The exponential opportunity: Tactical and strategic data exploitation

The theory is simple enough: define the challenge, collect the relevant data, organise it appropriately, and then analyse it effectively. This is how, slowly but surely, more and more previously intractable problems have been solved in the information age.

It’s also why Western Defence organisations risk incremental irrelevance and, should it come to it, defeat. Geopolitical volatility is rising fast, and the strategic security context is changing just as quickly. The cyclical approach to data exploitation and innovation is too slow in comparison. In the age of exponential technologies, linear progress is no longer acceptable if Western militaries are to maintain a competitive edge.

A central challenge for defence organisations is how to become as adept at discovering opportunities as they are at solving problems. This will require three things:

• A fresh understanding of why (and how) we collect, organise, and exploit data
• New partnerships with data experts who can collaborate on swift, low-cost experimentation
• A new way of valuing data, both as a capability in its own right, and also as a strategic resource – a resource with vast potential that is still unrecognised by many key decision makers

Putting this theory into practice isn’t, at least from a technological angle, as tough as one might think. In fact, it’s already happening in industries ranging from finance and capital markets to manufacturing and bioengineering. Those at the forefront of these industries are using data to help them ask the right questions, not just to answer them.

The problem with ‘problems’: a crude analogy

In the mid-to-late 19th Century, crude oil was refined primarily to produce kerosene. The other 90% of the oil’s potential – the gas, petrol, diesel, fuel oil, and countless derivatives – was discarded. A vast resource was being squandered because the focus was solely on solving the immediate, well-defined problem: finding a cheaper, more plentiful alternative to whale oil in order to provide light.

Across Government and MOD, something very similar has been happening with regards to data. Specific, well-defined problems are being solved. Data is, albeit often too slowly, being used in real-time, and performance is improving in a linear fashion. But we’re failing to see – let alone grasp – the vast opportunities that promise exponential progress.

During my time leading the RAF’s Rapid Capabilities Office, we were fully aware of the value of specific data in the context of specific use cases; that, after all, was why we collected the data in the first place. But the value we saw on the surface – the ‘solutions’ to the ‘problems’ – all too often blinded us to the deeper, wider, longer-term value of that data, much of which we were yet to realise.

As with so many teams across MOD, the urgency of our mission also meant we didn’t always have the time (or the budget) to drive genuine and potentially war-winning exploration and innovation.

This is where industry experts and academics can step up and in. Or rather, this is where they need to be invited in. This is where they excel, and where they can help UK MOD and its NATO allies to experiment – to combine and recombine data sets and data types, to apply different configurations of methodologies and technologies to address old problems and also uncover new, unidentified opportunities.

Unify the data, complete the picture, empower the decision maker

From a practical standpoint, one major challenge for MOD stems from the fact that defined problems lead to defined requirements and, of course, defined budgets.

For these reasons alone, it’s entirely understandable that our Armed Forces collect only the data they need to address known, well-defined problems. Not only are they responsible (and answerable) for spending the ‘King’s shilling’; Defence personnel may already feel overwhelmed by a data deluge. Nevertheless, they need, with the help of outside partners, to collect more data, and they need to be able to store, sequence, and normalise it so they can draw on it in the future, identifying and exploiting its full potential as threats change and operational demands evolve.

Diversity of data, however, is as important as volume.

Discrete data sets and streams can help solve known problems, from C5/ISR to sustainment and logistics. However, it’s only when diverse data sets and streams are brought together that we can unearth entirely new opportunities.

Multi-source event correlation, for example, can help us do so much more than simply understand an adversary’s disposition to see what, in Wellington’s words, ‘is on the other side of the hill’. By fusing structured and unstructured data for a wide range of sources, it’s possible to see what’s beyond the temporal horizon – to anticipate an adversary’s immediate actions, to foresee their near-term intentions, and even reverse-engineer their long-term strategic ambitions.

We need boldness (as well as budget) to back hunches

It’s easy to imagine those 19th-century innovators pouring the potential of oil derivatives literally down the drain because they were so focused on solving narrow problems that they overlooked a far wider range of opportunities. Even as more and more uses were found for these derivatives, from material science to medicine to the development of the internal combustion engine, it took decades before nations came to value oil as a strategic resource.

Defence, with the support of industry and academia, needs to learn from this and move faster. Technologists and data scientists can and must help MOD use its data more efficiently and effectively. They must help Defence users to do what they already do better, faster and more efficiently, and to do things they’ve never even thought of doing before.

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