Militaries have long depended on information. Tactical, operational and strategic intelligence is vital to warfare. And there has long been a close relationship between defence and technology. Military innovations during the Second World War – from cracking the German Enigma codes to naval gunnery – drove the developments of the earliest computers.
Defence is undeniably complex. It uses a vast range of equipment and materiel (equipment and supplies of military forces), and the defence sector is a large employer. If anything, the post-Cold War defence landscape is more complex than ever, with the use of reservists, civilian contractors and industry to create what the UK Ministry of Defence (MoD) calls the “whole force” concept.
And defence – from the armed forces to the logistics, supply chains and manufacturing that supports it – is moving quickly to make better use of data. By doing so, defence ministries hope to make better use of budgets, speed up decision making, and increase the availability and readiness of their forces.
“Defence is rightly focussed on establishing intelligence systems that provide insights on threats and give advantage on the battlefield,” says Tim Smail, a digital expert at PA Consulting.
“This means harnessing massive volumes of data from different sources and processing it at speed using hyperscale cloud environments and artificial intelligence. There is enormous opportunity in the application of these skills in enabling functions. And one area in which the opportunity is being pursued is defence support.”
This support is the logistics, supply chain, manufacturing and even recruitment that allows defence to operate on a daily basis, in peacetime as well as during conflicts.
As defence equipment becomes ever more sophisticated, it needs much tighter integration between manufacturers and the armed forces themselves. This includes equipment maintenance and repair (MRO) and upgrades and improvements to equipment during its service life, as well as its ability to gather and share data on the battlefield.
Increasingly, data is the thread that connects all aspects of defence, from the soldier, sailor or aviator on the front line, to logistics, manufacturing, R&D, and recruitment. All new defence systems being developed for NATO and other Western militaries – and, as likely as not, those of rival states – are equipped with sensors and networking.
The MoD talks about “systems of systems”, with equipment working together by sharing data on the battlefield. And hardware such as the F-35, the upcoming Type 26 and Type 31 frigates and even more basic hardware such as armoured vehicles will all undergo “spiral development” during their lifetime, with upgrades added as new technologies emerge.
Many of these new capabilities will be electronic, including sensors, software and data links. In the future, artificial intelligence (AI) could be used to monitor the health of troops, control drones, or help commanders form a clearer tactical picture of events.
Better use of data also promises to improve the armed forces ability to deliver “operational effect”, though greater readiness and better availability of equipment.
“Attitudes to data have changed rapidly over the past 5-10 years and we are not starting at ground zero,” notes Paul Finley, a defence sector expert at PA Consulting.
“We’ve always used data to run supply chains in ERP systems. But what defence is now pursuing is the value of data as a strategic asset, and we find people are talking about it in these terms. Maybe 10 years ago they wouldn’t. The sector has always recognised the critical importance of mission data, from birth of radar to using real life information to conduct information [warfare].”
The challenge now, he says, is to carry that use of data beyond the the front line, into the day-to-day work of running the defence “business” and to industry.
Defence data strategies
The need to make better use of data is set out in defence policy. In 2021, the UK MoD issued the UK Data Strategy for Defence.
The document states: “Data is a critical component of Defence’s digital backbone, alongside people, process, technology and cyber and is fundamental to the Digital Foundry (including the Defence AI Centre) in driving Defence exploitation activity.”
The strategy also sets out the “data vision and transformative change required for Defence to leverage data as a strategic asset”.
This needs a change of thinking, as well as the use of new technologies. According to the MoD, only 25% of 100 defence systems have data that is “automatically discoverable”, and too much analysis is still being done in spreadsheets, or even with pen and paper.
But there is more to the UK strategy than automating outdated processes. Defence holds vast amounts of data, as do its suppliers. The aim is to make better use of those data sources, by using everything from off-the-shelf business intelligence and analytics tools to AI.
Future military equipment is likely to have even more data gathering capabilities. Already, defence equipment is being designed with this in mind – for example, by providing more electrical power. Future armoured vehicles will have batteries to run sensors when their engines are off.
As Mivy James, digital transformation director at defence supplier BAE Systems Digital Intelligence notes, even something as complex as a fighter aircraft could be designed almost as a minimum viable product. The base airframe, with the aeronautical and safety critical systems, would be fixed, but the digital capabilities upgraded.
“In terms of the airframe and the parts that make it airworthy, there are laws of physics that apply. So, we know we are not going to be messing around with them,” she says. “But there are other things, like the communications systems, or radar, where you can take a much more digital approach to development.”
This offers the potential of shorter development lead times for new equipment, as well as better long-term value through in-service upgrades. Increasingly, defence companies are using digital twin technology to develop and test hardware, as well as to plan upgrades.
And this technology extends to another area where defence aims to make better use of its data, through maintenance and repairs.
