The evolution of intelligence gathering has been remarkable since I began my career in 2002. The process was entirely manual back then, presenting significant challenges that are almost unimaginable today. Analysts were not only tasked with searching for information but also with the critical responsibility of identifying the most relevant and accurate data for their specific needs. This manual approach was time-consuming and often led to inefficiencies, especially when time was of the essence and a report or analysis needed to be produced quickly. Fast forward to 2024, and the landscape has drastically changed. There is now an abundance of platforms designed to isolate, collate, and even generate reports for analysts and their teams. Despite these advancements, many organizations are still not fully leveraging the potential of intelligence platforms to enhance their operations. This post will explore the shift from manual intelligence gathering to platform-driven processes and why some organizations are slow to adopt these powerful tools.
In the early 2000s, intelligence analysts faced a daunting task. While search engines were available, they were still in their infancy from 2002 to 2003.. Techniques like dorking or advanced search engine manipulation were not yet part of the analyst’s toolkit. This meant that analysts had to rely heavily on their analytical skills and deep understanding of the subject matter to find the right information. The process was straightforward for familiar topics, but when dealing with new or complex subjects, the challenges multiplied.
The Internet itself was less developed, with fewer resources available and a less user-friendly experience. Analysts often spent significant amounts of time sifting through irrelevant or misleading data, a process that was both mentally exhausting and inefficient. This method required a great deal of patience and meticulousness, as the consequences of missing critical information could be severe. However, this was the norm, and those who excelled in this environment were truly masters of their craft.
As the mid-2000s approached, significant changes began to take place. Search engines, led by Google, started to improve, offering better algorithms and more relevant search results. The Internet became easier to navigate, which, in turn, made data more accessible. This period marked the beginning of a shift from purely manual processes to a more technology-assisted approach. Intelligence Platforms began to emerge, offering tools that could help analysts manage the increasing volumes of data more efficiently.
The creation of these early intelligence platforms was both explosive and innovative, as they started to address some of the key challenges faced by analysts. These platforms provided a more structured way to collate and analyze data, reducing the time and effort required to find relevant information. However, these tools were still in their developmental stages, and while they represented a significant step forward, they were not yet the fully automated, feature-rich platforms we see today.
Between 2005 and 2014, the intelligence community witnessed an era of rapid innovation. New tools were developed that significantly improved the ingestion, processing, and analysis of intelligence data. Notable platforms started to emerge during this time, and that represented a paradigm shift in how intelligence information was managed.
These tools allowed analysts to ingest, process, and analyze large volumes of data with far greater efficiency than ever before. Initially, many of these tools were designed for non-public information, but it quickly became evident that their capabilities were equally applicable to Publicly Available Information (PAI) and Open Source Information (OSINT), which were becoming increasingly important in intelligence operations. This marked a clear departure from the labor-intensive methods of the past.
Today, the intelligence community has access to a wide array of commercially available Intelligence Platforms. Each platform offers a unique set of capabilities, allowing organizations to choose the tools that best meet their needs.
Modern intelligence platforms can ingest data from various sources, including OSINT, internal logs, and proprietary databases. This ability to integrate multiple data streams enables organizations to identify potential threats more effectively and respond more rapidly to emerging risks. Additionally, many platforms offer advanced analytics and reporting tools that significantly reduce the amount of manual effort required from analysts. There are also platforms that need what many call care and feeding, as they are not automated in any way. This can lead to its own issues as the care and feeding of the platform takes a team member away from doing analysis to focus on the health of the platform.
After exploring the advancements in industry innovation, one might question why organizations are not universally adopting Intelligence Platforms. A primary concern is budget constraints. While these platforms are increasingly accessible, their costs can still be prohibitive for some organizations. Fortunately, a range of vendors offer scalable solutions, enabling even smaller organizations to invest in Intelligence Platforms that align with their financial capabilities.
Another consideration is the potential strain on security teams. Platforms requiring extensive maintenance and operational oversight can overwhelm existing resources, potentially detracting from day-to-day security management. Additionally, many organizations only allocate funds for security measures post-incident, adhering to the outdated mindset of "if it isn’t broken, don’t fix it." This reactive approach is increasingly inadequate in today's dynamic threat environment. Although a rudimentary, internally developed Intelligence system might have sufficed years ago, it is no longer sufficient for comprehensive Intelligence Analysis in the face of evolving threats.
Overall, several different options are available based on the size of the organization, its budget, and the sophistication of the team itself.