, such as security and scalability, but new technologies and lessons learned in both IT and operational technology create opportunities for innovation.
"What we want the end state to be is OT becomes the interactive real-time edge for IT, and IT becomes the elastic compute cloud for OT. That way, IT can leverage IoT better and OT can leverage data analytics and AI better," said Mac Devine, IBM fellow and vice president and CTO for strategic customer success of Watson's cloud division, during an IoT Slam session on Dec. 11.
As asset data moves outside the bounds of the machine and the vendors who support the data creation, IT and OT must work together and build trust.
"IT is becoming the custodian of the data and it has to create services that are important to OT. They have to step up to this new world of lots of legacy and proprietary systems and realize that they will have to support them for a long time in the future. While IT often becomes the final buyer of many IT/OT convergence projects, OT is [focused on] the end user," wrote Vernon Turner, founder and chief strategist at Causeway Connections, in an email.
To achieve these goals for each team, organizations must first understand the differences between IT and OT.
Identify where IT/OT convergence faces challenges
In the IoT Slam session "Finding harmony for IT/OT convergence when IT is from Mars and OT is from Venus," Devine defined IT as mostly open, software- and services-oriented, information-centric and cloud-savvy with multilayered security. OT is mostly closed, IoT-savvy and operations-centric with localized security.
IT and OT teams have differing perspectives within security alone. IT typically talks about cybersecurity, while OT focuses on physical asset and location security. When asset data moves beyond its generation points, greater security and teamwork is necessary to avoid malware attacks throughout OT industrial networks and to protect data once it's in the cloud.
"IT/OT convergence means different things to different vendors … what quickly happens is that more effort is spent on integration between IT and OT solutions and less time on innovation. The outcome is that OT sees longer time to value and is less trusting of IT," Turner said.
Trends drive IT/OT convergence opportunities
Since 2010, technological innovations have driven IT to move to as-a-service models, which decrease upfront expenses and enable organizations to explore new technology, Devine said. OT hasn't had the same innovations, which creates the opportunity for OT teams to use some of the lessons learned from IT innovation challenges.
Automation at the edge has been a key part of OT. With expanding edge computing use cases, OT must meet more requirements to advance automation, said Jerry Chen, head of global business development for manufacturing and industrials at Nvidia, during the session.
Organizations have found it difficult to use traditional equipment to control more complex use case processes, such as fabricating features onto wafers on the nano scale, Chen said. Edge AI capabilities applied to OT creates more flexibility at the edge and boost the ability to perceive data and change behavior accordingly in a more scalable way.
What we want the end state to be is OT becomes the interactive real-time edge for IT, and IT becomes the elastic compute cloud for OT.
Mac DevineIBM fellow
Historically, IT excluded real-time OT localized data and OT lacked IT data aggregation. Edge AI capabilities require both real-time computing and aggregation. Organizations have struggled to incorporate IoT and edge data into current processes because the data must be actionable in real-time, Devine said. Organizations must feed the data from the physical OT system to learn from it and make decisions from it.
To aggregate data, organizations must break down data silos in different systems, such as manufacturing supply chains. Approximately 75% of data loses its value in milliseconds and data is only valuable to organizations if it is actionable, Devine said.
If organizations must send data from the edge to the cloud, then real-time actions aren't viable. The challenge is getting an aggregate view across data silos to take localized action, but when real-time aggregation is achieved, organizations can derive more insights and look for new revenue opportunities.
"IoT is the great provider of data. CEOs and CIOs [must] continually look to see how data can fuel digital transformation and drive innovation. IoT data is the fuel for analytics, machine learning… but it's also the source for CIOs to help fuel new business models [such as] as-a-service [and] work from anywhere," Turner said.
Real-time data analysis also will provide an opportunity to increase the physical security of machines and information security. AI for security looks at the normal behavior of endpoints and equipment and can flag any anomalies and take protective actions before it's too late. Traditional security models respond to breaches reactively, but AI can act in real time and predict threats.
There are also opportunities for supply chains to benefit from greater IT/OT convergence. 5G can drive real-time data processing opportunities for global operational insights.
Organizations must be efficient and data-driven to handle far-reaching supply chains. Network and connectivity technologies, such as 5G, are key to organizations adapting on a global scale. IT and OT teams also have different perspectives of what 5G means. In the IT world, admins see 5G as incremental to what they're doing, while OT teams see 5G as fundamentally disruptive, Devine said.
