A Look At Today’s Digital Transformation

We’re generating more and more data every day but, are we properly using the data? Are we storing data in the right place? Are we getting the proper insights from the data?

Digital transformation is progressing rapidly in some sectors and less so in others. Here’s an overview of some of the factors that are at play.

Claudio Fayad, Vice President, Technology, Process Systems & Solutions, Emerson Automation Solutions

At the 2022 edition of Emerson Exchange, Editorial Director Gary L. Parr interviewed Claudio Fayad, Vice President, Technology, Process Systems & Solutions, Emerson Automation Solutions (emerson.com). The conversation focused on the current state of digital transformation and some of the factors that are enabling and/or discouraging progress. 

Fayad is responsible for product strategy and development of mission-critical platforms. He actively works with customers and stakeholders across the organization to develop innovative digital initiatives and extend Emerson’s DeltaV into a broader digital ecosystem. His 27 years of experience in the automation solutions business include previous roles in engineering, sales, project execution, project management, business management, product marketing and technology, participating in many projects around the world. He earned his electrical engineering degree from UNICAMP (Campinas Univ.) Univ. with a major in process control. He earned his executive MBA degree from Fundação Dom Cabral and is also a graduate of the post-MBA executive program from Kellogg.

The interview has been edited for clarity and brevity.

Where are we at with digital transformation. Do we have a group of companies that are well advanced and many that are experimenting with it?

It’s fair to say, companies are at different maturity levels of digital transformation. Digital transformation is a reality to the point where some companies in new industries—renewables, recycling—talk about sustainability, some of them are being born digital already.

We have some examples where companies are building digital twins to train operators. Their operational digital transformation is more focused on enabling operators in a constant way? We have other examples where we’re looking at simulation tied with digital twins. They do a virtual start-up because we’ve been doing virtual FATs (factory acceptance tests) for the DCS (distributed-control system) for a long time. Now they want to build this true simulation environment where they do a virtual startup a year before the plant is actually ready. As a result, the operators are upscaled and enabled for the startup, not just for the operation.

We also see the case where people approach digital transformation from, let’s get all the data together, let’s put everything on the cloud, and let’s figure it out. They are kind of taking a step back. The ones that had a purpose, say, let’s train operators, let’s optimize this process, let’s create an optimization mechanism, let’s do a virtual, have been very successful. Those that are born digital, have rethought their whole process and started from scratch, are very successful as well.

It seems a lot of people with legacy systems that don’t appreciate the power of digitalization or are satisfied with the status quo. Do you see that? 

At one point, for sure, it felt like everyone was looking at it. I used to say everyone wanted to be Amazon. Because you look at the complex operations that Amazon can do without missing a beat. They started those initiatives, some of them too big, and said, well, all we have to do is get the data together. A lot of them concluded there’s no value here.

As they’re rethinking that and putting the purpose on each one of their applications, they’re finding new value. So, it’s a mix. Now I think people say, oh, that works and this doesn’t make sense. In the end, everyone feels like digital transformation, combining the data in the proper way, solving those problems with digital transformation, does return value.

Is there still education to do for a lot of people? Or do you feel that there’s enough information available?

There is still education to do. It depends on the maturity level. There are a lot of automation groups and OT groups assembled from IT that are trying to figure the problem in the same way. Education will help those people.

There is an evolution even in the mindset of how to handle data and how to make data useful. We’re generating more and more data every day but, are we properly using the data? Are we storing data in the right place? Are we getting the proper insights from the data? Some industries, such as life science, are probably way ahead implementing and benefitting from the technology.

Also, digital twins. What is a digital twin? Is it just digital representation or is it digital representation plus simulation? A lot of people are still trying to figure that out and implement successful cases. I would say we’re much more mature and evolved than we were five years ago. The pandemic caused people to streamline their operations. They had to operate remotely and it forced them to kind of just get done with it. It was kind of education by brute force.

I keep my eye on the aftermath of the pandemic and whether there are positive things that come out of it and that’s one of them. People were forced to move forward, whether they liked it or not.

