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Analytics and Organization Culture

Published on 29 April 16
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As every organization that uses analytics for various purposes tells us it takes patience and perseverance to reach the answers to business questions that are asked. Sometimes the results prove a hypothesis to be true, and sometimes not, and sometimes there’s no conclusion for various reasons that require further work and investigation. It also requires creativity and asking questions of the data from multiple points of view.
Analytics and Organization Culture - Image 1

But all that happens mostly within the data sciences team. What about the rest of the organization? Is there a particular kind of culture that would be supportive of an analytics initiative, and improve its chances of success?

We live in a world in which technology has proven to be increasingly disruptive to the way business is done. We expect to see even more disruptive change in industries like banking (for example), thanks to the emergence of technologies like blockchain. When such impactful change takes place, what kinds of companies continue to survive and even thrive? Are they the ones that have a relatively open culture and are continuously adapting to change by challenging themselves and changing themselves all the time?

Companies like GE are synonymous with innovation and business excellence. In terms of practices that support the sustenance of business excellence, perhaps they are best known for their Six Sigma programs that set targets for improvement and allow people the freedom to think, ask questions and innovate in order to achieve them. Contrast this with companies that follow a rigid, command and control style of management, in which beliefs are not subject to challenge. If the commander(s) get it right, the organization gets an extension of life. If not, they perish. The very nature of analytics programs require the testing of commonly held knowledge for validity, and the openness of minds to new possibilities and discoveries. Of what useful impact could analytics be if it was only used to prove existing biases, or to affirm what has always been believed to be true?
Analytics and Organization Culture - Image 2

Businesses today operate in an environment in which everybody continuously receives information from various sources. News travels rapidly, and reaches and influences individuals no matter what kind of company environment they operate in. When everyone is aware of change in the external environment, how would it be possible for them to expect to achieve business success by not responding to those changes? And when responsive change has to be achieved quickly and innovation has to be continuous, the organizations that have proven to be successful have demonstrated that all minds in the company have to be involved and engaged, and not just a few at the very top.

It is in this sort of culture, one in which all hands on board are encouraged to think and challenge, that the questions of an analytics team can seem to be natural, and their results evaluated with deserved openness. After all, if everything is already known to the top, why use analytics at all in the first place?


As every organization that uses analytics for various purposes tells us it takes patience and perseverance to reach the answers to business questions that are asked. Sometimes the results prove a hypothesis to be true, and sometimes not, and sometimes there’s no conclusion for various reasons that require further work and investigation. It also requires creativity and asking questions of the data from multiple points of view.

Analytics and Organization Culture - Image 1

But all that happens mostly within the data sciences team. What about the rest of the organization? Is there a particular kind of culture that would be supportive of an analytics initiative, and improve its chances of success?

We live in a world in which technology has proven to be increasingly disruptive to the way business is done. We expect to see even more disruptive change in industries like banking (for example), thanks to the emergence of technologies like blockchain. When such impactful change takes place, what kinds of companies continue to survive and even thrive? Are they the ones that have a relatively open culture and are continuously adapting to change by challenging themselves and changing themselves all the time?

Companies like GE are synonymous with innovation and business excellence. In terms of practices that support the sustenance of business excellence, perhaps they are best known for their Six Sigma programs that set targets for improvement and allow people the freedom to think, ask questions and innovate in order to achieve them. Contrast this with companies that follow a rigid, command and control style of management, in which beliefs are not subject to challenge. If the commander(s) get it right, the organization gets an extension of life. If not, they perish. The very nature of analytics programs require the testing of commonly held knowledge for validity, and the openness of minds to new possibilities and discoveries. Of what useful impact could analytics be if it was only used to prove existing biases, or to affirm what has always been believed to be true?

Analytics and Organization Culture - Image 2

Businesses today operate in an environment in which everybody continuously receives information from various sources. News travels rapidly, and reaches and influences individuals no matter what kind of company environment they operate in. When everyone is aware of change in the external environment, how would it be possible for them to expect to achieve business success by not responding to those changes? And when responsive change has to be achieved quickly and innovation has to be continuous, the organizations that have proven to be successful have demonstrated that all minds in the company have to be involved and engaged, and not just a few at the very top.

It is in this sort of culture, one in which all hands on board are encouraged to think and challenge, that the questions of an analytics team can seem to be natural, and their results evaluated with deserved openness. After all, if everything is already known to the top, why use analytics at all in the first place?

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  1. 17 May 16
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