What's more sexy: analytics or innovation? What about combining them! That sounds great, and Thomas Davenport would be so proud if you pulled it off, but the reality is that the idea of innovation through analytics is one thing, while the reality of making it happen is another thing entirely. Dr. Tiffany Perkins-Munn, Head of Marketing Data & Analytics at JPMorgan Chase & Co., joined us for a discussion on the subject! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

We've been on a bit of a streak of culture and career discussions, which means we want to assure you that Tim is not actually tied up in a basement with no access to our content calendar. Actually, in this episode, Tim plopped down on the therapy couch as a vessel for the wisdom of Moe and Michael about structured techniques for analysts to chart the best paths for their careers. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Happy new year! We're not really resolution-making types, but the incrementing of the annum is a good time to take a breath and think about some ways we might want to approach our work differently. On this episode, we took a pretty big swing at "culture" — sitting down with Aaron Dignan, founder of Murmur, author of Brave New Work (and host of the eponymous podcast) — to discuss some of the ways modern organizations are, well, broken! From there, to the analysts within those organizations, to frameworks and approaches for getting to a better way of working, it was a brain-stretching way to kick off 2023! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

It's that one-time-of-the-year when we do a little bit of navel-gazing, a little bit of prognostication, and, when the year is a year like 2022, a little more cursing than usual. Not only did the podcast hit a fairly meaningless vanity metric milestone this year, but we also maintained our explicit rating! Executive producer Josh Crowhurst joined us to look back on the podcast and the analytics industry in 2022, as well as to do a little bit of crystal ball gazing into 2023 and beyond! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

You've got some solid experience under your belt, and you're starting to feel like you're ready to move into a data leadership role. What does that even mean? Shifting your keystrokes from SQL to slide decks? Maybe (but maybe not). Katie Bauer, Head of Data at GlossGenius, has held multiple data leadership roles over the course of her career, and she penned a thoughtful post on the various tactics she employed to find a role that is a good fit. She wrote the post so that she wouldn't have to keep repeating herself when data folks in her network reached out for advice. But that didn't stop this podcast from reaching out to record a lively discussion on the topic! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

As analysts, we conduct analysis on behalf of the business to (hopefully) provide them with clear and objective information to help with making decisions. We use visualizations of data and, when we're really hitting our stride, we even tell data stories. So, how does that compare to mainstream journalism and the stories they tell, especially when there is data that can be visualized in support of the story or the analysis? There could be no better guest than Philip Bump, long-time columnist for The Washington Post, author of the How to Read This Chart weekly newsletter, and author of a soon-to-be-published book about the baby boom generation! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Ethics in AI is a broad, deep, and tough subject. It's also, arguably, one of the most important subjects for analysts, data scientists, and organizations overall to deliberately and determinedly tackle as a standard part of how they do work. On this episode, Renée Cummings, Professor of Practice in Data Science and Data Activist in Residence at the University of Virginia (among many other roles), joined us for a discussion of the subject. Her knowledge of the topic is as deep as her passion for it, and both are bordering on the limitless, so it was an incredibly informative chat! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

So, you finally took that recruiter's call, and then you made it through the initial phone screen. You weren't really expecting that to happen, but now you're facing an actual interview! It sounds intense and, yet, you're not sure what to expect or how to prepare for it. Flash cards with statistical concepts? A crash course in Python? LinkedIn stalking of current employees of the company? Maybe. We asked Jay Feng from Interview Query to join us to discuss strategies and tactics for data scientists and analyst interviews, and we definitely wanted to hire him by the time we were done! 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 built a data-related "thing" — a dashboard, a data catalog, an experimentation platform, even — only to find that, rather than having the masses race to adopt it and use it on a daily basis, it gets an initial surge in usage… and then quietly dies? That's sorta' the topic of this episode. Except that's a pretty clunky and overly narrow summary. Partly, because it's a hard topic to summarize. But, data as a product and data products are the topic, and Eric Weber, the data scientist behind the From Data to Product newsletter, joined us for a discussion that we've been trying to make happen for months. It was worth the wait! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Do analysts make things more complicated than they need to be, or is the data representing a complex world, so that is just the nature of the beast? Or is it both? Stakeholders yearn for simple answers to simple questions, but the road to delivering meaningful results seems paved with potholes of statistical complexity, data nuances, and messy tooling. What is a business to do? Frederik Werner from DHL joined Michael and Tim for a discussion that definitively determined that, well, the topic is…complicated! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Here at the Analytics Power Hour, we have a very clear delineation of who owns what when it comes to the show production. And ownership is the topic of this episode. It's possible that the owner of the episode description feels like this is an awfully touchy-feely topic, but said owner also knows that teamwork means going along with the majority when it comes to show topics. I guess that's joint ownership? Can that work? Sadly, that, specifically, was not discussed, but the show definitely earned its explicit rating with this episode! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Our podcast junkie co-host heard the following statement on another podcast a while back when he was out for a jog: "I actually think the word 'uncertainty' is used in English in a very different way than the word 'uncertainty' is used in statistics." He almost ran into a tree (causation is unclear: he's not known for his gross motor skills, which may have been a confounder). Not only is that quote, essentially, the theme for this episode, but the person who said it, Dr. Rebecca Goldin from George Mason University, was our guest! And we are absolutely CERTAIN that it was every bit as enlightening a discussion as it was a fun one! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

