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PODCAST

The Analytics Power Hour

Michael Helbling, Moe Kiss, Tim Wilson, Val Kroll, and Julie Hoyer

Attend any conference for any topic and you will hear people saying after that the best and most informative discussions happened in the bar after the show. Read any business magazine and you will find an article saying something along the lines of "Business Analytics is the hottest job category out there, and there is a significant lack of people, process and best practice." In this case the conference was eMetrics, the bar was….multiple, and the attendees were Michael Helbling, Tim Wilson and Jim

business marketing

All Episodes

01:07:14

#268: You Get an Insight! And YOU Get an Insight!...

The Analytics Power Hour ·

2025/04/01

Do you cringe at the mere mention of the word, "insights"? What about its fancier cousin, "actionable insights"? We do, too. As a matter of fact, on this episode, we discovered that Moe has developed an uncontrollable reflex: any time she utters the word, her hands shoot up uncontrolled to form air quotes. Alas! Our podcast is an audio medium! What about those poor souls who got hired into an "Insights & Analytics" team within their company? Egad! Nonetheless, inspired by an email exchange with a

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01:01:11

#267: Regression? It Can be Extraordinary! (OLS FTW....

The Analytics Power Hour ·

2025/03/18

Why? Or… y? What is y? Why, it's mx + b! It's the formula for a line, which is just a hop, a skip, and an error term away from the formula for a linear regression! On the one hand, it couldn't be simpler. On the other hand, it's a broad and deep topic. You've got your parameters, your feature engineering, your regularization, the risks of flawed assumptions and multicollinearity and overfitting, the distinction between inference and prediction... and that's just a warm-up! What variables would you

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58:59

#266: AI Projects: From Obstacles to Opportunities

The Analytics Power Hour ·

2025/03/04

In celebration of International Women’s Day, this episode of Analytics Power Hour features an all-female crew discussing the challenges and opportunities in AI projects. Moe Kiss, Julie Hoyer and Val Kroll, dive into this AI topic with guest expert, Kathleen Walch, who co-developed the CPMAI methodology and the seven patterns of AI (super helpful for your AI use cases!). Kathleen has helpful frameworks and colorful examples to illustrate the importance of setting expectations upfront with all

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55:03

#265: Connected Wellness in the Age of AI with...

The Analytics Power Hour ·

2025/02/18

Every listener of this show is keenly aware that they are enabling the collection of various forms of hyper-specific data. Smartphones are movement and light biometric data collection machines. Many of us augment this data with a smartwatch, a smart ring, or both. A connected scale? Sure! Maybe even a continuous glucose monitor (CGM)! But… why? And what are the ramifications both for changing the ways we move through life for the better (Live healthier! Proactive wellness!) and for the worse

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01:08:15

#264: When the Analyst’s Toolbox Includes Assessing...

The Analytics Power Hour ·

2025/02/04

We all know that data doesn't speak for itself, but what happens when multiple instruments of measurement contain flaws or gaps that impede our ability to measure what matters on their own? Turning to our intuition and triangulation of what's happening in the broader macro sense can often help explain our understanding of our customers' ever-changing choices, opinions, and actions. Thankfully we had Erika Olson, co-founder of fwd. — which in our opinion is essentially the Freakonomics of marketing

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01:06:18

#263: Analytics the Right Way

The Analytics Power Hour ·

2025/01/21

Every so often, one of the co-hosts of this podcast co-authors a book. And by “every so often” we mean “it’s happened once so far.” Tim, along with (multi-)past guest Dr. Joe Sutherland, just published Analytics the Right Way: A Business Leader's Guide to Putting Data to Productive Use, and we got to sit them down for a chat about it! From misconceptions about data to the potential outcomes framework to economists as the butt of a joke about the absolute objectivity of data (spoiler: data is not

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22:46

(Bonus) 2024 Listener Survey...Wrapped!

The Analytics Power Hour ·

2025/01/14

The start of a new year is a great time for reflection as well as planning for the year ahead. Join us for this special bonus episode where we talk through some of our favorite learnings and takeaways from our 2024 listener survey and some of the ways we’ve already been able to put that feedback into practice! We also have some freebies and helpful nuggets to share with our listeners, so be sure to tune in to learn more. For complete show notes, including links to items mentioned in this episode and

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01:08:09

#262: 2025 Will Be the Year of... with Barr Moses

The Analytics Power Hour ·

2025/01/07

Every year kicks off with an air of expectation. How much of our Professional Life in 2025 is going to look a lot like 2024? How much will look different, but we have a pretty good idea of what the difference will be? What will surprise us entirely—the unknown unknowns? By definition, that last one is unknowable. But we thought it would be fun to sit down with returning guest Barr Moses from Monte Carlo to see what we could nail down anyway. The result? A pretty wide-ranging discussion about data

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01:03:33

#261: 2024 Year in Review

The Analytics Power Hour ·

2024/12/24

Ten years ago, on a cold dark night, a podcast was started, 'neath the pale moonlight. There were few there to see (or listen), but they all agreed that the show that was started looked a lot like we. And here we are a decade later with a diverse group of backgrounds, perspectives, and musical tastes (see the lyrics for "Long Black Veil" if you missed the reference in the opening of this episode description) still nattering on about analytics topics of the day. It's our annual tradition of looking

