When people think of analytics data, many often think of “cold hard facts”, but this is can be very inaccurate. Like many other things in life, data can be skewed, biased, or even outright corrupted. Everyone has a bias and for an analytics team to act as an independent voice in an organization, steps need to be taken to ensure bias does not impact a team’s ability to deliver on that promise.
Putting unintentional issues and flaws with data aside, what steps can those that lead analytics programs do to ensure data is not intentionally or unintentionally influenced by biases? What can be done to ensure an analytics team does not create conflicts of interest?
On this week’s episode of the 33 Tangents podcast, Jim and Jason discuss how to address conflicts of interest and developing a plan to prevent them from becoming a reality. They also talk about why many times this is a topic that is avoided within analytics teams.
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