Michael Bagalman
Decision Science | Data Strategy | Executive Analytics
Most organizations are drowning in dashboards but starving for insight.
I operate at the intersection of statistical rigor and executive strategy. My work focuses on stripping away the "hype cycle" of AI to reveal the fundamental mechanics of decision-making. I don't just provide answers; I ensure you are asking the questions that actually matter to your bottom line.
From Chaos to Clarity: At STARZ, I architected the global subscription reporting system that integrates disparate data feeds from Apple, Amazon, and Roku. This single source of truth now powers the marketing and finance decisions for a multi-million subscriber business.
Why "tearing it down and rebuilding" is rarely the answer. A guide for executives on renovating legacy data stacks without halting the business.
Moving beyond the "fairy dust" of GenAI to understand the tactical shift in how users discover content.
When the factory turns the lights on, the experiments end. A look at the operationalization of AI in the coming year.
Prediction is cheap. Knowing what to do when the prediction is wrong is where the value lies.
I distrust "black box" solutions. If you cannot explain the model to the Board, you do not understand the risk.
The best data stack in the world cannot fix a company that is afraid of the truth.