We try not to navel gaze too much on this show, but our 200th episode felt like just enough of a milestone that we could do a mid-year "look back, look forward" show with a 7-year range. And we tracked down our original Commonwealth representative to join us for that discussion. Did we (first) party (cookie) like it was 1999? Maybe not, but that's the sort of reference you get with Jim Cain, the founder of Napkyn Analytics, and a co-founder of this very podcast! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Multi-touch attribution, media mix modeling, matched market testing. Are these the three Ms of marketing measurement (Egad! The alliteration continues!)? Seriously. What's with all the Ms here? Has anyone ever used experimentation to build a diminishing return curve for the impact of a media measurement technique based on how far along in the alphabet the letter of that technique is? Is "M" optimal?! Trust us. You will look back on this description after listening to this episode with John Wallace from LiftLab and find it… at least mildly amusing. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

We've always said that the genesis of this podcast was the lobby bar of analytics conferences across multiple continents, and this year's Marketing Analytics Summit in Las Vegas was a reminder of our roots on that front. All three co-hosts made the trip to Caesars Palace for the event. Moe presented on bringing a product mindset to analytics (by "presented on," we mean "workshopped content for a future podcast episode"), and the closing keynote was a recording of the show in front of a live (and thoughtful and engaged) audience. Give it a listen, and it will almost be like you were there! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Sure. GPT-3 and large language models in general can take a prompt and spin out in any of a million human-sounding directions. That's neat, but maybe not exactly what you'd want to turn loose as your guide through a narrative multiverse of AI-boosted creative play and community. "A what?" You say. Exactly. In this episode, we dug into Hilary Mason's latest endeavor, Hidden Door, and how she and her team are working to apply the right level of "human" to AI-driven narrative play. Intrigued? You should be! It's fascinating! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Every consumer is now aware, at some level, that they are constantly generating data simply by moving through the world. And, every organization that puts physical devices or digital experiences into the paths of consumers has to make decisions about what data they collect, how they manage it, and what they do with it (both the immediate plans and what unknown plans may emerge in the distant future). The questions, decisions, and mindsets that this reality brings into play are just one big gray area after another. Angela Bassa grapples with these issues on a daily basis both professionally and personally, so we sat down with her for a lively and thought-provoking discussion on the subject. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

The Web3 world—blockchain, cryptocurrency, NFTs, and more—seems to be everywhere these days. And, as analysts, how could we not salivate at the idea of a data set that is just one flat, immutable, ever-growing table with a handful of columns (aka… a blockchain-powered public ledger)? We sat down with Anthony Mandelli from Coin Metrics to see whether Tim and Moe could be moved from "totally clueless" to "barely knowledgeable" on the topic in a single hour (Michael was already a knowledgeable enthusiast). The jury is out as to whether we were successful, but stay tuned for the upcoming announcement of the Analytics Power Hour DAO we're starting up (we're minting RockFlag coins to make it happen). For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

The workplace is changing! Even before COVID, the look, feel, and layouts of offices went through various phases: the rise of cubicles in the 1960s (ick!) and then, decades later, the rise of the open office ("Headphones…deployed!") are just two examples. What does the "next" workplace look like in a world that supports remote work, hybrid work, and in-office work? It looks… complicated (but exciting). On this episode, David Stella from db.19 joined us to discuss how data (and experimentation!) can be an important tool when it comes to designing productive and effective professional environments. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

It's easy to get sucked into the "technology" side of things when it comes to improving the effectiveness and scaling up data teams, but, much to Tim's dismay, shoring up the people, process, and culture is often just as (if not more) critical. So, sure, we can talk about the modern data stack, but what about the modern data CULTURE stack? Prukalpa Sankar, co-founder of Atlan, joined us for a lively discussion of the topic! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

If you're like most data workers, you probably spend a little bit of time reacting to and servicing data requests, a bit more time on some larger analysis projects, and then you've got a big pile of free time where you're wondering what else you should be doing. Oh. No? You're absolutely drowning in work and questioning whether you're actually providing value? Yeah. That's actually much more common. We were just kidding with that opener. The great news, though, is that Emilie Schario joined us to talk about different tactics (strategies?) for finding the capacity to do more and better work, regardless of your level in your organization. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

"The people" are often the most valuable asset for a company, so getting the ones who are a good fit, supporting them in their work and their careers, and figuring out what motivates (and demotivates) them is critical. And data—both quantitative and qualitative—can help with that. It's a topic we've wanted to tackle for a long time (well, Moe and Michael have; Tim was confused, as he thought it couldn't be that hard to analyze a data set consisting of a single "Do they do their f***ing job?" boolean flag), and we finally got to it, with Andrew Marritt from OrganizationView! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

"Modern art" was a terrible label because, ya' know, time would pass and here we are 50 years after the end of that period shaking our heads at what a short-sighted semantic gaff that was. We share that observation for no particular reason. On this episode, we sat down with broad, deep, and entertaining thinker Benn Stancil from Mode to talk about one facet of the modern data stack: the metrics layer. What is it? Who's thinking about solving for it? What is a monthly DAU? These are questions to ponder that, hopefully, won't leave you impersonating a piece of modern art. For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

We are excited to announce APH+, a subscription that includes bonus content and other perks for our most dedicated listeners. 

Can a digital analyst make it to the C-suite? And, if she does, will she wonder, "Oh, dear. WHAT have I gotten myself into?!" The answer to the first question is "Yes!" And our guest for this episode is a proof point: Mai AlOwaish is the Chief Data and Innovation Officer at Gulf Bank, and she spent a good portion of her career in digital analytics before taking on that role! The answer to the second question is, "Not if you go in with a clear vision and strategy!" But, of course, there's a lot more to it than that! For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.