A sales rep once shared with me a moment that changed the way he thought about strategy. He noticed one product was selling unusually well in one neighborhood but not in another same price, same promotions, same inventory. Instead of overthinking it, he visited both stores. In the high-performing one, the product was next to the checkout counter; in the other, it was tucked behind cleaning supplies. A simple placement difference explained a 40% gap in weekly sales. No workshop, no stakeholder interviews, no grand theory, just observation. And MIT research backs this up: companies that ground decisions in real data instead of assumptions are 5% more productive and 6% more profitable.
That’s the heart of data science in business: theory can suggest possibilities, but data real-world, messy, on-the-ground data reveals what actually drives results. While traditional strategy is great at building frameworks and gathering perspectives, data-driven action picks up the signals that matter: behavioral patterns, anomalies, trends, operational friction. This is why McKinsey reports that data-driven companies are 23 times more likely to acquire customers and 19 times more likely to remain profitable.
Data-driven companies are 23 times more likely to acquire customers and 19 times more likely to remain profitable.
Strategy stops being guesswork when it stops being abstract. In the end, you don’t need better opinions; you need better observations.
