Why great organizations need to insist on wisdom and not just intelligence.

There is clearly a difference between knowledge or intelligence and wisdom. The latter has a connotation of being more holistic and considering all of the facets of intelligence to take action. The former might be important components of making wise decisions, however, on their own, they could actually force one to draw conclusions that are not entirely accurate.

When you combine this reality with the culture we live in today, the results can get even worse. We live in a world that has an insatiable demand for quick answers and immediate data. We want to know now, not tomorrow, how our consumers are responding to the work we do. We also want the easy road, we don't want to work as hard as we might need to in order to get accuracy, we would rather have a few quick data points that we then convert into metrics and use as the basis to understand our consumers and make sound decisions.

These factors have fed the beast of analytics to the point where decision-makers and stakeholders are often held captive to something that appears to be unshakeable data. But hold on a minute, let's consider two examples of these benchmarks that have become so vital and influential in today's business models.

A/B Testing: This is used by companies everywhere and the belief is that it will help them determine what their customers want more of, prefer, and understand how they behave. But does it really do that? Are the results as extensive and as informative as they are sometimes treated. The experiment itself is a biased one because it begins by forcing a choice, A or B. But are A and B even the right alternatives for your hypothesis test? What are your pre-existing beliefs that may have influenced how you designed those choices? What would success look like? The reality is that any test you run should make us ask more questions, like why, rather than serving as an answer to everything.

Attribution: Everybody wants to validate the work they do through attribution studies, they all desire to demonstrate how point A led to financial gain at point B. However, the world we live in is not that simple, regardless of any data trail left behind on the web, cookies and pixels can only tell us part of the story. In fact, many newer rules mean that tracking this history is actually impossible. The big problem with this work is not that it exists, because it is still helpful, but that it has become the only story that executives want to hear and it forces long term strategic discussions down to a very crude analysis and as a result entire teams can become obsessed with satisfying the needs around "return on spending" rather than doing what may be right for the business or the customer. Often the data scientists, while busy bragging about some type of attribution metric, forget to recognize that they will always fall second place to the highest Return on Spend for any company, one that is almost impossible to track, that is the old fashioned word of mouth from satisfied or evangelical customers.

The danger with both of these tools is that they do have value, they should be utilized. If they did not then they would not threaten good decision-making and sound strategy. It is their easy-to-understand benefit that gets everyone over-excited and often obsessed. The problem is like many things when the value gets blown out of proportion and their returns exaggerated; before you know it we are giving more concern to these results than we are to other equally, if not more important metrics. That is the difference between wisdom and intelligence. Used correctly, intelligence can amplify wisdom, however, if things get out of balance then very quickly the formula is upside down.