In this episode, we explore forecast reconciliation—why store-, region-, and national-level forecasts often misalign and how to fix them with Mint. We'll cover the math behind minimizing forecast error variance, how to estimate the covariance matrix from historical residuals, and compare traditional bottom-up/top-down/middle-out approaches. We’ll also discuss ERM as a robust alternative and share real-world retail and manufacturing case studies highlighting the operational benefits.

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