Data with Consequence
Data With Consequence is a podcast about AI, data and decision-making, hosted by Garima Gupta, for leaders who act on the numbers. Most data shows start at the model, the metric or the tool. This one starts a step later: the moment someone makes a decision based on a number, and that decision has a consequence. Garima has built data functions from scratch three times and interviewed around two thousand data hires. She talks about where AI agents speed up data work, and where they fail without warning by making silent assumptions that produce confident, wrong answers. Episodes cover data...
Your Data Debt Is Trust Debt
Two teams used the same word, churn, and told leadership two different stories. Garima Gupta explains why the most underestimated data debt is a business that hasn't agreed on what its own metrics mean, and how to fix the definitions that cost you the most trust.
At an early-stage startup with 130 KPIs, product measured 60-day churn and finance measured 30-day churn. Investors saw one story while the roadmap followed another. Garima introduces the Blast-Radius Test for deciding which metric to settle first. She also shows how AI raises the stakes: a self-serve analytics agent failed...
Hire for the Floor. Bet on the Slope.
How do you hire data scientists and analysts when AI can write the SQL? Garima Gupta shares the hiring philosophy she drew from about 2,000 interviews: hire for the floor, bet on the slope.
Technical skill is the floor, a real gate every candidate has to clear. The slope is curiosity and ownership: whether someone understands the business problem before reaching for a solution. Garima compares two candidates. One was technically brilliant but couldn't say what his model changed. The other missed the hardest SQL question, then was promoted twice in about 12 to 15 months.
In this...
01: AI Doesn't Fail Loudly. It Fails Confidently
What if the biggest danger of artificial intelligence isn't that it fails, but that it delivers completely wrong answers with absolute confidence?
In this episode of Data With Consequence, I'm sharing a real experience that fundamentally changed how I think about AI, data analytics, and the role of human judgment in business decision-making.
My team built an AI-powered customer churn prediction model that appeared to work perfectly. No errors. No warnings. No technical failures. But buried inside the results was a critical mistake: the model predicted that a company's most loyal founding members were just...
