The Data-Driven Transformation of Intelligence
- by 7wData
When “little green men” invaded Crimea in early 2014,they left a data trailthat went largely unnoticed by the U.S. Intelligence Community (IC). Distracted by a large Russianexerciseto the west, the ICdid not connect the digital dotsthat indicated the impending invasion. In the Information Age, the “dots” are more plentiful and glaring as everyone now leaves a data trail. Given that, how can Intelligence analysts better gather, share, organize, and view data to reveal intent, more accurately predict behavior, and make better decisions with limited resources?
Intelligence is, for the most part, production focused, meaning many analysts are often forced to make quick assessments from limited text-based sources to meet deadlines. As such, they can be trapped into making predictions that put too much weight on personal experience and cognitive biases. This is a big problem considering the difficulty of forecasting the behavior of every rival the U.S. faces in the global arena or on the battlefield. The best analysis derives from the right combination of art and science. It is dangerous to favor the former at the expense of the latter, even for the most experienced and skilled analysts.
If the U.S. government is to deal with deceptive and elusive adversaries, the IC must make data, structured in a way to tell a story, the foundation for its intelligence assessments. Data analytics are changing how we approach economics, elections, health, security, business, and our daily routines. It is time for intelligence to catch up. Analysts must pair their intuition and expertise with data science to give decision-makers the best possible intelligence.
In turn, IC and defense leaders must accelerate this data-driven transformation of intelligence tradecraft, and demand a more structured, scientific approach to the intelligence problems we face.
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