A different take on business intelligence

3 min read

Data is useless if it doesn’t shed light. The more light it sheds on the most acute problems businesses face, the better.

Within this context, data synergy–data from multiple sources and disciplines that is more valuable than the sum of its parts–is often underappreciated. With data synergy, the light can be in many more places, and can illuminate dark, unexplored nooks and crannies, providing previously undiscovered insights. Those insights constitute intelligence.

The intelligence community, when it has succeeded, has done so with the help of data synergy. How the US handled the Cuban Missile Crisis was an example of that synergy, with signals intelligence and imagery intelligence both playing a role. Signals intelligence provided an initial heads up regarding heightened activity in and around Cuba. Then focused imagery intelligence supplied details concerning Soviet missiles under construction there.

When the intelligence community has failed, the reasons have been because of a lack of data synergy and disconnectedness. An investigation after the September 11, 2001 (9/11) suicide terrorist attacks revealed, for example, that intelligence and criminal investigation data that could have been combined for early warning was instead kept separate, which implied that the only means of getting info from one system to another involved human intervention.

Because data has become so much more valuable, some private sector businesses are starting to resemble intelligence agencies. Let’s explore some of the distinctive features of intelligence and its capacity for data synergy and thoughtful exploration, by contrast with the narrow focus of business intelligence.

This past February 12th, we celebrated the 20th anniversary of a famous observation made three months after the 9/11 attack:

Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns—the ones we don’t know we don’t know. And if one looks throughout the history of our country and other free countries, it is the latter category that tends to be the difficult ones.

–Donald Rumsfeld at a Pentagon briefing, February 12, 2002. The “known knowns” matrix Rumsfeld described has been popular ever since. In 2005, science historian Michael Shermer even wrote a Scientific American column about the scientists who’ve been influenced by this matrix. If you don’t ask good questions, obtain facts to help you answer those questions and understand what you don’t know and why you can’t make good decisions.

Just using the known knowns matrix, of course, won’t guarantee good decisions.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.