ポイント
- Gathering data isn’t enough. How information is interpreted (the "orient" in the OODA loop) is what separates success from failure.
- From reconnaissance missions to command centres, the flood of data isn't matched by systems that convert it into insight.
- Valuable data is routinely discarded post-mission due to lacking infrastructure and cost-benefit miscalculations.
- Victory in modern warfare depends not on data volume, but on speed-to-insight and the ability to act on reliable intelligence.
- Applying rigorous data methodologies can reclaim time and elevate human decision-making capabilities with AI support.
The nature of war is constant: the attempt to resolve a clash of political wills through violence. The character of war, by contrast, is usually seen as fluid — shaped by evolving technology, doctrine, and geography. Yet one aspect of war’s character is enduring: the focus on decision-making.
In the ‘fog of war’ or the ‘heat of battle’, commanders of all ranks must make better, more accurate decisions than their opponents. From Napoleon at Jena, to the Battle of Britain control rooms, to modern satellite imagery, people have always sought the ‘high ground’ for warfighting advantage.
Today, Western Defence organisations tend to gather enormous amounts of data, but sometimes forget that the purpose is to support decision-making. U.S. military strategist John Boyd described this decision-making process as the OODA loop: observe, orientate, decide, and act. The key, battle-winning step here is ‘orientate’. You can have all the data in the world but if you can’t make sense of it your decision is likely to be wrong.
The thirst for Defence data
Imagine a reconnaissance mission where an aircraft spends hours flying repeated passes over a point of interest, capturing detailed imagery from every angle. Later, it turns out that the requesting unit only needed to know if a vehicle could cross a bridge: a simple yes-or-no question that could have been answered with a glance from the cockpit as easily as gigabytes of data.
This unquenchable thirst for data, fed by live video from satellites, aircraft, drones, and more, has led to huge walls of screens dominating command centres. But do these drinking straw views of the battlefield actually drive strategic decision-making? There’s a fundamental misalignment between technology, doctrine, and training: vast data is often collected, but it’s seldom stored, catalogued, and exploited properly. In many cases, data is discarded after reconnaissance missions because it’s only seen as useful for real-time decision-making and the cost vs benefit of storage isn’t well understood.
With the ability to retain, retrieve, and reuse data on demand, leaders can richly enhance their orientation in the battlespace. Instead, countless terabytes of data are being lost to future commanders.
This kind of wasted data has been a challenge for decades, but it’s untenable now. The ability to harness data at scale is critical if Ministry of Defence initiatives like the Digital Targeting Web, proposed in the UK’s 2025 Strategic Defence Review, are to drive tangible strategic advantage.
We’re collecting exponentially more, but understanding proportionally less
A century ago, World War 1 commanders pored over a single image from an observation balloon with a magnifying glass. Today, decision-makers face a torrent of data, but lack an efficient means of turning it into useful, actionable insight. Our ability to gather data has surged, but our ability to turn it into battle-winning insights has stagnated.
As this gap widens, the value of data risks being lost, especially when we consider a strategic reality that remains unchanged: advantage isn’t conferred to those who collect the most information, but to those who understand it fastest. Accelerating the sensor-decider-effector process is crucial to success in today’s digitally enabled operating environment.
The pressure’s on and the work’s getting harder. We don’t just have more data, more sensors, and more assets. We have more kinds of data, more types of sensors, and a greater variety of assets on which to mount them — all more than enough to overwhelm any analyst.
The problem is well documented, and it has a well-defined solution: apply the models, methodologies, and mindset of rigorous data science to give analysts and commanders back what they need most — time. More time to think, more time to interpret, and more time to bring their intellect, imagination, and intuition to bear.
The good news is that, in terms of speed and sophistication, we’re making progress. Systems are getting smarter, human-machine teams are becoming better integrated, and the journey from data to decision is faster and more effective than ever.
Yet information inefficiencies and technological bottlenecks are stopping us from exploiting the full value of the data at our disposal, as well as the potential of underlying technologies that leverage it. As discussed previously, we’re failing to turn incremental performance gains into exponential productivity.
These inefficiencies pervade two distinct stages of the data-to-decision journey: data storage and cataloguing, and, later, analysis, exploitation, and dissemination of the resulting intelligence.
The disadvantage of poor data management
Despite the accelerating proliferation of autonomous and uncrewed systems, we still regularly send fast jets on intelligence, surveillance, and reconnaissance sorties. In the absence of lower-cost, lower-risk, more efficient ways of getting an eyeball or sensor over a target, such sorties are often the only way of closing the distance at the speed needed for decision makers under enormous time constraints.
The greatest inefficiency comes when we burn not just fuel, time, and money — but invaluable insight. We throw away too much of our collected data because we haven’t thought about how to store and harness it! When information is systematically captured and retained, it becomes possible to identify trends across multiple missions and diverse data types. By applying advanced data science to this accumulated knowledge, Western Defence organisations can extract insights that were previously unattainable, reshaping strategic decision-making. This capacity to anticipate and out-think adversaries not only offers a decisive operational advantage, but also acts as a potent deterrent to future conflict.
This is still a persistent, pervasive issue. Without a coherent data architecture — clear taxonomies, searchable archives, and assured provenance — we’ll continue to force commanders to rely on the next flight instead of the true ‘high ground’: the latest, most relevant, and most reliable data-led insights.
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