Digital Analytics Power Hour
Without business acumen, even the most sophisticated models and dashboards fail to impact company outcomes, limiting analysts to a technical role rather than a strategic partner. As data environments grow more complex, cultivating this skill set helps professionals cut through noise, align insights with real business goals, and stay relevant in a rapidly evolving analytics landscape.
In episode 289 the hosts unpack business acumen as the missing link that transforms data analysts into strategic partners. They distinguish two complementary flavors: foundational business knowledge—finance, marketing, P&L mechanics—and deep, company‑specific context that includes industry nuances and internal challenges. By weaving these strands together, analysts move beyond building elegant dashboards to explaining how insights drive revenue, reduce churn, and influence top‑line decisions. This dual‑lens approach resonates across sectors, from e‑commerce subscription models to franchise‑based enterprises, highlighting why fluency in both generic concepts and the firm’s unique operating model is essential.
The conversation then shifts to why business acumen matters on the ground. Understanding how a company makes decisions—who the key stakeholders are, what metrics truly matter, and how revenue is recognized—allows analysts to frame recommendations that align with strategic priorities. Real‑world anecdotes illustrate the pitfalls of narrow focus: a monthly ROI report that ignored product‑line timelines, or teams optimizing the wrong metric and inflating acquisition costs. By recognizing cross‑functional tensions between sales, marketing, and finance, analysts can surface hidden frictions, avoid bias from over‑familiarity, and deliver insights that resonate across the organization.
Finally, the panel shares practical tactics for rapidly building acumen, especially for newcomers or external hires. They recommend structured stakeholder interviews, shadowing sessions across finance, marketing, and product, and immersing in industry‑specific literature to grasp vertical dynamics. Leveraging AI‑assisted tools like Ask Why can automate repetitive data tasks, freeing time for deeper business conversations. Continuous learning, curiosity, and a habit of questioning how data flows through the business ecosystem empower analysts to become trusted advisors, turning raw numbers into actionable strategy.
That darn data. It's so complicated and fragmented and gap-filled and noisy that no amount of time is ever enough to truly get to the bottom of all of its complexity. As a result, it's pretty easy to fill all of our time handling as much of that underlying data messiness as possible. At what cost, though? It's easy for the analyst's connection to the business to suffer as they get mired (too) deeply in the data and lose sight of the broader business needs. In this episode, the gang had a chat about business acumen—what it is, how to develop it, and why it's a must-have for any data or analytics role.
This episode's Measurement Bite from show sponsor Recast is a brief explanation of identifiability—what it is and how to check for it using simulation—from Michael Kaminsky!
For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.
#289: The Imperative of Developing Business Acumen
Published: Jan 20, 2026
That darn data. It’s so complicated and fragmented and gap‑filled and noisy that no amount of time is ever enough to truly get to the bottom of all of its complexity. As a result, it’s pretty easy to fill all of our time handling as much of that underlying data messiness as possible. At what cost, though? It’s easy for the analyst’s connection to the business to suffer as they get mired (too) deeply in the data and lose sight of the broader business needs.
In this episode, the gang had a chat about business acumen—what it is, how to develop it, and why it’s a must‑have for any data or analytics role.
This episode’s Measurement Bite from show sponsor Recast is a brief explanation of identifiability—what it is and how to check for it using simulation—from Michael Kaminsky!
Book: Psychology of Intelligence Analysis by Richards J. Heuer, Jr.
Program: Harvard Business School Online Credential Of Readiness (CORe)
Book: The Innovator’s Dilemma: The Revolutionary Book That Will Change the Way You Do Business by Clayton M. Christensen
Book: Humankind: A Hopeful History by Rutger Bregman
Book: Lord of the Flies by William Golding
Podcast Episode: The Real‑Life Lord of the Flies on the Everything Everywhere Daily podcast (this is not the episode Tim referenced on the show, but he found it while trying to track that down)
Podcast Episode: Chaos on the Throughline podcast (possibly/probably the episode Tim was remembering… and it also references Humankind: A Hopeful History!)
Video: In the Long Run, Everything is a Fad: Benn Stancil (Small Data SF 2025)
Podcast: Knowledge Distillation Episode #4: Michael Helbling on 20 Years in the Trenches, Why Trust Is the Real Bottleneck, and The Difference Between Data Retrieval and Actual Analysis
Conference: DataTune Nashville – March 6‑7, 2026, Nashville, TN
Conference: Marketing Analytics Summit – April 28‑29, 2026, Santa Barbara, CA
Website: Commoncog
Photo by Adeolu Eletu on Unsplash
00:00:05.76 [Announcer]: Welcome to the Analytics Power Hour. Analytics topics covered conversationally and sometimes with explicit language.
