Concavity and Network Flow in Profit Optimization: How Diminishing Returns Enable Efficient Solutions

Understanding why retail revenue functions are concave, how this property enables convex optimization, and the network flow interpretation that powers modern markdown pricing algorithms

Cyril NoirotMay 15, 20257 min read

Cyril Noirot

Analytics consultant specializing in marketing science, forecasting, and strategic data solutions. Passionate about bridging the gap between advanced analytics and business impact.

Data Science

From lifecycle limits to markdown rules: The product constraints behind retail profit optimization

Why retailers can't escape markdown pricing—a deep dive into the lifecycle, inventory, and pricing constraints that shape modern retail optimization strategies

May 156 min

Data Science

Inside the profit optimization problem: From price uncertainty to prescriptive decision-making

How retailers transform predictive demand models into prescriptive pricing decisions through stochastic programming, jointly optimizing markdown prices and inventory allocation under uncertainty

May 15 min

Data Science

Why price elasticity is the most difficult parameter to estimate in retail analytics

A deep dive into why measuring price elasticity remains the biggest challenge in demand modeling, from data scarcity and endogeneity to seasonal confounding—and how modern techniques address these challenges

Apr 186 min

Cyril Noirot

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From lifecycle limits to markdown rules: The product constraints behind retail profit optimization

Inside the profit optimization problem: From price uncertainty to prescriptive decision-making

Why price elasticity is the most difficult parameter to estimate in retail analytics