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Best Practices in the IoT to Promote Collaboration between IT and OT

Business transformation leaders will be unable to substantiate their contributions to IoT initiatives if the challenge of IT and OT collaboration is not resolved.
By Chad Meley
May 24, 2017

An agile shared data architecture has become a critical business requirement, and will ultimately accelerate digital transformation across businesses. For the purposes of clear differentiation, information technology (IT) systems include any use of computers to process, store and secure data in any form.

Operational technology (OT) controls the physical processes, devices and technologies that run manufacturing plants, trains, oil rigs and other heavy, complex assets that make up modern industry. Many IoT projects are initiated within OT, but often without the involvement of the IT team. OT professionals tend to be skeptical about partnering with IT pros, especially when that collaboration involves ceding control of systems and data. Yet, like similar evolutions of data-driven process redesign, transformational outcomes only occur when the line of business eventually includes the IT organization.

Fortunately, we can look to lessons learned from experience, along with early successful Industrial Internet of Things (IIoT) case studies, that begin to form best practices that IT professionals can use in bridging the divide with OT.

IT has a great deal of expertise and resources to offer to the OT community with respect to core enterprise data outside the purview of OT that provide essential business context to sensor data, the lifeblood of IoT. Additionally, IT offers powerful analytical capabilities to glean insights from sensor and core data. Despite that, in order to win over OT, IT will need to make investments in an agile shared data architecture.

OT analytics functions and applications include modeling, performance monitoring, feedback control and fault tolerance analysis. Yet one of the most common reasons that those outside of IT elect to develop their own analytical infrastructure is a belief that IT has different and unique goals. OT and IT departments may pursue objectives that can often seem at odds. By definition, IT seeks overall business agility and revenue growth, while OT is focused on machine and infrastructure reliability and efficiency. IoT introduces new opportunities to improve efficiencies for both teams. As a result, projects will meet fewer obstacles if staffers share a common approach: a set of standards and architecture plans. This shared architecture must meet the diverse needs of OT, IT and other IoT business stakeholders.

Alignment is created by formulating, documenting and socializing policies that use the words "must" and "should," acting as both a contract and roadmap. The most effective shared data architectures establish the foundation for long-term success, but also clarify specific objectives and generate value quickly. It's about prioritizing objectives, balancing competing imperatives and thinking through architecture, infrastructure and toolset decisions within the broader context of business goals.

Further, OT will introduce a certain amount of chaos into the life of the IT organization, by involving the use of thousands of devices sending data constantly, most of which won't conform to the existing enterprise architecture. OT knows the source, structure, meaning and potential uses of this data, necessitating a new era of citizen data integrators and stewards.

A common success criterion for any modern information architecture involves adding vital flexibility for exploring unrefined data, and experimenting on emerging theories without the long planning cycles typically imposed by IT. This is enabled by a suite of solutions that simplifies the process of loading, managing and analyzing data by providing a level of self-service previously unavailable in IT systems.

An agile shared data architecture will not only accelerate the adoption of IT capabilities by the OT organization, but also accelerate digital transformation for the entire organization.

Chad Meley is the VP of IoT marketing at Teradata. He has a strong background in the Teradata Unified Data Architecture and related Big Data Analytic Services.

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