The future is now for businesses as machine learning and predictive modeling take center stage in operations. Businesses should conduct time series forecasting to prepare for future events, allocating resources efficiently, staying agile and adaptive, and optimizing their team's time. Time series forecasting describes predictions made with historical data, providing valuable insights into trends and patterns. The most fundamental application is simple moving averages (SMAs), which can provide long-term trend forecasts using exponential smoothing. SMAs are useful for getting a clear picture of a metric's general trend but not for predicting exact future values. By applying time series forecasting techniques, businesses can make informed decisions, reduce errors, and increase profits.