Bridging the IIoT gap: How Information Technology (IT) and Operational Technology (OT) can Work Together

As companies across the energy value chain look for ways to become more efficient and agile, the Industrial “Internet of Things” (IIoT) offers attractive opportunities. Harnessing sensor data, machine-to-machine (M2M) communication and Big Data analytics enables oil and gas companies to take automation and efficiency to new heights, while creating the foundation for new business models.

But to realize the potential of IIoT, companies must first bridge a yawning gap: the technological and cultural divide that often separates their information technology (IT) and operational technology (OT) organizations.

Why the divide? In most industrial organizations, including oil and gas producers, IT and OT traditionally have different priorities. For OT, ensuring the uptime of production automation systems is paramount. Reducing risk is the top priority, which is one reason why automation systems are often in service for years, if not decades—change equals risk. For IT, innovation is the top priority, often leading to continual change and upgrading. This difference in priorities helps explain why OT often insists on keeping automation systems completely isolated from IT.

The IIoT changes the status quo, creating a new imperative to share data from machine sensors and automation systems managed by OT—including SCADA (Supervisory Control And Data Acquisition) systems—with enterprise resource planning (ERP) systems and analytics platforms managed by IT. How can oil and gas companies bridge the gap between these two worlds, while ensuring that the competing priorities of OT and IT are met?

Three approaches

One approach employed by some energy companies is to effectively merge the two, integrating OT within the IT group. On the surface, this seems like the most straightforward approach, essentially forcing OT and IT to work in coordination. In practice, however, the cultural differences can remain. For example, IT may try to impose its standards-based approach on an OT team used to systems specialized for particular production tasks. Unless IT has a clear understanding of the requirements of these automation systems, the result can be a lack of coordination that decreases system stability. For this approach to work, OT must have a voice in the combined organization.

Another approach is to create a technology team free from these traditional distinctions, responsible for all OT and IT functions. This approach is feasible in an entirely new organization or for a large company spinning off a new satellite organization. But for most large, complex oil and gas producers with established technology groups and lots of legacy infrastructure, it may not be a workable alternative.

The third approach is one we’re seeing more and more in forward-looking organizations, where there is a new breed of “industrial technologists” who have a combined IT/OT perspective. They understand the need for stable, highly available automation systems, but they also understand the enterprise system integration and analytics required to make the IIoT a reality. With a foot in both worlds, these industrial technologists play a key role in ensuring that the priorities of both OT and IT are met.

Showing OT the value

Overcoming the cultural divide between OT and IT will likely be a gradual process for many organizations. A key step in facilitating that process is showing the OT team the value of the IIoT and of “opening the door” to their automation systems and data.
For example, gas gathering operations could turn the manual, inaccurate process of reconciling the production imbalance sheet into a remotely automated process, laying fiber or using wireless, to all of their remote facilities to relay sensor data to a centralized analytics system. This can allow them to access accurate imbalance sheet data for all production sources in near real time, without tying up valuable staff time.

Another example near and dear to OT is that of predictive maintenance. Sensor data for a range of operational parameters can be collected for individual equipment components and sent to analytics engines or machine learning systems to detect anomalies—such as vibration patterns on compression turbines or temperature excursions on a motor—before a failure occurs. This can reduce unplanned downtime, the bane of OT, while also helping identify the optimum maintenance or replacement intervals, minimizing costly planned downtime and capital expense.

Reducing the risk of change

A critical success factor when merging OT and IT functions is effectively managing risk. OT must be assured that SCADA systems and data will maintain the highest levels of availability. That means building in fault tolerance for all mission-critical systems linked to production.

Availability is especially critical given the cost pressures the industry is under today. With technology staffs cut to the bone, it is essential to ensure that automation systems at remote locations—such as compression stations, well locations and storage facilities—stay up and running. If someone has to travel to the location to deal with an outage, production could be impacted for days. Moreover, building in availability helps avoid the inevitable finger-pointing between OT and IT if an outage were to occur in a converged IIoT infrastructure.

The benefits of the IIoT are too attractive not to take advantage of them. Bringing OT and IT together in a way that effectively manages risk is the key to unlocking the tremendous potential of the intelligent, automated energy enterprise.