Defense & Intelligence: Adopting digital engineeringwith Rob Clifford
On the first episode of our Defense and Intelligence mini-series, Microsoft’s AT Ball is joined by Rob Clifford, Chief Data Officer for BAE Systems, Maritime and Land Division.
Episode 44: Defense & Intelligence: Adopting digital engineering
Public Sector Future
On the first episode of our Defense and Intelligence mini-series, Microsoft’s AT Ball is joined by Rob Clifford, Chief Data Officer for BAE Systems, Maritime and Land Division. They discuss how digital engineering with agile approaches and cloud-enabled technologies can help achieve mission outcomes.
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How digital engineering can support defense organizations
On the first episode of our Defense and Intelligence mini-series, Microsoft’s AT Ball is joined by Rob Clifford, Chief Data Officer for BAE Systems, Maritime and Land Division. They discuss digital engineering and how organizations can move from traditional engineering models into development with agile approaches and cloud-enabled technologies.
– Rob Clifford
– Rob Clifford
– Rob Clifford
– Rob Clifford
Introducing guest host AT Ball
For January, Public Sector Future is dedicating a set of episodes to exploring opportunities for digital transformation in defense and intelligence organizations. Guest host, AT Ball is part of the Defense and Intelligence team here at Microsoft. Prior to joining the team, he had a 30-year career in the US military where as a distinguished commander and aviator, he built extensive, on the ground experience in operations around the globe.
Ball’s first guest is Rob Clifford, the Chief Data Officer for BAE Systems, Maritime and Land Division. When asked about his role at BAE, Clifford said “I’m excited by information. I want to help those in search of information to use it and solve problems to make their life better.”
Who are BAE Systems?
“We’re one of the largest defense contractors in the world. We employ upwards to 90,000 people in 40 countries, so really dispersed geographical base. The mission statement is to work closely with local partners, to support economic development, for transferring knowledge skills in technology. We’re a big company. We cover a lot of ground, and our defense solutions protect people in national security, critical information infrastructure, and we have a diverse portfolio of customers, so there’s never a quiet moment. We’re always looking to deliver that competitive edge across air, maritime, land and cyber. So, one of the big players, the biggest in Europe, and one of the largest in the world, in the defense space.” Clifford said.
The digital transformation journey
How do organizations and industry partners move away from their legacy methodologies into a more advanced digital engineering approach?
Clifford says, “It’s not a small challenge to have. In BAE, as an organization, we deliver solutions to complex problems. As a global manufacturer, we have to embrace advances in technology and innovation is our sort of life’s blood. It’s what we do for our customers, and it’s integral to our business. What we do matters. The people we deliver for, those are the people who are keeping us safe. So there’s no second-best here. There’s no second attempt. We’ve got to get it right the first time, and we’ve got to do it at speed.”
“The geopolitical landscape is changing and changing at pace. We need to adapt to that, and the whole enterprise has a role to play in that. So when we talk about technology and we talk about data, what we’re trying to do is orchestrate those capabilities in front of us to deliver maximum effect, to make that difference. You need to be looking for that edge, that innovation that will de-risk the delivery of that improved capability, and also give a much better, I suppose, product and service to the end user.”
Digital twins improving efficiency and reducing risk
“A digital twin is effectively a data created or virtualized entity of a physical object. It’s that sort of virtualized view of a physical product. Now, a digital twin can be of a thing. It can be an asset, a system. It could be a process even. The point being that there is a physical analog of it, and the digital twin is using the information we have to recreate that.”
So why would you create a digital twin, and to what complexity?
“Well, there are so many reasons why you’d do this. You might create them to test data or hypotheses which are very expensive or risky to test, again and again, or to actually test out many scenarios in parallel. When we talk about that speed and efficiency, we can’t afford to keep doing tests or research in sequence; we need to do it at the same time.”
