Big data and omission neglect

In my previous post, I used the book Mastermind: How to Think Like Sherlock Holmes by Maria Konnikova to explain how additional information can make us overconfident even when it doesn’t add to our knowledge in a significant way. Knowing this can help us determine how much data our decisions need to be driven […]

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Big data and the treadmill of overconfidence

In her book Mastermind: How to Think Like Sherlock Holmes, Maria Konnikova discussed four sets of circumstances that tend to make us overconfident: Familiarity — When we are dealing with familiar tasks, we feel somehow safer, thinking that we don't have the same need for caution as we would when trying something […]

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Sisyphus didn’t need a fitness tracker

In his pithy style, Seth Godin’s recent blog post Analytics without action said more in 32 words than most posts say in 320 words or most white papers say in 3200 words. (For those counting along, my opening sentence alone used 32 words). Godin’s blog post, in its entirety, stated: “Don’t measure […]

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Data science versus narrative psychology

My previous post explained how confirmation bias can prevent you from behaving like the natural data scientist you like to imagine you are by driving your decision making toward data that confirms your existing beliefs. This post tells the story of another cognitive bias that works against data science. Consider the following scenario: Company-wide […]

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Can data change an already made up mind?

Nowadays we hear a lot about how important it is that we are data-driven in our decision-making. We also hear a lot of criticism aimed at those that are driven more by intuition than data. Like most things in life, however, there’s a big difference between theory and practice. It’s […]

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Data science and decision science

Data science, as Deepinder Dhingra recently blogged, “is essentially an intersection of math and technology skills.” Individuals with these skills have been labeled data scientists and organizations are competing to hire them. “But what organizations need,” Dhingra explained, “are individuals who, in addition to math and technology, can bring in […]

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The data that supported the decision

Data-driven journalism has driven some of my recent posts. I blogged about turning anecdote into data and how being data-driven means being question-driven. The latter noted the similarity between interviewing people and interviewing data. In this post I want to examine interviewing people about data, especially the data used by people to drive […]

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O say can you see by the data’s insight?

I have previously compared data visualizations to the magic mirrors of business intended to reflect what you need to see, such as true business insights, but which, because of how our eyes process data, may just be reflecting back your own image of what you want your data to show […]

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This isn’t Jeopardy

Imagine a political debate between two candidates where one candidate answers every question quickly, beaming with confidence, and the other candidate answers every question slowly, and with less assertiveness in their response. tags: business intelligence, data driven decision making, data quality

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The data sharpshooter fallacy

Jim Harris (@ocdqblog) explains the Data Sharpshooter Fallacy.

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