Jim Harris shows how data-driven businesses incorporate three aspects of data governance to guide their decisions.
Tag: data driven decision making
Two years ago, I found myself the proud, first-time owner of a garage. My wife and I quickly started to add new items to the garage – a battery-powered lawn mower, two beach cruisers and four Tommy Bahama beach chairs. They were stored with ease. What a fantastic world I'd been missing out on. But it wasn't long before we outstripped our
Henrik Liliendahl Sørensen recently blogged about the times when a HiPPO (Highest Paid Person’s Opinion) outweighs data in business decision-making. While I have seen plenty of hefty opinions trump high-quality data, those opinions did not always come from the highest paid person. The stubborn truth is that we all hold our
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
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
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
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
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
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
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