In today’s world data is more valuable than ever. Famously referred to as ‘the new oil’ in 2006 by British mathematician Clive Humby, by 2025 the world is set to produce 463 exabytes of data per day.
But when it comes to harnessing this vast quantity of data, organisations today must focus on creating business value. Illustrating this is Arnaud Langer, Global Managing Partner - Edge & IoT at Atos.
With more than 15 years of experience in the IT industry, Langer first studied as an electrical engineer, before later moving to Atos. There, his initial projects around connected vehicles not only marked successes in Europe but also paved his way to the US, where he expanded Atos’ offerings in big data, AI and machine learning.
With extensive experience across the fields of IoT and big data, Langer discusses the early days of IoT, where the emphasis was on connectivity for its own sake. “The goal was really to connect everything, without necessarily knowing what we would be able to do with the connected things themselves,” he observes.
This insight extends to big data initiatives, where companies amassed vast data lakes without a clear strategy for deriving value. It was this realisation that spurred a strategic pivot at Atos, under Langer's leadership, to focus on the end goal of creating business value from data. “We need to collect data from something, even if it's remote, and then we need to connect it so that the whole data chain makes sense,” he asserts. “That's why I decided to create that offering and then that line of business within Atos. We take the data from wherever it is needed, but ultimately we start with the end goal, which is to make money with what we're creating.”
Atos' approach under Langer's guidance has been to develop a platform that – while complex – delivers a comprehensive solution to customers at what the company describes as the Far Edge: edge computing infrastructure deployed in a location farthest from the core data centre and closest to the users. “We've been able to develop the whole platform so that it can be a giant black box that we deliver to the customer,” he explains.
“We've got the right hardware and the whole data platform. We've been partnering with a few companies out there, but I'm pretty happy that now we have an offering that makes sense. That offering is pretty complex, but at the end of the day we now have a good opportunity to make money with data which, as we all know, is the new oil.”
Atos supporting customers on their edge transformations
The edge is – like Atos’ black block solutions themselves – a complex environment. At the heart of Atos' strategy for edge transformations is recognising these complexities, and simplifying these journeys for clients.
Highlighting the challenges of managing devices in diverse and remote locations, this complexity is twofold.
“First, the device is in the field, and not in a data centre anymore,” Langer explains. “As a result, you cannot have your IT department available 24/7, ready to look at why a box is blinking red, instead of green.
“Secondly, you have a different scale of management. If you have a complex infrastructure in a data centre, it's a few racks. At the edge, you've got thousands of locations and therefore you have all sorts of diversity in the field. One location will be cold, the other one will be hot. One location will have cellular network available, the other one will be cable only.”
The scalability, diversity and management of edge devices call for a nuanced approach, emphasising automation and foresight to avoid repeating past mistakes.
“You have to have automation and the right level of decision-making that is automated by the management platform, so that you can be successful in deploying edge deployments,” Langer says, advocating for a thoughtful approach to edge deployments. “Otherwise, you're going to have the exact same issues that we had 15 years ago when we started with IoT.”
Atos SmartEdge for Business Outcomes: Turning data into decisions
Atos’ SmartEdge for Business Outcomes initiative highlights the company’s expertise in turning data into strategic decisions. By taking a holistic approach, Atos enables clients to leverage data effectively, balancing the need for detail with the imperative for cost-efficiency and scalability.
“Over the years we have been able to combine a pretty deep portfolio of technological items, so that we can provide an offering that's completely abstracted from the technology to our customers,” Langer says, highlighting how Atos’ approach involves a tiered structure of Core, Edge, and Far Edge computing, ensuring that data management and processing are optimised across different environments.
With these complex ecosystems, with different infrastructures and sets of software, Langer describes how it is crucial to have the right software in place.
“You have to have a unifying software that brings everything as a whole so that you don't lose control and you still are able to run automation for management, monitoring, deployment, security all together.”
Real-time data and applied AI driving business value
Real-time data and applied AI stand as the cornerstones of Atos’ strategy to drive business value. Langer advocates for a lean approach to data management, focusing on essential data points to ensure cost-efficiency and scalability.
