Bridging the gap to IT/OT convergence
Author : Jason Andersen, Vice President, Business Line Management at Stratus Technologies
12 December 2017
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For over 20 years there have been discussions about IT and OT convergence, but meaningful progress has not been made. Divisions largely continue to persist but there is promise that it’s about to change. Now, as companies become more involved in the Industrial Internet of Things (IIoT), adopting new infrastructures and Big Data, we are seeing the need to bridge this divide.
But how can companies start to successfully merge these two disparate parts of the business, what are the benefits and what will this mean for future business models? Jason Andersen, Vice President, Business Line Management at Stratus Technologies offers his thoughts.
The drivers
First, let’s start with what is driving this need for IT/OT convergence. Jason outlines three main factors:
1. Skill sets
Traditionally, IT has a deep skillset focused on computer enabled technology whereas OT has a very broad understanding of the production plant with its control and production equipment. The priorities, measures and incentives for each field of expertise are different and until recently there has been little need for much cross-over since they worked independently. The IIoT brings with it a step-change for the OT side, as they become less focused on tools and much more on data. While for IT, the same change means that the plant information needs to be brought seamlessly into the enterprise management for timely decision making. As control becomes less centralised and production technologies and equipment more intelligent, IT is also required to move out onto the plant floor or into the field – to the ‘edge’. This further blurs the lines and requires an IT/OT hybrid approach; the ideal engineer to meet the challenges of implementation and maintenance of such systems would have both IT and OT skills. In reality, such engineers are rare at best.
Somehow the two departments must find common ground and work to build the new combined skillset that will carry them into the IIoT era.
The aim should be to organise a team made up of IT and OT operatives that takes advantage of both skillsets so it can move faster and be more agile to meet business needs. This ‘hybrid OT’ approach is starting to show dividends for those at the front of the IIoT adoption curve.
2. Cost efficiency
Implementing IIoT programmes can be financially daunting. For multi-site industrial enterprises, bringing each site into line with the others across the business can offer huge efficiency savings such as the ability to reduce the different skills required to service the plants and apply best practises throughout the enterprise. But this kind of investment can cost a lot of money and needs to be based on predictable ROIs. For smaller industrial enterprises, the job might be bringing different lines at the same site into step with others or connecting different production silos to the enterprise management and resource planning systems. As the technology of the IIoT era becomes simpler to deploy and takes advantage of open standards, the cost barrier is reduced. Moreover, as industry accepts that IIoT is not only a preferable long-term approach but an inevitable one, it becomes clear that overcoming the challenges associated with bridging the gap between IT and OT is critical.
3. Technology footprint
The size and complexity of industrial networks and IT infrastructure is being reduced by many early adopters of IIoT principles. Consolidating the technology footprint ties into the cost efficiency driver, and makes use of virtualisation of operational applications. This moves traditionally hardware oriented networks of cables and servers into the realms of software and introduces more cloud-like approaches working closer to the edge, where the data is collected and processed before being centralised for decision-making. This reduction in a company’s ‘technology stack’ can be very beneficial in reducing the complexity and skills required to maintain it, especially where low-human-touch sites, such as dangerous or remote areas of production, are concerned.
IT/OT or IT vs OT?
Despite these drivers, the IT and OT parts of many businesses remain at odds, and despite evidence of pioneering companies starting the convergence process, Jason feels animosity between the two teams can still be found.
For OT, stability and reliability are crucial and they often adopt the ‘if it ain’t broke, don’t fix it’ policy. IT is generally more comfortable with change as servers and software are updated all the time, and can better cope with some downtime to upgrade or update systems, since it is usually a quick process that won’t affect productivity adversely. In fact these two approaches are deeply rooted in habit and culture – and both should be harnessed for effective transition to IIoT. But the human dynamics will be one of the biggest challenges going forward. The UK has a large generation of engineers that are facing retirement and they’re going to be a lot more reluctant to learn new approaches or apply new methods. It’s much easier to change when you have an influx of fresh faces, particularly digital natives, those born from the early 90s onwards, since they have an expectation of how technology should enable and enhance everything they do. We’re definitely seeing convergence accompanied with some new blood coming in, but the problem here will be recruiting enough people to the sector to fill the widening skills gap.
