storytelling with data podcast

The episode contains a handful of genuinely useful pedagogical techniques (the 3-minute story constraint, the Thomas Edison/Shark Tank persona exercise, the AI sandbox day) but is padded with well-worn data communication platitudes and repeated affirmations between guests. For a B2B operator rather than an educator, the actionable idea density is notably low.

“analysis alone doesn't tend to lead to action, but understanding does”

“the constraint, that time constraint is very powerful because it forces clarity and it mirrors those real life situations where time is limited”

A few creative exercises stand out - particularly the historical persona (Edison pitching Shark Tank investors) and the AI sandbox experiment testing Claude vs. ChatGPT vs. Gemini for graph design - but the majority of the episode recycles standard data-viz orthodoxy (audience first, declutter, tools are agnostic) without any contrarian or first-principles argument.

“I gave them all a graph and then I gave them a better graph, right? So I said, this is an example of an existing graph. This is an example of what I would consider good looks like. And their challenge that class was to open any AI tool and try to replicate what good looks like”

“I introduced this element of who's the storyteller? And in this case I said it's Thomas Edison”

Elizabeth Ricks is a credible practitioner as an early Storytelling with Data hire turned academic; the others are working professors with adjacent industry exposure. However, the panel skews heavily academic and is narrowly relevant to educators, not to B2B operators trying to improve internal data communication at scale.

“my graduate degree is in business analytics. However, at the time that I went to graduate school, I did not learn anything about effective communication with data. So I learned that the hard way in my own analytical career”

“I teach in the executive MBA program at Xavier University in Cincinnati, Ohio”

The episode names specific tools (Tableau, Power BI, Claude, Kaggle), specific institutions, and even a specific AI experiment with outcomes described qualitatively; however, there are no learning-outcome metrics, no business-impact numbers, and no hard evidence that any of these techniques actually improve practitioner performance.

“our books are currently being used by over 750 instructors in courses across numerous disciplines and countries”

“Most of us were very frustrated by the end of this class because we had spent a ton of time prompting, coaxing and none of the AI tools, and we used everything from Chat to Gemini to Claude, were able to design graphs in the way that we would like them to”

The host keeps the conversation organized and asks topically sensible questions, but she never challenges a claim, never probes for evidence behind assertions, and frequently validates guests effusively before moving on. The format functions more as a coordinated panel showcase than an interview with genuine intellectual friction.

“That is so well said, Lisa”

“I love how you gamify it a little bit with getting the investors to fund the entrepreneurs”