Which mathematical algorithm first revolutionized retail demand forecasting in the 1980s, leading to the modern predictive analytics systems used in retail technology today?

The intersection of mathematics and retail has transformed how businesses understand customer behavior. Predictive analytics has become a cornerstone of retail technology, allowing companies to forecast trends, optimize inventory, and personalize marketing. But do you know which mathematical innovation first revolutionized retail forecasting? Test your knowledge about the historical development of mathematical models in retail technology!

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Exponential Smoothing Models developed by IBM for retail inventory management
Box-Jenkins ARIMA models adapted specifically for seasonal retail sales patterns
Neural Network systems created by MIT researchers for product recommendations
Bayesian Probability Networks designed by Walmart's early analytics team