Which forecasting approach would use past sales data to predict future sales trends?

The reasoning behind selecting time series forecasting lies in its methodology, which relies heavily on historical data to identify patterns and trends over a specified timeframe. This approach analyzes past sales figures to predict future performance, assuming that past behavior is indicative of future outcomes.

Time series forecasting involves collecting data points at consistent intervals over time, allowing for the identification of seasonality, cyclical behavior, and overall trends. By fitting a statistical model to this historical data, businesses can derive forecasts that help in planning and decision-making processes, especially in inventory management and demand planning.

In contrast, qualitative forecasting, market analysis, and competitive assessment involve more subjective techniques or external factors and may not solely rely on historical sales data. Qualitative forecasting often gathers opinions or insights from experts or market studies, while market analysis evaluates the broader market conditions and consumer behaviors, and competitive assessment focuses on the strengths and weaknesses of competitors. These methods may complement time series forecasting but do not specifically leverage past sales data for future predictions in the same direct way.