What is a system without empathy? What is a show summary without an attempt to overly distill the discussion to the point of sounding like nonsense? On this episode, Hilary Parker (who you may know from the Not So Standard Deviations podcast or elsewhere) joined us to discuss what we can learn from the design process (as in: actual designers) when it comes to analytics and data science. Among other things, that mindset highlights the importance of the analyst empathizing with stakeholders. Tim got very uncomfortable. Michael said he understood Tim's discomfort. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Stop for a minute and think about the highest stakes campaign or test you've ever run. Were you nervous? Now, instead, imagine that you're on an aircraft carrier with a few thousand people on board whose safety you are responsible for, and your team is about to watch 40,000 tons of ordnance detonate (in an environmentally friendly way) right next to the ship... so you can collect data to verify that the various systems are working as expected. On this episode, our guest can't really talk about the former situation, but he can discuss the latter in depth: Capt. Paul Lanzilotta is the commanding officer of the USS Gerald R. Ford, the lead ship in the latest class of U.S. Navy aircraft carriers. Perspective, much? For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

As analysts, it can be easy to get so focused on the data that we lose sight of the imperative that we answer meaningful questions (aka: validating relevant hypotheses). On this episode, we sat down with Wil Reynolds, co-founder and accidental lead generator for SEER Interactive, for a discussion that turned out to be about curiosity and the power of trying to prove yourself wrong (and being willing to invest the time to do so!). In the end, we concluded that Wil has always been a "data person," even if he doesn’t necessarily see himself as such. That is... actually kinda' profound! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Have you ever worked in a large organization where the data team(s) are perfectly structured to deliver efficient, harmonious, and meaningful results to the business with 'nary a gap nor a redundancy? If you answered "yes," then we'll go ahead and report you to HR for being a LIAR! From high growth startups to staid enterprises, figuring out how to organize the data and data-adjacent teams is always chock full of tradeoffs. And that's the topic of this episode. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Have you ever thought, "you know, it would be interesting to take my analytical knowledge and just totally run an organization based on what the data says?" Yeah. Us, either. That's terrifying! But, that's exactly what our guest on this episode did. Ben Lindbergh, along with his stathead-in-crime (aka, co-author) Sam Miller, took over the management of a minor league baseball team in 2015, and the result was The Only Rule Is It Has to Work: Our Wild Experiment Building a New Kind of Baseball Team. How does that apply to analytics in the business world? In a surprising number of ways, it turns out! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Data is everywhere and it's simply not going away. Plenty of people do seem to ignore it to their peril, but if we are trying to make sense of the world, making good sense of data is absolutely critical. In business we call it data literacy, and, truthfully, it is a mandatory skill set for almost anyone. Data and understanding data might have a set of rules, and it seems like not everyone is committed to playing by those rules. Sometimes even our own brains get in on the act of hiding what the data actually means from us. And that's the subject of this episode with Financial Times columnist, BBC presenter, and Data Detective / How to Make the World Add Up author Tim Harford. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

We're baaaaaaack…! Shorter show name, a rebrand, some minor formatting and structural updates, but still "Moe Kiss with a couple of guys who listeners can't keep straight." On this episode, we talk for a little bit about what we've been doing while we were on hiatus and then dive into a topic that only Cassie Kozyrkov has dared to deeply explore before: the distinction between analysts, statisticians, data engineers, ML engineers...and data charlatans. Well, really just the first two. But, Cassie('s content) has made numerous appearances on the show, so it seemed like high time that we dug into some of her ideas. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Once upon a time, there was an analyst. And that analyst had some data. She used that data to do some analysis, and from that analysis she realized she had some recommendations she could make to her organization. This was the point where our intrepid analyst reached a metaphorical fork in Communication Road: would she hastily put all of her thoughts together quickly in a slide deck with charts and graphs and bullets, or would she pause, step back, and craft a true data story? Well, if she listened to this episode of the podcast with presentation legend Nancy Duarte, author of five award-winning books (the most recent one — DataStory: Explain Data and Inspire Action Through Story — being the main focus of this episode) she would do the latter, and her story would have a happy ending indeed! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page. This episode originally aired on December 17, 2019.

We can watch (sort of) what users do on our sites. That's web analytics. We can ask them how they felt about the experience. That's voice of the customer. But, can we (and should we?) actually analyze their emotional reactions? On this episode, Michael and Tim sat down with Dr. Liraz Margalit, Head of Digital Behavioral Research at Clicktale, to bend their brains a bit around that very topic. And, they left the discussion thinking differently about conversion rates, and even realizing that scroll tracking might just have a valuable application! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page. This episode originally aired on June 20, 2017.

Do you model professionally? Would you like to? Or, are you uncertain. These are the topics of this episode: Bayesian statistician (among other official roles that are way less fun to say) Dr. Elea Feit joined the gang to discuss how we, as analysts, think about data put it to use. Things got pretty deep, included the exploration of questions such as, "If you run a test that includes a holdout group, is that an A/B test?" This episode ran a little long, but our confidence level is quite high that you will be totally fine with that. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.  This episode originally aired on March 13, 2018.