Which forecasting technique uses historical data to predict future demand?

Time series analysis is a forecasting technique that relies on historical data to make predictions about future demand. This method works by examining patterns and trends within a sequence of data points collected over time. By analyzing these historical patterns, such as seasonal variations, cyclical trends, and moving averages, time series analysis allows organizations to identify consistent trends that can help forecast future demand with greater accuracy.

The effectiveness of time series analysis lies in its ability to leverage established data patterns without the introduction of outside factors, which is often the case in other forecasting methods. It is particularly useful when historical data is abundant and reflects the same influencing factors expected in future periods. This makes it a preferred choice for industries or businesses with stable demand patterns over time, where past behavior can be a reliable indicator of future performance.