How to Implement Demand Forecasting in the Supply Chain using Python
Demand forecasting is an essential aspect of supply chain management. It involves predicting future demand for goods or services, which enables companies to make informed decisions about production, inventory, and distribution. In this article, we’ll explore how to implement demand forecasting in the supply chain using Python. We’ll cover different forecasting techniques and demonstrate how to use Python’s data analysis and machine learning libraries to build accurate demand forecasting models.
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Forecasting Techniques
Forecasting techniques are used to predict future demand based on historical data. There are several methods used in demand forecasting, including time-series forecasting, regression analysis, and machine learning.
Time-Series Forecasting
Time-series forecasting is a technique that uses past data to predict future demand. This method assumes that the future will follow the same pattern as the past. The most common time-series forecasting method is the Moving Average (MA)…
