Why the transition to IIoT will be an evolution, not a revolution
Author : Jason Andersen, Vice President Business Line Management, Stratus Technologies
17 January 2018
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Listen to technology vendors and you’ll likely hear about the “IIoT revolution.” They focus on the transformative impact the IIoT will have on every aspect of industrial automation. And in some respects, this is true. The vision of an intelligent, connected automation infrastructure has the potential to dramatically reshape how industrial enterprises operate. But the journey will be strictly evolutionary. And there are good reasons for this, Jason Andersen of Stratus Technologies comments.
Evolution vs. revolution
Not all technology shifts are the same. For example, the migration to the cloud truly is a revolution, in the sense that it is a binary move: You are either performing application workloads in the cloud, or you are not. There is no “transitional state.” Indeed, the “all or nothing” nature of cloud computing is a key factor keeping many industrial enterprises on the sidelines for now, sticking with their existing datacentre infrastructures for their business-critical applications.
At the operational technology (OT) edge, a revolution is just not feasible for some very practical reasons. First, most OT organisations have their hands full just managing their existing infrastructure; the challenge of creating a completely new architecture from the ground up is just not an option. Second, the idea of purchasing an entirely new automation infrastructure at once just doesn’t fit with the capital investment profile of most OT organisations. They generally take an incremental approach to limit both financial and operational risk, with an eye toward depreciating these assets over long time horizons.
So what does the evolution to IIoT look like for enterprise automation? I believe there are four key steps, with each step building on the one before it.
1. Modernising Systems
Updating OT systems is the first, fundamental step on the journey to IIoT. In many industrial enterprises, this is long overdue. It’s not uncommon to find old systems at the edge that are long past their freshness date. As long as they kept running, they were largely ignored. Replacing these systems with new, standards-based hardware and software will deliver immediate benefits in terms of performance, reliability and cost savings over time, while setting the stage for subsequent steps toward IIoT.
When modernising the automation infrastructure, selecting systems that offer improved security and availability is an obvious priority. Not so obvious - and often overlooked - is the need to prioritise serviceability, as well. OT organisations are often stretched thin and generally do not have the advanced technical capabilities common in the datacentre. Selecting platforms that are designed for ease of service, including support for remote servicing, will pay tremendous dividends in terms of uptime, as well as reducing the burdens on OT and IT staff.
2. Connecting Devices
Bi-directional exchange of data to and from devices and sensors and the delivery of device data into the cloud is a critical pillar for IIoT. That means connecting edge devices and systems that have traditionally been operated as isolated “islands.” Many OT organisations have resisted connectivity, believing that it introduces a new element of risk to business-critical automation systems. After all, if the system running a key production line or gas pipeline isn’t connected to anything else, it can’t be hacked, right?
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To address this concern, it is important to select connectivity approaches and solutions that support appropriate levels of security between industrial automation systems and the IT resources they connect with - including data warehouses, ERP systems and, ultimately, analytics engines.
3. Leveraging Real-time Analytics
For many, the notion of using real-time analytics to create an “intelligent” automated enterprise is the holy grail of IIoT. And there’s no question that tremendous potential value lies in the promise of real-time analytics, harvesting Big Data generated by the connected OT infrastructure to optimise operations on the fly. For example, “smart” supply chains that automatically optimise production based on a granular, up-to-the-second understanding of each link in the chain, from materials pricing to equipment dynamics to market conditions.
The most exciting potential for real-time analytics, however, does not lie simply in making operations more efficient. Rather, the real promise lies in analytics’ “killer insights” that help increase top line, rather than bottom line, growth. Once these come into focus, expect to see more industrial enterprises accelerating their adoption of real-time analytics.
4. Optimising Operations
The journey to IIoT is not just a technological shift but a cultural one, as well. The IIoT raises new questions that challenge the traditional roles of OT vs. IT. Who owns and manages this new, connected infrastructure and the data it generates? What new governance policies must be developed…and who will enforce them? Will the OT organisation require new skill sets to operate and manage this IIoT environment?
Thinking strategically about “the people factor” is a key step for optimising your operations to achieve the full potential of IIoT investments.
Let the evolution begin
Viewing the journey to IIoT as an evolutionary process helps place the risk/reward calculation of such a migration into a more realistic perspective so that enterprises can get started on their way. Taking a stepwise approach guided by a clear set of priorities will enable companies to reap rewards at each step, making the most of their investments as they move to modernise their infrastructure, embrace connectivity, take advantage of real-time analytics, and optimise their operations. Starting this evolution now will give them a head start toward tapping the full potential of the IIoT to create the automated enterprise waiting just over the horizon.
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