“You can use digital twins for the design, manufacturing and maintenance of equipment,” says James. “If you get that right from the beginning, you can explore how you manage change, and be much more iterative. You can do some really smart analytics in terms of maintenance and support.”
As in the civilian world, defence forces are moving away from fixed servicing and overhaul schedules to data-driven approaches to predictive maintenance.
And with better data, commanders will be able to choose whether, for example, to use an asset on an exercise or deployment for longer by delaying a refit, or parts that analytics identifies as a risk could be replaced before the patrol starts.
Defence suppliers are also investing more in digital capabilities and data analysis, and are looking at how this can be used to support their customers’ fleets.
“They [defence firms] are starting to become more savvy, in terms of how their data can be used,” says Joyce Klein, applied intelligence lead for aerospace and defence at consulting firm Accenture. “The emergence of generative AI has served as a bit of a reawakening in terms of the power of data. But the data needs to be good, and the data needs to be governed.
“You have that opportunity of trying to understand how to use this data and information to increase the uptime of the product, or to improve the repair protocols associated with it. The extension of this information into MRO is another critical area.”
But achieving this, within the specific requirements of the defence sector, presents its own challenges.
Challenges to data in defence
The greatest barrier to making more use of data in defence will always be security. But the sector faces other challenges, including complex business processes, legacy systems and skills. In this respect, defence is not that different to other critical industries.
But the sector also needs to improve the way information flows from manufacturers to users and back again. This means tackling data that has been segregated, often for historical reasons, but also dealing with hardware that was not designed for the digital age.
Both manufacturers and armed forces are taking steps to do this, not least by making more use of off the shelf information technology, including open source and the cloud.
“Just because you have segmented data in a certain way doesn’t mean you can’t draw across different segments to answer questions,” says Paul Finley, at PA Consulting. “There are some significant further opportunities there. As newer assets go into service, there will be more telemetry on them. What are the big data patterns across the fleet? What are the operating conditions that can be automated through AI and ML, and how can an AI engine learn what gets assets in a serviceable state to the front line?”
The potential for data is recognised in the UK’s Defence command paper, which talks about the need to build systems that work together “to leverage the value of data”, Finley says.
“With older kit, it is much harder to extract data and it is invasive to fit telemetry,” he adds. “Newer kit will continually deliver new opportunities. For example in maritime, the Type 26 [frigate] will have three times as many data points as the Royal Navy’s aircraft carriers, but on a much smaller platform…When building these assets, they are architected to have more communications across systems of systems, and to supply larger and larger amounts of data to exploit.”
Data sharing, though, raises security issues. Defence organisations need to protect systems against cyber attacks by hostile states, and manufacturers need to protect their intellectual property.
Nor is sharing data with customers simple: a manufacturer can sell hardware to several NATO members, members of alliances such as AUKUS, and to friendly but non-aligned nations. All parties need to be sure that data generated by equipment for operations does not give away tactical or strategic intelligence.
“We want to want to be able to share data whilst also maintaining security, so you don’t just have this big data soup, where everybody can see everyone else’s data and noodle around as much as they see fit,” says BAE’s James. “That has all sorts of challenges around protecting intellectual property and there might be commercially sensitive information in there.”
This also applies to sub-contractors and the wider supply chain: a supplier might sell to other prime contractors or OEMs, and not want each customer to see those details. The number of suppliers involved in defence projects is significant, from large multinationals to small, precision engineering firms that might not be familiar with digital ways of working.
“It’s being open and closed at the same time, and it is a bit of a paradox to to manage there,” adds James.
A further aspect is tactical security. Building in instrumentation and telemetry is all well and good, but as James notes, military equipment, unlike civilian vehicles, needs to control its radio frequency (RF) signature and operate in “silent mode”. This means a good understanding of when data collection is appropriate and when it is not.
As a result, improving the use of data also requires both militaries, and their suppliers, to have both the right data skills and deep knowledge of the defence environment.
The UK’s Data Strategy for Defence identified a skills gap. But addressing skills shortages is easier for defence suppliers, who can recruit from the open market, than it is for the forces themselves who need to develop data specialists on their existing enlisted personnel and officers.
“The data scientist isn’t the one with the business knowledge or the understanding of how the product might actually be best used over time,” says Accenture’s Klein.
This is why data connections between the defence industry and its customers are so important. Given the constraints around military recruitment and training, not just in the UK, it could be an opportunity for industry to supply more digital services alongside hardware. This could lead to manufacturers investing more to recruit and train data specialists.
Accenture’s Klein talks about creating a digital feedback loop that between forces to manufacturers and back. “That feedback loop is so powerful,” she says. “It gives information from the actual consumer of the of the capability or equipment back to the OEM. It’s really up to the OEMs to continue that flow of information and use that data and information to enhance products.”
Ultimately, defence customers and manufacturers alike hope that their equipment will never have to be used in anger. But using data to ensure better readiness, availability and more potent capabilities offers a deterrence value of its own.