00:00:14.56 [Michael Helbling]: Hi everyone, welcome. It’s the Analytics Power Hour and this is episode 289. There’s a comfortable trap that a lot of us in this industry could fall into. We spend hours debating the merits of different data tools, what the best visualization is for a data set, or whether our tracking pixels are firing just right. Data is our craft, and we love it. But there is a harsh reality, and it usually hits about three to five years into a career. You can build the most rigorous model or beautiful dashboard, but if you can’t explain how it actually helps the company drive revenue or reduce churn, it kind of doesn’t matter. We like to complain about how our business stakeholders lack data fluency. But maybe we need to flip the mirror and ask ourselves the hard question. Do we lack business literacy? So that’s what we’re going to talk about. Business acumen. Is it the missing link that turns a data analyst into an actual strategic partner? We’ll talk about it. And to do that, let me introduce my co‑hosts, Val Crawl. Hi, Michael. Hey. And of course, Tim Wilson. Hello. Hello and welcome. And Moee Kisss.
00:01:27.32 [Moe Kiss]: Howdy, team.
00:01:28.68 [Michael Helbling]: Hey, and I’m Michael Helbling. All right. I think maybe to kick things off, we should start with like a brief intro to maybe a definition about what we mean when we say business acumen in the first place. Anybody want to take a first stab at it?
00:01:45.65 [Tim Wilson]: I think as we were thinking about this, the little light bulb that went on for me is there’s two types of business acumen and one of them being knowledge of business itself. This is how business, this is how finance works, this is balance sheet, income statement, cash flows, marketing, four P’s and more—whatever aspect of the business, which is kind of, this is something that you build over time and take throughout and are sort of truisms or practices in business. And then there’s another type of acumen, which is like knowledge of your business, the company you’re working for or with and understanding where they are unique, they all are doing, they overlap and that your business is operating in the context of the broader business, but there is what are the specific external and internal challenges that your business is facing. So to me, that’s, I don’t know if that’s a definition, but that’s kind of two flavors of it.
00:02:54.38 [Moe Kiss]: But if you had to pick, if you had to stack rank, do you think one is more important than the other?
00:02:59.80 [Tim Wilson]: I feel like they leapfrog as they go along, because you can’t be super incredibly deep in one without being deep in the other. If you were trying to say, I’m just going to know everything about the organization I work for, at some point you’re going to run into the finance team who’s going to be talking about revenue recognition.
00:03:26.36 [Michael Helbling]: Yeah, because I think on the first level, the first one is concepts. So how does a P&L work? And then the second one is context. How does it work in our company? And maybe that would frame it like that. And I don’t know if I could pick, Moee, to your question, which of those is more important. I feel like you need both of those wherever you’re going to be if you’re going to really, truly own business acumen in the place where you work.
00:03:53.84 [Moe Kiss]: It’s funny, though. One of the things that my mind goes to is, is there also like a third category, which is like knowing your type of business, like your industry, right? So like you can have a really deep experience in like e‑commerce or FMCG or, I don’t know, insurance or government or something. And that’s like a different type of knowledge and experience that you can apply as well.
00:04:17.17 [Michael Helbling]: Oh yeah. I think that’s true. I still boil that into the context, you know, awareness of how your business or your vertical works.
00:04:25.82 [Tim Wilson]: But I think that how you’re running is a good, the FMCG or CPG is a good example when you, the number of FMCG brands I’ve worked with who’ve said, we want to be like and they insert B2C retailer. And it’s like, well, yeah. And they’re like, yeah, all we need to do is get direct information about our individual buyers. I’m like, you’re selling soap. That’s where on earth would you have that permission? I mean, maybe that goes back to the concepts of saying, well, you’d understand what the limitations are in the context of this vertical and what you have to do instead. But as you’re talking, I just realized this week had a case where two completely different verticals, but both of them had a franchise model was kind of the way they were working, completely different spaces. And I was kind of like pleasantly surprised to realize that there were some similarities into how that sort of corporate franchisee relationship worked and was managed that was shockingly parallel. And I haven’t worked with that many franchises, but I was like, oh, wait a minute, does every brand that operates on a franchise model or do most of them have this sort of setup. And that went from learning it for one and then kind of stumbling across it for another. But applying those patterns, which I think, Michael, you’re having those concepts and saying, okay, how does that concept apply in this specific context is a, I love that phrasing.