How can we actively recruit new people?
In his previous employment at IBM, Jason noticed the level of academic involvement was especially high. Students from the world’s top universities were heavily involved in the Cloud and in standardisation processes etc. He doesn’t see the same collaboration between the industrial and academic world on a global scale. This becomes an issue as it’s important to cultivate skill sets before they enter the workforce.
One thing Jason saw in South Africa this year was Wonderware, the Schneider Electric software team, actually build their own training programme because the number of people attending university is so low. Jason emphasises how impressed he was with the level of awareness on the need to train up OT technicians and he doesn’t understand why this isn’t happening on a global scale. It’s so important for industry to reach out to the academic world.
Furthermore, successful convergence is down to leadership. Leadership has to embrace the challenges, bring in new people to help define the future, but also understand the risks. There’s a high level of pressure on leaders today to deliver results but businesses have to acknowledge this is a 5-10 year transition with costs involved. If you don’t it embrace it, there’s a chance you might be displaced.
Emergence of new skills
There’s no doubt that the IIoT will bring about new skills and ways of working. The easiest one to start with is the approach to analytics; think about a sales manager today compared to one ten years ago, they’re going to have to become much more data and analytics aware. Instead of running the business based on well-established processes, they’re going to have to take a look at the KPI’s (Key Performance Indicators) of the business and work out the best way forward. These types of adjustments happen naturally when you start to become more data driven.
Further, there’s the drive to become more industry aware. IT and OT employees are going to need to extend their knowledge pool to achieve this. We certainly can’t expect an IT person to become aware of how automation systems work or vice versa but Jason thinks there definitely has to be some form of cross training so at least there’s a high level of understanding on how both can work together.
The security concern
The biggest problem we have is security and cyber security technology is designed for the datacentre, not the edge. There’s a lot of different edge solutions out there but none of them are really designed for the operator, it’s all IT driven.
A lot of these edge-based systems are ‘set it and forget it’ and that’s just not acceptable if you are connected to the Internet, you have to constantly stay on top of protocols, best practices, and software defences. How can you do that if you have no IT skill sets? If you think about IoT and IIoT, a big function is delivering technology in places where there are no people. So you have to get to the point where the technology is absolutely seamless and safe.
Bridging the gap
Whether you’re a large corporation or an SME, IT/OT convergence is an important part of your digital journey but the strategies used to achieve this can vary. Small companies tend to be more distributed with fewer people, whereas bigger companies, like an automotive manufacturer, have datacentres and IT people onsite and a wider range of resources. So it’s important each company tailors their approach to suit their individual needs.
Yet, after numerous discussions with analysts, Jason found that there is actually no single ‘best practice’. Some organisations are putting all OT resources under the IT department, working for a Chief Information Officer (CIO). Whereas in others, they’re taking the IT department and placing them under the head of operations.
However as a first step Jason does advise aligning your management systems and performance metrics. Organise the teams in a way that makes sense for your business and then it’s up to each individual company to work out the best process for them.
Looking ahead: the four I’s of IIoT
Stratus Technologies refer to four stages that allow companies to measure their current level of automation and their ability to start reaping the benefits from IIoT:
1. Informed – at this stage you’re already utilising your traditional supervisory control and data acquisition (SCADA), human-machine interface (HMI) and historian database solutions. Many industry analysts believe the evolution of these technologies will naturally support the adoption of IIoT.
2. Insight – now we see the addition of analytics. Companies can now analyse the data captured across the entire production value chain and start using it to optimise processes.
3. Intelligent – once you’ve completed the above step, you can start to make real time, intelligent decisions.
4. Invisible – this is the part where artificial intelligence comes into play. Your systems are now able to identify and fix problems without human intervention.
Most companies today are at the first step, they’re informed and they recognise the need to change. As they work their way through the stages, they’re deploying technology in a much more distributed way and potentially reaching into the supply chain or on to customers more directly, bringing them ultimately closer.
Right now everyone is focusing on efficiency, predictive maintenance and the cost side of the equation, allowing companies, in 5-10 years, to invent new business models.
Jason hopes that this time next year, we’ll be talking to companies about how to move from sandbox pilots to real deployment and moving progressively through those four I’s of IIoT.
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