"Demand forecasting" refers to the process of estimating future demand for products or services based on historical data, trends, market analysis, and other relevant factors. Accurate demand forecasting is crucial for businesses to optimize their production and procurement planning, manage inventory levels, control operating costs, and better meet customer needs.
Typical functions of software in the "demand forecasting" domain are:
Data analysis and preprocessing: The software allows for the analysis and preprocessing of historical sales data, customer orders, inventory levels, and other relevant data sources to identify trends, patterns, and seasonal fluctuations.
Statistical models and algorithms: It provides a selection of statistical models and algorithms for predicting future demand, including simple methods such as moving averages and exponential smoothing, as well as more complex methods such as ARIMA (Auto-Regressive Integrated Moving Average) and machine learning.
Automated forecast generation: The software enables the automated generation of demand forecasts based on the selected models and parameters, saving users time and allowing for quicker decision-making.
Validation and adjustment of forecast models: Users can validate the accuracy and reliability of the generated forecast models by comparing them to actual data and making adjustments as needed.
Real-time updating: The software offers the capability to update forecast models in real-time to respond to changing market conditions, new data, and unforeseen events.
Visualization and reporting: It allows for the visualization of forecasted data through charts, graphs, and dashboards, as well as the creation of reports for analysis and communication of results.