You want to drive adoption of a critical new AI tool. Your data team builds a model and tells you to target the obvious evangelists—the...

You just invested millions in a new country-wide sales program. The initial data says it's working… on average. But what if that...

Your new loyalty program is a roaring success… or is it? You set a threshold: spend over €100/month and get a 10% discount. A quick...

Your brand perception report is already a history lesson. Here’s a story I see play out constantly. A major consumer goods company tracks...

That 'sophisticated AI' your team built to predict employee turnover? It might be an illusion. A very expensive, beautifully back-tested...

Your company is flying blind, and your big data model is the blindfold. A major music streaming service is facing a crisis. Their most...

Your LLM just cost you a seven-figure fine. It confidently misclassified a critical customer complaint as a simple inquiry, and you had...

You look at the dashboard. Sales for your flagship product are flat, but stable. Customer surveys show a respectable 4.2 out of 5...

Let's be brutally honest. Most corporate recommendation engines are stuck in kindergarten. They operate on a laughably simple logic: "You...

Your company just invested in a state-of-the-art AI system. You were promised transparency. You were promised "Explainable AI." When the...

Your ML model is telling you a beautiful story. The problem? It's probably fiction. You have a model that predicts customer churn with...

Stop Asking "Did It Work?" Start Asking "WHO Did It Work For?" I see it constantly. Companies spend millions on a new training program, a...

Every empty seat on an airplane is a perishable good. The moment the cabin door closes, its potential value drops to zero. The central...

What was the ROI of that massive Olympics ad campaign? Or the real impact of your new flagship store? When you make a huge, one-of-a-kind...

You’re spending millions on programs, but can you prove they actually work? I’m not talking about pretty dashboards showing a “before...

Your new booking platform has been live for two years. You know it created a lift at launch. But what's the real ROI now ? Has the effect...

Your new loyalty program launched six months ago. You know the one-month effect on customer spending, but what about the six-month...

For the past two months, we've gone deep. We've talked Causal DAGs, RCTs, SUTVA, and the failures of strategy that lead to "dashboard...

we have to think like physicists. We must start with the Potential Outcomes Framework. It’s a simple but profound idea: for any person, city, or store, there are multiple potential realities. There’s the reality where they got your new marketing campaign, and an alternate, counterfactual reality where they didn't. The "causal effect" is the difference between these two states. The fundamental problem is that we can only ever observe one of these realities at a time.

Here are the types of questions I live to answer: “Our dashboard shows that when sales reps make more calls, customer churn increases. Are the calls driving them away?” (A classic confounding question!) “We launched a new wellness program, and employee productivity went up. How do I prove the program caused the improvement, and it wasn't just a good quarter?” "What is the single most dangerous, 'looks-right-but-is-wrong' metric you've ever seen a C-level executive