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Analyst's Depot: Quality of Information Check

If there is one scenario we seek to avoid in the intelligence production process, it is being forced to rely on single-source intelligence.
For this reason, for every single intelligence report and information requirement, we task multiple assets simultaneously to collect on the same target. The purpose of this is to be able to see the different types of information collected on the same topic via multiple assets, identify contradictions, and make a clearer assessment of the information's veracity.
However, at this point, the analyst faces the challenge of correctly filtering this information—which has been collected on the same topic, possesses varying degrees of source reliability and information accuracy, and is, at times, contradictory. This creates the problem of deciding which information to use in the analysis and how to arrive at a sound conclusion.
This is precisely where the "Quality of Information Check", mentioned in the title, comes in. It is an analytic technique developed specifically to solve this exact problem.
The Quality of Information Check is a structured method used to evaluate the validity and reliability of the information upon which analysts rely. By critically examining the sources and content of information, it ensures that conclusions are based on accurate, reliable, and relevant data. The technique is extremely valuable because it prevents misinformation, increases accuracy and reliability, and reduces the risk of flawed assessments.
The application of the technique consists of seven sequential steps.
Step 1: Identify Information Sources
In this step, all pieces of information related to the subject at hand are listed, and the source of each piece of information is clearly identified. Our objective is to understand where the information comes from and the nature of the reporting sources.
Step 2: Evaluate Source Reliability
Here, every source listed in Step 1 is analytically evaluated and assigned a reliability rating. Our objective is to determine how trustworthy each source is based on its past performance and dependability.
Step 3: Evaluate Information Accuracy
In this step, we cross-reference the information provided by each source against other known facts, our historical data, and alternative sources. We check for any logical inconsistencies. Our objective is to determine whether the information itself is credible and its level of consistency with other evidence.
Step 4: Test for Relevance
In this step, we examine how clearly the information answers the current intelligence question or supports a specific analysis. Our objective is to eliminate data that does not contribute to our main goal—meaning it cannot answer the intelligence question or carries the potential to distract our focus.
Step 5: Review Currency
In this step, we check when the information was collected and whether the situation it describes is still valid. Our objective here is to prioritize current and actionable information and to flag outdated information.
Step 6: Conduct Contextual Analysis
Here, we consider the environment and circumstances under which the information was collected to identify the quality of the context and any potential interests or biases of the source.
Step 7: Assign Overall Confidence Level
Finally, we assign an overall confidence level to each piece of information based on its source reliability, information accuracy, relevance, currency, and context. Our objective is to summarize the quality of the information while deciding how much weight to give it during the analysis process.
There are three important points you must pay attention to as an analyst when using this technique:
  • Confirmation Bias: Analysts may give more weight to information that confirms their existing beliefs, leading to a distorted analysis. It is crucial to question initial assumptions.
  • Over-reliance on a Single Source: Single-source information is risky and must be corroborated whenever possible.
  • Over-reliance on Outdated Information: Information that is no longer current can mislead analysts, which is why it is essential to check the currency of all data.

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