Machine Learning in Demand Forecasting
Demand Forecasting is an area of predictive analytics whose task is to predict the demand for the company’s products and services for production planning, developing marketing strategies, and making decisions about the market launch of new products. Demand forecasting includes analysis of historical sales data as well as statistical methods. In business, Demand Forecasting gives us an estimate of the number of goods and services that the customers will likely purchase in the future.
There are different ways to do demand forecasting. Based on the forecasting model you use, your forecast may differ. The most successful practice is to do multiple demand forecasts. Using more than one forecasting model can show differences in predictions, and they can point to a need for more research or better data inputs.
Types of demand forecasting:
- Macro-Micro level
- Short-term
- Long-term
- Active Demand Forecasting
- Passive Demand Forecasting
Methods of Demand Forecasting:
- Qualitative Methods
- Quantitative Methods
Demand forecasting helps drive smart business decisions. With customer expectations changing faster than ever, It doesn’t matter whether you choose simple or more complex methods. Without a deep understanding of demand, businesses cannot make the right decisions about marketing spend, production, staffing, and more.
Our full article could be helpful if you’re looking for a fulfillment solution to help you improve demand forecasting.
https://jelvix.com/blog/demand-forecasting-methods-machine-learning