The nature of work has changed. Remote work may not be for everyone, but it is here. Hybrid work is here. We realize we don’t need to travel as much. We like to see people but you don’t need to travel every week. You don’t need to travel for a small meeting. When you think about people working remotely, how can they tackle problems if they don’t have a common understanding and perspective of the problem? What’s going to give that? Digital transformation. How can I help an operator solve a problem if all his notes are on a piece of paper or spreadsheet. As people work remotely more and more, it becomes an issue of partnership and collaboration.

There are very few challenges that we can solve individually. Most have been automated in some way, shape, or form. So how you drive collaboration that will result in a single digital understanding of the problem, of the things you’re trying to optimize. We see people five years ago, seven years ago, who were talking about the DCS as untouchable. It has to be air gapped. It cannot be connected. People don’t care about that anymore. We need it connected. The cybersecurity models have to evolve because you can’t be a sitting duck, but people are willing to deal with that risk.

One pre-pandemic thing that will stick in my mind for a long time is the issue of data in the cloud and the resistance to allowing any data to be stored outside of the plant. The other thing is resistance to remote access and control. Today, we view both of those items quite differently.

Now, if you say, I have a data center. What do you mean you have a data center? You’re not using the cloud? You think about security, in many cases, the cost for you to establish and maintain your own security policies against what cloud suppliers can give your data as long as you trust that supplier. It’s more protected there than if you have a whole army of people to just protect your data within the plant. 

That leads to cybersecurity. The message is it’s never a one-and-done thing. It’s continuous. Do you see the same thing for digital transformation? Is it a continuum or a set-it-and-forget-it situation?

That’s a great question. There is an initial hurdle to be overcome. You have to establish the infrastructure. That’s kind of one-and-done, more stable. A control system will evolve over time. It will grow, but it grows in a structured, planned way. As you start thinking about how to combine the data, the data model, the way data is combined will evolve over time. Because, again, if you just say, I don’t know the problem I’m trying to solve, I’m just going to get all my data dumped somewhere. You’re only as good as that. So you’re going to be thinking about your problems, and you’re going to be preparing your data model and that’s going to be an evolution. 

In some cases, you’re going to be looking at raw data and say I like this, but I need this data with this context connected to that data. Then you start building a knowledge base and that’s going to be an evolving effort, just like people do in general with IT. And that’s a big difference, because OT was, let me install it and I’ll pay you money to let me forget about it. Don’t touch it, don’t change it, don’t move it. 

Now what we are seeing, is people thinking about new devices every day. I want to optimize this but I don’t have the data. The first thing I need to do is install instruments to get the data. Now that I have the data, how do I connect it? We have to make it so the infrastructure is there and it’s easy to extend, easy to connect, and easy to tie back to the digital twin.

Because that’s the other thing. The digital twin and the modeling cannot be static. If you build a plant, you build the digital twin. You’re going to be happy using it for the startup, for a few years, but all of a sudden you have to create a continuous-feedback loop, change the plant, change the business model, do some optimizations. The moment you stop doing it is like your garage. When it’s all clean, it stays clean. You start moving things around and, in a week, it’s a mess. That’s what we see happening is that you have to find a way that you tie in your process so your digital twin, your digital transformation, keeps delivering value or you’re going to lose interest. At that point, everything will break because it needs to be properly maintained and evolve.

Are you seeing customers change their culture? Are younger people making it easier to develop a more collaborative culture?

Yes, we are. But it is not just a company. It’s the culture of the whole industry. The culture is changing in the understanding that OT and IT are different. But they can leverage technologies, they can leverage policies, but they sometimes need specific policies. And I don’t know if it’s just young people being involved, though that’s definitely a factor. They’re more comfortable writing code, writing scripting, integrating those technologies. But I think it’s just maturity of the IT departments understanding the domains are different.

Cybersecurity actually made people think about that in a different way. Because the thing that involved IT everywhere was cybersecurity. When you say, I want to make my plan secure, they don’t ask the OT guy, they ask the IT guy. Now they have to understand what the OT guys are doing. Then they want to implement the IT policies. No, we can’t do that. It is the education, the learning that kind of started with that exchange. Young people, who are more tech savvy, kind of helped with that. But cybersecurity actually brought a lot of that together.

We see a lot more IT folks in our meetings than we used to before and we see people more comfortable with that. Because it’s no longer IT trying to take over. We need to work together. EP