Writing on how decisions get modeled, built, and deployed.
Les échecs de GenAI en entreprise ne sont pas technologiques — ils révèlent des inadéquations structurelles entre organisation existante et nouvelles capacités. Comment décider si et comment investir.
Most companies are not ready for autonomous commerce agents. The practical starting point is Agentic RAG: systems that retrieve business context, reason over it, and produce decision-ready outputs.
Two initiatives can show the same ROI and still deserve very different decisions. The missing variable is time-to-ROI: how fast the initial investment is recovered.
Sales volume mixes demand and inventory effects. Sell-through rate captures what actually matters: how fast inventory clears under pricing and context constraints.
Most CRM organizations don't have a feedback loop. They have a broadcasting system. The shift from propensity to uplift modeling changes everything.
Pourquoi le forecast de lancement produit est souvent un exercice politique plus qu'une estimation robuste, et comment le transformer en système probabiliste et explicable.
Revenue is a derived quantity. Marketing influences demand, units sold, not price. Modeling revenue directly entangles two mechanisms and produces misleading attribution.
A comprehensive guide to deploying production-ready Marketing Mix Models—covering data ingestion, model training, cloud deployment, and real-time optimization APIs for budget allocation
Deep dive into gradient boosting trees with quantile regression for robust uncertainty estimation in travel retail forecasting.
Interactive tools and calculators for practitioners — built to explore ideas, not to sell software.
Available for consulting engagements in forecasting, pricing, and decision systems. More about me