Every business needs the ability to predict the future accurately in order to make better decisions and give the company a competitive advantage. With historical data, businesses can understand trends, make predictions of what might happen and when, and incorporate that information into their future plans, from product demand to inventory planning and staffing. If a forecast is too high, companies may over-invest in products and staff, which results in wasted investment. If the forecast is too low, companies may under-invest, which leads to a shortfall in raw materials and inventory, creating a poor customer experience.
Time series forecasting is a technique that predicts future time series data based on historical data. Time series forecasting is useful in multiple fields, including retail, finance, logistics, and healthcare. Demand forecasting uses historical time series data in order to make future estimations in relation to customer demand over a specific period and streamline

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