Clifford added, “Digital twins ultimately, depending on how they’re used and depending on how information is gleaned from them, they can solve a range of problems. They can improve efficiency, they can de-risk outcomes. They can actually allow you, if you’ve got good enough data quality— you can start to predict outcomes and then you can start to change your entire system to reflect the outcomes you want to see. The digital twin, it’s that virtual view of a physical asset created with data, hopefully derived from the physical asset.”
Finding better outcomes
“If we’re going to talk about digital twins and talk about technology, we also need to keep in mind that sort of wider ecosystem of capabilities. The digital twins, they’re great by themselves, but they also work in concert with these DevOps as an approach, the cloud, improved sharing of information.”
Clifford continued, “When you start to orchestrate all of these things together, yes, you can see efficiencies. You can move away from that risk of getting it wrong once, and having to rebuild, but actually what you can start to do, if you connect your people together with that twin, with that information, you can share learning as you go along.”
“The ability to do something in one part of the forest, to learn from it, at speed, and then share that insight, that virtual insight somewhere else, using the cloud, or using another means, that’s absolutely critical. That improves efficiency. It de-risks. And now, risk is a great word, because you can apply it either way. It can remove a problem, or it can remove the risk of not being able to go as fast as you want. So, these capabilities, when orchestrated together, can start to join up different teams and organizations, and receive real – I suppose real mood change and a change in the paradigm across the defense community.”
Moving toward digital engineering
Clifford shared a recent example:
“It’s not necessarily in the manufacturing space, this is actually in the training space for armed forces. So, in the UK, recently, it’s been announced that BAE, working with partners QinetiQ and Inzpire, are going to be doing work for the Royal Navy to develop a synthetic training environment. This means using advanced sensors to link together to create a digital twin, which can be connected to BAE’s combat system, So, BAE provides the combat system to the Royal Navy, so the idea being that the sensors which are deployed connected to that combat system’s digital twin can start to replicate a synthetic environment for training, and the idea being that the carrier task group, which involves the Queen Elizabeth carrier, can work together to simulate threat environments.”
Clifford added, “And combined with technologies like HoloLens, and AR and VR, what we’re starting to see is that sort of multidomain view, different environmental inputs, which, you know, this is getting the best out of all these organizations. And at the heart of it is data. It’s data, it’s understanding, it’s knowledge, different technologies, different approaches coming together to deliver for that customer, who ultimately deliver for us, in terms of protecting the UK and the wider democratic world.”
Why defense organizations are choosing cloud
“I mean, the data proliferation issue is a real one. I suppose as a data professional, I would say, you know, it’s the insight that matters, not the data. But how do you get to the insight? You get to the insight by crunching the data, by analyzing it. So, whilst the goal isn’t to get more and more data, the reality is we need those inputs. We need that variety of data sources to give us the insights that will give us that effective edge.”
Clifford continued, “We are past the point where I think most organizations can manage the volume of data, the volume of analysis that’s required at the speed of relevancy in their own estate. I think, you know, companies, organizations like Microsoft and other hyperscalars have proven the utility of the cloud. It’s more secure, it has greater processing power. And when you start to adopt new DevSecOps as a discipline, you can start to see that real immediate translation of understanding and insight from the cloud to where it matters. And you can repeat that and you can scale it. So, it doesn’t surprise me at all, that cloud is a critical part of most planning and major organizations in the defense community.”
There can be questions around how to orchestrate that in a high assurance environment, but there are answers as well. And Clifford urged that it’s not an all or nothing situation.
“It’s not a zero-sum game. There are different places where you can start, and there are still huge benefits to be seen by even taking the sort of smallest step into that environment. I think, if you’re a modern defense organization, or you’re delivering to the defense community, we all know that data, IoT, the amalgamation of sensor information is going to be critical to the next gen of capability. So, we need to make sure we have the infrastructure, the culture, and the tools to make the most of them. All of the directions point towards cloud as being the enabler for that.”
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