Rev 2, the second annual Summit for Data Science Leaders, is quickly approaching. This year’s conference will take place May 23-24 in New York City.
Early Bird pricing expires at the end of this month!
We’re incredibly humbled and excited by the data science leaders that will be joining this year’s event to share their experiences, learnings, and advice with the crowd. It’s in this spirit that we’ll spend a few minutes each week introducing our speakers here – in no particular order – to give you a sense for who they are, where they’ve come from, and why you might be interested in meeting them at Rev.
Let’s start by highlighting a Rev alum who will return to the stage this year: Eric Colson, who runs a team of more than 100 data scientists in his role as Chief Algorithms Officer of Stitch Fix. Prior to Stitch Fix, Eric served as VP of Data Science and Engineering at Netflix. Eric’s insightful presentations reflect his experience running data science organizations at truly model-driven companies that have disrupted industries. If you haven’t yet, you should read his recent HBR article “Why Data Science Teams Need Generalists Not Specialists”, or check out the blog he and Data Science Manager Hoda Eydgahi wrote on how to “Become a Full Stack Data Science Company”.
At Rev, Eric will share the stage with Stitch Fix Director of Data Science Daragh Sibley. Together, they will discuss how leaders can make better business decisions by deeply understanding the ways our brains are wired and the fallacies in our intuition that are often revealed through empirical A/B testing. This talk will be a compelling follow-on from Daniel Kahneman’s keynote address on The Psychology of Intuitive Judgment and Choices earlier that day.
Below you can view the complete details for Eric’s and Daragh’s session at Rev.
How to Make Fewer Bad Decisions
2:40 - 3:10 on Thursday, May 23
The increasing prevalence of A/B testing has revealed a powerful, but seldom discussed insight: Our intuitions are soberingly bad! Yet, most of us are either unaware or chose not to believe this. Time and time again, randomized controlled trials reveal that our predictions on the outcomes of business decisions are deeply fallible: Experiments show that our optimism in new features is often misguided; what we thought would help actually hurts; and what we believed to be the next big thing fails completely. Our intuitions can even lead to worse outcomes than what we would expect from random chance alone.
This is not a talk about A/B testing, but rather what empiricism reveals about our intuitions. We describe some types of errors domain experts commit. We discuss how these systematic errors arise from heuristic reasoning processes that served us well on an evolutionary time scale, but now impair our judgments. Using interactive audience demonstrations we illustrate how cognitive heuristics can compromise decisions and their evaluation.
While we can’t change how our brains are wired, knowledge of how they work can give us an advantage. There are several mechanisms to mitigate these human limitations and improve our decision-making. We believe that businesses which make fewer bad decisions will have a distinct competitive advantage.