Mastering information fusion: learning from spies

Mastering information fusion: learning from spies


Reading time: 4 mins

We have seen the future of insights. It is
information source agnostic and it seamlessly weaves together disparate data
into a story that answers two key questions: So what? What’s next?

Insights professionals of the future will
be information omnivores. But it will be the quality of analysis —not the
quantity of data — that will make the difference. 

How do we know that? We need only look to
the example of the intelligence community. Their analysts are continuously
engaged in rapid, high stakes analysis and reporting. They have been
incorporating behavioural economic techniques in their analysis for the past 50
years. And they have long been dealing with multiple data sources and rapid
technological change. Their today is our future.

“In the beginning we had almost a monopoly on insights,” Antony R. Barton, Director of Product Innovation and Marketing Insights at Intel told me in an interview for my book The Insights Revolution: Questioning Everything, “and that put us in a very special position, because nobody else had access to data. We had to do this survey, or we had to do this discrete choice, or this set of focus groups, because nobody else could get the data. And then, all of a sudden, there is this explosion of data. There are lots of ways to get at insights. I think the industry has struggled with that.” This change is happening to insights now, but in the world of intelligence, it happened many years ago.  

Dealing with diverse sources

A former CIA-analyst and current professor
of intelligence analysis (who must remain anonymous) I recently interviewed for
my new book, explained: “In the early 1980s, the job of a US government
intelligence analyst was to deal with the secret stuff: the satellite imagery;
the intercepted telephone conversations; reports from the spies and all that
kind of stuff.”

“In the 20-some years that I was in the
business,” he continued, “it was very much transformed by how much really good
material is out there now, unclassified and open world. And Google Earth is
just one example of this. So, the intelligence analyst…their job has really
changed. They have to be aware of all that stuff that’s out there in the
outside world. They can’t come to the table with just the secret stuff, because
there is so much valuable information out there.”

Intelligence analysts deal with an
astonishingly diverse array of information sources and distil them down into
insights to guide decision-makers. They include what the intelligence community
call SIGINT—which is primarily signal interception, IMINT—image intelligence,
which includes photos, radar sensors and electo-optics, MASINT—other signal
sources that can be used to track targets, and GEOINT—which is the analysis and
visual representation of security-related activities on the earth. They also
use other sources that are more familiar: OSINT—open-source information that is
publicly available, and HUMINT—human intelligence and espionage.

Each of these areas has people with
specialised technical skills. But the bulk of the insights are generated by “all-source
analysts” who must synthesise all these streams of data quickly and accurately,
as mistakes are deadly. What kind of people are these?

The CIA analyst job description sums it up
nicely: “Collaborative. Problem-solvers. Critical thinkers. These are the
qualities needed for CIA analytic positions. The ability to study and evaluate
sometimes inconsistent and incomplete information and provide unique insights
that help inform decisions is a key aspect of these positions.”

Note the focus on collaboration and
critical thinking. Those are two things we could use more of in the world of
insights. Too often, we work without much cross-team discussion of
implications, and we regularly run with the first interpretation that comes to
mind.

Thinking about thinking

The professor of intelligence analysis I
spoke to focuses on teaching how to think about analysis, more than how to
wrangle specific pieces of information. He does this because he knows the types
of information available will continue to change and evolve, but the task of
analysis will not.

The intelligence community has developed
numerous approaches to analysis they call ‘structured analytic techniques’
(SAT), which they use to help guide their thinking as they assess the evidence.
While each SAT is slightly different, common themes are generating and testing
multiple hypotheses, encouraging collaboration when generating hypotheses, critical
thinking and being aware of the effect of cognitive biases.

This consciousness of cognitive bias is long-standing.
“Intelligence analysts must understand themselves before they can understand
others,” wrote former CIA analyst Richards Heuer in the Psychology
of Intelligence Analysis
. Indeed, the intelligence community started
structuring their analytic techniques around behavioural economics in the late
1970s, as Kahneman and Tversky were just unveiling their work on heuristics and
biases.

Heuer believed, “Intelligence analysts
should be self-conscious about their reasoning process. They should think about
how they make judgments and reach conclusions, not just about the
judgements and conclusions themselves.” That’s a rigor the insights industry
can learn from.

A singular focus

So, while intelligence analysts have been dealing
with intense data fusion for a long time, we in the insights community should
note this emphasis on “thinking about thinking” and considering how to do
better analysis. The intelligence community have gotten past being seduced by
technology or overwhelmed by the volume of information. The focus is on how to
do thoughtful and accurate analysis.

As Sherman Kent, a Yale historian who
founded the analysis branch at the CIA, wrote prophetically in 1947 “Whatever
the complexities of the puzzles we strive to solve and whatever the
sophisticated techniques we may use to collect the pieces and store them, there
can never be a time when the thoughtful [wo]man can be supplanted as the
intelligence device supreme.”

As our industry is transformed by the opportunities afforded by new data sources, let’s learn from the intelligence community. Our focus should be on one unchanging thing: excellence in analysis.  



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