00:06:08.26 [Moe Kiss]: It’s funny though, the one thought I do have about knowledge of your business. Well, I have multiple thoughts. One is, I suppose the first being, it can really unlock a lot in terms of, let’s say hypothetically, you’re talking about maturity or data usage and how great it is in the company. You ask folks to give you a score of zero to 10, right? Zero totally should house and 10 being amazing industry leading, most data‑driven, I’ve got air quotes for those listening along, company in the world. And it’s like, you might have knowledge that actually your company can only get to an eight, like a 10 is just not possible at your company for various factors. But it’s interesting because at the same time I say that, I also think it can danger the work that you do and how you provide it sometimes by absolutely biasing your approach. Like you think of Richard Harris’s book, The Psychology of Intelligence Analysis, and for that reason they tell analysts to move around because if you know something too well, you can also make mistakes.
00:07:12.87 [Michael Helbling]: I think, Moe, that’s an incredible point because it’s very natural for people to get locked in on whatever function they’re in. As analysts, it’s an amazing experience to see different parts of the business and build context around those and see how they work together and build out knowledge across. Finance and the way they look and analyze data is different than how marketing does versus how merchandising does versus how sales does. All these different functions within the business look at it different ways. You can become a much more fully‑featured business analyst by taking time in each of those. You can sometimes get a little bit too—I don’t want to say stuck—but there’s a bias that can influence how you even approach or think about what’s possible in terms of insight or action or recommendation that then leaves your analysis not as fresh or aggressive enough. I don’t know the right way to say that good, well, but that’s what I think you’re trying to say too.
00:08:22.77 [Val Kroll]: I think that’s a good connection point between some of the concepts we’re talking about and what that means to the analyst connecting it to their work. I think what you were just talking about, Michael, with the recommendations and the actions, when I think of business acumen and analysts and like building the skill, I think one of the first things is just understanding how the business makes decisions. Therefore, you can come up with the best ways to think about framing or recommendations or proposing actions for the business because it’s like, what is your relationship, you know, but everyone, you know, well‑tread area between sales and marketing, but like, what is your relationship with other decision‑making arms of the business and how is it supporting that, whether you’re in‑house or consulting, yeah.
00:09:07.59 [Moe Kiss]: It’s funny. I actually had someone ask that in an interview and I to this day always reflect on it being such a great question. The question was “how does the business make decisions? Like who are the key decision makers and talk me through the process of how they get signed, you know, folks get signed off for something.” And I was like, it actually is such a wonderful question because it tells you so much about the culture and the ways of working. Like it really is an unlock for someone who is trying to gain that knowledge of the business quickly.
00:09:38.21 [Tim Wilson]: I think there’s cases where I think that’s a love‑that point and it also is the sort of thing we’re talking about like to be a better analyst, to be thinking kind of not necessarily just who you’re direct partner that you’re supporting and I think they can wind up in a group in a, not a group thing, but kind of caught in a way of this is somebody who may be a mid‑level paid media person and they have been poisoned by their media agency as to what metrics matter and they’re not necessarily don’t. thinking through the broader business, how decisions are getting made, what sales is expecting, what is coming back. There can sometimes be a challenge or an opportunity for the analysts to say, I can’t just trust exactly who I’m supporting. I mean, you want to have a positive relationship, assume good intent, but there are definitely plenty of people in business who are operating with blinders on and often the analysts are the ones, if we’re trying to connect the dots, you need to have more than one dot. So that’s kind of a weird, as you’re talking, it’s making me think about sometimes the analysts needing or having value and having a broader perspective in order to do the analysis that may be providing to somebody who has a narrower perspective to help broaden their perspective.
00:11:04.29 [Val Kroll]: No, I like that. And I think even thinking, I completely agree, because even if you think about the group that you’re supporting, it’s always helpful to think about who else might have a completely inverse motivation at that table. Even if you think about resources and thinking about budget allocation or time allocation of resources or, you know, marketing wants as many leads as possible, but sales only wants to qualify leads. So there’s like this tension that I think you can tap into between these different groups to understand, you know, there was a group we were working with where we were working the leaders high up enough that we had one group in the retail group that was focused on the sell‑in to the marketplace partners, and then there was a group sitting across the table from them that was only focused on sell‑through. And so we had to think about how do these two concepts work together and what is the thread between them that kind of aligns to, again, how the business is making decisions. But I think that those, the motivations, even if it’s not a stated goal, helps you understand the friction and who might be not thinking the same way as the client and the group you’re supporting.
00:12:14.81 [Tim Wilson]: Okay, time …
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