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01:00:08

#260: Once Upon a Data Story with Duncan Clark

The Analytics Power Hour ·

2024/12/10

Data storytelling is a perpetually hot topic in analytics and data science. It's easy to say, and it feels pretty easy to understand, but it's quite difficult to consistently do well. As our guest, Duncan Clark, co-founder and CEO of Flourish and Head of Europe for Canva, described it, there's a difference between "communicating" and "understanding" (or, as Moe put it, there's a difference between "explaining" and "exploring"). Data storytelling is all about the former, and it requires hard work and

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01:01:30

#259: Dateline Data

The Analytics Power Hour ·

2024/11/26

There's data, data everywhere, including in the media! Data often gets collected, analyzed, published in a study, covered by a journalist, and then distilled down to a headline. The opportunities for lost-in-translation (or lost-in-simplification? Lost-in-summarization?) misfires are many. We tried an experiment—each of the available co-hosts brought some headlines that made them raise an eyebrow, and we tested our own data literacy (data skepticism) with a real-time review. The parallels to the

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01:05:52

#258: Goals, KPIs, and Targets, Oh My! with Tim Wilson

The Analytics Power Hour ·

2024/11/12

KPIs? Really? It’s 2024. Can’t we just ask Claude to generate those for us? We say… no. There are lots and lots of things that AI can take on or streamline, but getting meaningful, outcome-oriented alignment within a set of business partners as they plan a campaign, project, or initiative isn’t one of them! Or, at least, we’re pretty sure that’s what our special guest for this episode would say. He’s been thinking about (and ranting about) organizations’ failure to take goal establishment, KPI

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01:05:35

#257: Analyst Use Cases for Generative AI

The Analytics Power Hour ·

2024/10/29

udging by the number of inbound pitches we get from PR firms, AI is absolutely going to replace most of the work of the analyst some time in the next few weeks. It’s just a matter of time until some startup gets enough market traction to make that happen (business tip: niche podcasts are likely not a productive path to market dominance, no matter what Claude from Marketing says). We’re skeptical. But that doesn’t mean we don’t think there are a lot of useful applications of generative AI for the

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01:27:17

#256: Live at MeasureCamp Chicago

The Analytics Power Hour ·

2024/10/15

For the first time since they've been a party of five, all of the Analytics Power Hour co-hosts assembled in the same location. That location? The Windy City. The occasion? Chicago's first ever MeasureCamp! The crew was busy throughout the day inviting attendees to "hop on the mic" with them to answer various questions. We covered everything from favorite interview questions to tips and tricks, with some #hottake questions thrown in for fun. During the happy hour at the end of the day, we also

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59:23

#255: Dear APH-y: Career Inflection Points

The Analytics Power Hour ·

2024/10/01

To data analyst, or to data science? To individually contribute, or to manage the individual contributions of others? To mid-career pivot into analytics, or to… oh, hell yes! That last one isn’t really a choice, is it? At least, not for listeners who are drawn to this podcast. And this episode is a show that can be directly attributed to listeners. As we gathered feedback in our recent listener survey, we asked for topic suggestions, and a neat little set of those suggestions were all centered

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01:04:35

#254: Is Your Use of Benchmarks Above Average? with...

The Analytics Power Hour ·

2024/09/17

It's human nature to want to compare yourself or your organization against your competition, but how valuable are benchmarks to your business strategy? Benchmarks can be dangerous. You can rarely put your hands on all the background and context since, by definition, benchmark data is external to your organization. And you can also argue that benchmarks are a lazy way to evaluate performance, or at least some co-hosts on this episode feel that way! Eric Sandosham, founder and partner at Red & White

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01:08:03

#253: Adopting a Just In Time, Just Enough Data...

The Analytics Power Hour ·

2024/09/03

While we don’t often call it out explicitly, the driving force behind much of what and how much data we collect is driven by a "just in case" mentality: we don't know exactly HOW that next piece of data will be put to use, but we better collect it to minimize the potential for future regret about NOT collecting it. Data collection is an optionality play—we strive to capture "all the data" so that we have as many potential options as possible for how it gets crunched somewhere down the road. On this

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52:19

#252: The Ever-Shifting Operating Environment of the...

The Analytics Power Hour ·

2024/08/20

Broadly writ, we’re all in the business of data work in some form, right? It’s almost like we’re all swimming around in a big data lake, and our peers are swimming around it, too, and so are our business partners. There might be some HiPPOs and some SLOTHs splashing around in the shallow end, and the contours of the lake keep changing. Is lifeguarding…or writing SQL…or prompt engineering to get AI to write SQL…or identifying business problems a job or a skill? Does it matter? Aren’t we all just

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01:01:29

#251: The Continued Rise of the Analytics Engineer...

The Analytics Power Hour ·

2024/08/06

We're seeing the title "Analytics Engineer" continue to rise, and it’s in large part due to individuals realizing that there's a name for the type of work they've found themselves doing more and more. In today's landscape, there's truly a need for someone with some Data Engineering chops with an eye towards business use cases. We were fortunate to have the one of the co-authors of The Fundamentals of Analytics Engineering, Dumky de Wilde, join us to discuss the ins and outs of this popular role

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01:05:03

#250: Real World Data (RWD) Lessons from...

The Analytics Power Hour ·

2024/07/23

A claim: in the world of business analytics, the default/primary source of data is real world data collected through some form of observation or tracking. Occasionally, when the stakes are sufficiently high and we need stronger evidence, we'll run some form of controlled experiment, like an A/B test. Contrast that with the world of healthcare, where the default source of data for determining a treatment's safety and efficacy is a randomized controlled trial (RCT), and it's only been relatively

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299 results

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