If you’re an intelligence lead procuring new software, your agency may be struggling to find enough experienced analysts to handle mission requirements. Additionally, some of your analysts are likely to turn over their seats in less than a year. Which intelligence tools will minimize training time and make your analysts most efficient?
Accelerate insights amidst growing data volumes
This question is becoming more relevant for intelligence teams grappling with growing data volumes—much of which are now open-source. The goal of intelligence is to support accurate, timely decision-making when it comes to policy, security, and situational awareness. While intelligence tools themselves aren’t solutions to these challenges, they influence how quickly analysts arrive at relevant insights.
Intelligence tools include software that helps analysts collect, process, and analyze data. The US Defense Intelligence Agency states that about 80% of agency intelligence reports are based on unclassified open sources. This means that the modern intelligence toolkit relies heavily on open-source intelligence (OSINT) tools designed to gather public information, largely from online data sources.
There are a variety of commercial OSINT and intelligence tools available on the market, but not every solution will expedite mission-driven intelligence analysts. Why is analyst efficiency lacking in today’s information environment, and which intelligence tools address this gap?
“Closing the gap between decisions and data collection is a top priority for the Intelligence Community (IC). The pace at which data are generated and collected is increasing exponentially—and the IC workforce available to analyze and interpret this all-source, cross-domain data is not.”US Office of the director of national intelligence
The data abundance challenge
Intelligence analysts have access to an abundance of information but lack the staff, time, and resources available to process and analyze it. According to the US National Intelligence Strategy (2019), data abundance provides significant opportunities but challenges intelligence teams’ ability to provide relevant and useful insight quickly enough.
Data science skills shortages are also impacting the development of more advanced applications like AI, which can help address efficiency issues.
Intelligence software usability is also a concern, especially in environments with high analyst turnover. Adopting a new intelligence tool takes a significant amount of resources, including training, integrations, and maintenance—not to mention the time it takes away from the rest of the toolkit.
Unique intelligence requirements
Procuring complex tools is more likely to extend analyst training and reduce consistent engagement. According to a 2017 survey on intelligence tools, analysts tend to recommend an analytic tool based on its usability over its usefulness. This means that even the most powerful intelligence tools may slow analysts down or be avoided entirely if they’re not user-friendly.
Government environments also have unique requirements that aren’t always considered in commercial software usability. According to 2020 research, military tech usability is typically assessed with factors relevant to commercial solutions like e-commerce platforms or web portals.
These are often based on evaluation methods like Nielsen’s usability heuristics, not factors unique to intelligence infrastructure. Agencies must consider usability not just for average people, but for intelligence analysts—especially when procuring solutions from commercial companies.
Intelligence tools for analyst efficiency
Intelligence organizations must procure tools that promote consistent user adoption and efficiency. What does this look like in a piece of software? Here are some features to prioritize during the procurement process.
“If intelligence is about providing timely, relevant, and accurate insight into foreign actors to provide U.S. leaders an advantage in formulating policy, then many new technologies hold the potential to unlock deeper and wider data-driven insights and deliver them at greater speed, scale, and specificity for consumers.”CSIS: The Intelligence edge
Artificial intelligence and machine learning
An analyst’s subject matter expertise and experience are irreplaceable when it comes to the intelligence cycle. But because of data overload, AI techniques like natural language processing are becoming necessary to offload straightforward but time-consuming intelligence tasks in data analysis, processing, and collection—something CSIS calls strategic bandwidth.
For example, intelligence tools powered with machine learning models can help filter relevant data, provide additional context, visualize patterns, and generate written summaries.
According to CSIS, AI can also help analysts efficiently generate more accurate and verified intelligence: “Machine knowledge and judgment of past analytic lines, source quality, and competing hypotheses can add rigor to the process, helping analysts confront bias, avoid groupthink, think critically, and be transparent about their levels of confidence.”
Real-time or near real-time insights
Generating intelligence efficiently isn’t just up to the analyst. Intelligence tools also need to collect and display data in real-time or as close to real-time as possible to ensure timely delivery. For example, many OSINT tools ingest public social media data, but not all tools provide real-time access. While one tool may render a post within a few seconds of it showing up online, others may take several hours.
In the intelligence cycle, this could make a big difference for policymakers. Intelligence professionals can avoid this lag by verifying latency times with technology vendors, prioritizing products with real-time or near real-time data.
The value of an intuitive user interface
We know that analysts are more likely to engage with an intelligence tool and have a shorter learning curve if it’s easy to use. Many commercial intelligence products are extremely powerful at data visualization, collection, processing, and analysis—but may take months for a user to apply its full potential. This is not ideal in an agency where analysts may be reassigned within a matter of months.
While usability factors may vary for different intelligence disciplines, intelligence tools generally should:
- Have a simple user interface with consistent design elements
- Be built around an intuitive workflow
- Avoid click-heavy processes
- Render information in a simple format
- Only display relevant information, reducing noise and false positives
- Provide simple training and support resources, including features like tooltips
In an information environment overloaded with data, modern intelligence analysts are only as efficient as their tools. To support analyst efficiency, team leads and other procurement decision-makers must ensure that intelligence tools are easy to use, provide real-time data access, and leverage AI to alleviate time-consuming tasks.
Prioritizing these features reduces training resources, ensures higher rates of adoption and usage amongst analysts, and ultimately drives a more timely intelligence cycle.