Critical Thinking in Intelligence Analysis Work
What is critical thinking?
Critical thinking is the analysis
of available facts, evidence, observations, and arguments to form a judgment. For
intelligence analysts, critical thinking is at the heart of intelligence analysis
and affects all stages of open source intelligence investigation work, from
investigation planning, information collection, and intelligence analysis to
decision-making and communication. In short, critical thinking is the ability to
deal with, study, and analyze a given situation clearly and rationally.
Critical thinking is the key for intelligence analysts to carry out open
source intelligence work.
When working on open source intelligence
investigations, analysts need to consider how to find all the data needed for
mission planning, which data sources and tools need to be considered and weighed
against each other.
In every question planned by the intelligence analyst,
it is necessary to consider whether it is objective, whether the requirement
segmentation is appropriate, and whether the data found can fully answer the
requirement.
In the actual investigation, the data found may include false
information, such as fake news and fake reports. Intelligence analysts need to
consider whether and why the data sources used are trustworthy.
Conducting
open source intelligence investigations requires critical thinking. By critically
thinking about how to collect raw data as much as possible, then process, analyze,
and refine the data to obtain intelligence. During this process, please pay
attention to:
1. Identify survey needs. It's best to communicate with
customers and define answerable questions. For example, if a customer wants all the
information about an institution, then it must be communicated to determine what
exactly "all information" includes.
2. To study a topic in detail. For
example, the need to understand customers and their areas of focus or competitors.
3. Identify requirements and segment them. The commonly used method can be
the 5W2H method: why, what, who, when, where, how, and how much.
4. Define
the data source.
5. Formulate keywords for each segmented requirement. There
may be only a few at first, and then you can continue to improve.
6.
Consider the tools needed for this requirement.
7. Browse for context with a
quick search. So as not to be overwhelmed by a lot of information or attracted by
some unimportant information when you really start to do it.
8. Consider
whether the initial findings met expectations. If not then please repeat the
workflow, which is the intelligence loop.
9. Gather the information you
need and exhaust all resources.
10. Refine and analyze the collected
information.
11. Evaluate the report, considering whether the report is
objective. You can ask colleagues who are not familiar with the topic to help. If
you find new problems or directions, you need to repeat the workflow.