Contextual Intelligence (CQ): a definition
Big data offers unprecedented opportunities for discovery and insight. When used the right way big data can help us understand what happened, why it happened and what will happen tomorrow. It can help us foresee problems and potential through correlations and connections we weren’t aware of. It can rinse our eyes and overrule our cognitive biases.
As we enter a world of big data, we are being driven towards the numbers and extensive analysis. Numbers are supposedly uncontaminated by bias, judgement or opinion. Numbers are objective. Objectivity is scientific. Scientific equals robust.
But what about context?
Without context data is meaningless, irrelevant and even dangerous. Creating competitive edge with data requires a new type of intelligence: Contextual Intelligence (CQ). This is 21st Club’s DNA: applying context to data and delivering competitive edge.
The concepts of EQ and IQ are well established, but CQ is the new intelligence. We came up with the phrase to describe how 21st Club are humanising the big data movement by marrying empirical rigour with intuition; helping our clients make better informed decisions.
Contextual Intelligence (CQ)
By applying CQ, we resist the temptation to undertake retrospective analysis without first understanding the problem we’re trying to solve. This avoids both confirmation and hindsight bias; affirmation of the narrative we wanted to see. CQ encourages us to begin with the end in mind and seek first to ask the right questions before embarking on our journey of data exploration.
CQ is also about the long-term. It champions a performance-driven (strategic) approach, as opposed to being results-driven (reactive). Yes, we are all ultimately judged by results, but luck often plays its part – meaning that outcomes are often superficial. CQ forces us to delve deeper and focus on the underlying performance factors that lead to success.
At 21st Club, we are data-savvy, but not data-obsessed. We appreciate the value of both big data and small data. The most important thing is giving meaning to data. And meaning comes from applying Contextual Intelligence to the problem and delivering results.