The difficulty with many intelligence problems is knowing where to start. This applies equally to strategic and tactical problems – tactical problems are sometimes the more difficult of the two due to the apparent lack of specific information on the area, group, or issue. Localisation is where you should start.
Localisation not only provides a starting point to get you moving forward, it will ultimately provide a more actionable level of detail for decision makers in the final intelligence product.
So what is localisation?
In simplest terms, localisation is the process of identifying a narrower object to analyse. Using illegal fishing as an example, instead of looking at the whole Pacific Ocean, the issue could be narrowed down to illegal fishing in one piece of the ocean, such as a country’s EEZ (or one part of an EEZ), or to a particular fleet of vessels. Another example is analysing insurgency in one specific geographic area, rather than writing off a whole region or country with a generic threat level. Even an OSINT investigation into a specific individual can be localised into smaller segments such as social or professional activity, times of day, or relationships to certain topics.
When applying localisation, an object can be a geographic area, a group, a person, an issue, or even a time period. It is less important at the outset which object is used to localise the analysis, the point is by doing this first, it rules what is in and what is out. This allows for easier triage of information, making database searches easier if there is a lot of reporting, and providing local context if there is not. Overall it narrows down the problem to an achievable task.
Localisation is useful for both analytical and collection problems. To an extent, localisation is probably more familiar to collection disciplines. Collection naturally requires translating a task into practical objectives to implement on the ground – which source will provide the best information. This value is demonstrated well by Stanimir Dobrev, one of the few analysts who predicted the Russian Armed Forces would struggle during an act of aggression (as early as 2018 no less). During an interview with Bernhard Kast of the Military History Not Visualized YouTube channel following the invasion of Ukraine, he explains that his analysis was based on local and social media sources from around key military bases and units, in contrast to the traditional analytical institutions who largely relied on national level reporting, such as state media, and that mostly translated into English.
With this process, you will initially miss some of the picture. But you will get 80% of it, and from this strong position, you can identify which specific areas you need to look at next, if you need to at all. The reason you apply localisation in the first place is to avoid chasing more information down a rabbit hole.
In addition to finding a start point, the end benefit of localisation is that it provides a more actionable intelligence product for decision makers. The assessment is grounded in an entity that is relevant to the problem facing a decision maker. Ideally, the localisation coincides with the reach or level of authority of the organisation being supported – such as organised criminal activity within a certain district, or smaller area. This allows the intelligence product to lead directly to application of resources in that area, group, or time period. The practical link from intelligence to action is explained incredibly well by former NYPD Deputy Commissioner, Jack Maple, in his book The Crime Fighter (Maple and Mitchell, 2000). Maple was part of the NYPD senior leadership team turned turned crime around in New York City during the mid-1990s with intelligence-led policing.
Localisation is a proven method to begin analysis of complex intelligence problems. It can be applied across all different contexts, from the strategic to tactical level, and in both analysis and collection. By design, the process leads to actionable detail in the final product. If you don’t know where to start, start here.
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