Before there was BI, there were "decision support systems." Somewhere along the way, we seem to have quietly dropped the "decision support" part and just kept the systems. Zohar Strinka, founder of Analytics Strategies and creator of the Meta-Problem Method, joined us to put the point back where it belongs: if nothing is going to be done differently after the analysis, then the analysis had exactly zero effect on the world. But -- and this is the part that's easy to miss -- that does NOT mean marching up to a stakeholder and demanding, "What decision are you going to make?" People don't want a model that hands them the right answer. They want to understand and weigh the trade-offs themselves, which means good decision support looks a lot more like a really well-informed pro/con list than a score. We got into problem spaces, high-yield problems, the cost of being wrong in each direction, why "we have all this data, so the answer must be in here" is really just a person pulverizing a bag of rocks hoping for diamonds, and, ultimately, peanut butter.

This episode is brought to you, in part, by our sponsors, Stape and Prism from Ask-Y.

For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Stephen Follows has spent 15 years turning film-industry curiosity into a career — asking questions like how much movies really earn, why poster colors have shifted over decades, and whether old studio domains are still up for grabs. In this episode, he joined us to talk about building that unusual path, the cautionary tale of TheNumbers.com, and his theory about Sandra Bullock. Go start your passion project.

This episode is brought to you, in part, by our sponsors, Prism from Ask-Y and Stape.

For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.

Everyone's posting their AI projects online like proud pet owners sharing videos of their cat doing something marginally impressive — cute, occasionally clever, sometimes a little cringe. And the Analytics Power Hour is no different! In this co-hosts-only episode, Tim, Michael, and Julie skip the thought leadership hot takes and just… compare notes. What have they actually built? What broke? What surprised them? From a custom GPT podcast librarian to a full-blown show production app wired up to Neon, Vercel, Resend, and about five other things Michael is only sort of sure he set up correctly, to a Gemini Gem that simulates a client interaction so realistically it raises your blood pressure in a safe environment — there's a lot of ground covered. Plus: why AI-generated communication has a Stevia aftertaste, why deploying AI context across a team is way harder than it looks, and why the LLM will absolutely tell you what you want to hear about your Meta spend if you give it half a chance.

This episode is brought to you, in part, by our sponsors, Stape and Prism from Ask-Y.

For complete show notes, including links to items mentioned in this episode and a transcript of the show, visit the show page.