When it comes to extracting value from data, businesses should consider two things: the amount of data, and where the value comes from. To illustrate this, Langer uses the example of performing analytics using computer vision on video feeds.
“You could say that you want the best camera to have the clearest picture, to make sure that the AI runs right and can detect a specific kind of dog, instead of just identifying a dog. But the business question is, do I need that quality, or do I need to know that information?
“If you are using a 4K camera instead of an HD camera, you are multiplying the number of pixels and therefore multiplying the amount of analytics that you want to run. Therefore, you are getting into a more expensive infrastructure, with more energy consumed, more maintenance and more potential failure points.”
By following Atos’ approach, organisations can be more lean when it comes to data - reducing the cost of infrastructure and leading to widespread benefits.
“I'm all for having all the data of the world available. Specific companies do that, but that's not what every enterprise should do. And that's exactly the opposite of what I'm advising my customers to do,” Langer adds.
“If you want to use ChatGPT internally, go for it. But if you want a specific business case, we need to be very lean. What we plan for our customers is scaling up. We start with a single business case so that we can establish a good foundation, but still scale up the infrastructure and the software, so that everything is flexible.”
How Atos edge and cloud solutions have delivered benefits for customers
By employing edge-enabled predictive maintenance, Atos has improved customer experiences and operational efficiency. Langer cites a specific case with a theme park in Orlando where predictive maintenance has reduced queue times for rides, enhancing the overall customer experience.
With theme parks attracting thousands of visitors each day, ensuring that all attractions function properly and are open to the public on a continuous basis is a question of reputation and customer loyalty.
“One of the ways to have happy customers is for customers to wait less in a queue to get on a ride,” Langer explains. “How do we make them wait less? We make the ride get more people every hour on it. How do we do that? We need to make sure the ride works. How do we do that? We predict failures.”
As a result of Atos’ solution, the theme park operator has been able to eliminate inefficient preventive maintenance and carry out more highly targeted predictive maintenance, leading to less downtime, lower costs and happier visitors.
“By having the right data management, AI and everything, you can predict failures. If you predict failures, the ride is available for more people, and the customer is happy.”
Atos’ vision for the future of Edge
Looking ahead, Atos envisions a future where edge technologies blur the distinction between operational technology (OT) and information technology (IT). Langer foresees a landscape where edge devices resemble smartphones in their ease of use and integration, and as a result democratising data access and analytics.
“One part of our vision is how we can automate the whole ecosystem. We're already working with partners on automating the onboarding of devices, similar to when you switch a smartphone to the newer model, where you input a username and password and it gets all your data, contacts and applications.”
As Langer describes, Atos also aims to bridge the gap between OT and IT. “I've heard customers, who were really on the OT side, telling me that our solution seems very IT heavy. In OT, usually you don't run software updates. You install some equipment and 15 years later you change it, but in the meantime, no one connects to it.
“We are getting to a point where that piece of equipment can run for 15 years, but we need to extract data from it. The more we are going to evolve at the edge, the more previously isolated and protected devices and data will become connected and smarter.”
World starting to acknowledge the need for the edge
Langer anticipates a surge in the market for both edge computing and AI. He foresees widespread adoption of AI and edge technologies by large companies, driven by a growing recognition of their importance.
The concept of Sovereign AI also highlights an emerging trend where businesses seek to develop bespoke AI solutions tailored to their specific needs and data governance requirements. This approach ensures that AI models are not only customised but also operate within the regulatory and ethical frameworks pertinent to the business or region.
“How we get that AI on board and just make it for us is where the market is going,” Langer predicts. “I don't see any large company that will not have any sort of AI or Sovereign AI or edge in the next 18 months. I think overall we are going to have a widespread AI and development and utilisation across the board.
“I think that the world will start to acknowledge the need for the edge. AI is becoming mainstream, and the question is not if companies are going to embrace AI, but how? Therefore, they start getting to understand that edge will be part of the equation. I really see an explosion in our market in both edge and AI.”
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