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Why data-driven marketers shouldn't trust the data fully - Chief Marketing Technologist | #TheMarketingAutomationAlert

Why data-driven marketers shouldn't trust the data fully - Chief Marketing Technologist | #TheMarketingAutomationAlert | The MarTech Digest | Scoop.it

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But the choice of labels on that graph — admittedly, taken out of context — triggered an important tangent that I think is worth discussing. It’s good to be confident in embracing data-driven management, but great data-driven managers should always be skeptical of the data.

 

In some ways, this is Clay Christensen’s classic innovator’s dilemma: what worked in the past holds us back from what needs to change in the future. Data from the previous strategic context can further calcify that prior worldview. To break out of the dilemma, you need to consider different data. It’s not a question about whether the data is right, but whether it’s the right data.

 

You can have confidence in using data while not fully trusting the data. It’s not that you doubt its accuracy. But you’re skeptical of data’s context, relevance, and completeness in the conclusions that are being drawn from it.

 

“Fact-based decision-making” is a term that’s growing in popularity. And while I laud the intent behind it — data over opinions — I remain cautious that “facts” are a slippery thing, especially when you go from the what to the why. Opinions can be all too easily disguised with data to look like facts.

 

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Marteq's insight:

Scott Brinker often writes about hypothesis testing and the scientific method. And this is an adjunct of that thinking: challenge the data through testing, testing, testing. And if you test it multiple ways, you may find that your conclusion is correct.

Marteq's curator insight, May 19, 2014 7:02 AM

Scott Brinker often writes about hypothesis testing and the scientific method. And this is an adjunct of that thinking: challenge the data through testing, testing, testing. And if you test it multiple ways, you may find that your conclusion is correct.

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Why data-driven marketers shouldn't trust the data fully - Chief Marketing Technologist

Why data-driven marketers shouldn't trust the data fully - Chief Marketing Technologist | The MarTech Digest | Scoop.it

Digest...


But the choice of labels on that graph — admittedly, taken out of context — triggered an important tangent that I think is worth discussing. It’s good to be confident in embracing data-driven management, but great data-driven managers should always be skeptical of the data.

 

In some ways, this is Clay Christensen’s classic innovator’s dilemma: what worked in the past holds us back from what needs to change in the future. Data from the previous strategic context can further calcify that prior worldview. To break out of the dilemma, you need to consider different data. It’s not a question about whether the data is right, but whether it’s the right data.

 

You can have confidence in using data while not fully trusting the data. It’s not that you doubt its accuracy. But you’re skeptical of data’s context, relevance, and completeness in the conclusions that are being drawn from it.

 

“Fact-based decision-making” is a term that’s growing in popularity. And while I laud the intent behind it — data over opinions — I remain cautious that “facts” are a slippery thing, especially when you go from the what to the why. Opinions can be all too easily disguised with data to look like facts.

 

__________________________________

Receive a FREE daily summary of The Marketing Technology Alert directly to your inbox. To subscribe, please go to http://ineomarketing.com/About_The_MAR_Sub.html  (your privacy is protected).


Marteq's insight:

Scott Brinker often writes about hypothesis testing and the scientific method. And this is an adjunct of that thinking: challenge the data through testing, testing, testing. And if you test it multiple ways, you may find that your conclusion is correct.

Marteq's curator insight, November 12, 2013 9:41 PM

Scott Brinker often writes about hypothesis testing and the scientific method. And this is an adjunct of that thinking: challenge the data through testing, testing, testing. And if you test it multiple ways, you may find that your conclusion is correct.