(SCM) involves the use of mathematical modeling, statistical analysis, and algorithmic solvers to optimize the millions of daily decisions—such as what to buy, where to move stock, and at what price—that drive global trade. By leveraging historical data and computational power, these methods aim to reduce subjectivity and improve the financial outcomes of supply chain operations. Core Quantitative Techniques
: Uses algorithms (e.g., linear programming, Branch-and-Bound) to find the most efficient use of resources. It is frequently applied to minimize total costs in network design and resource allocation.
: Extrapolates historical patterns using methods like moving averages, exponential smoothing, and ARIMA models.
Ensures supply chain decisions align with business profitability.