Demand Forecasting is a systematic analytical process aiming to estimate the consumer demand for goods or services based on the past sales data. Demand plays a crucial role in decision making. In competitive market conditions, it is essential to make the right decision and plan for future events such as sales and production. The effectiveness of a decision taken by a business executive depends on the correctness of the decision taken.
It is a technique for estimating the possible demand for a product or a service in the future. It is based on the analysis of the past demand for that product and service in the current market conditions. We may think of it as an attempt to estimate the future demand after collecting past demand data from various aspects of the market.
Demand Forecasting decreases the risk regarding commercial operations and helps making effective decisions. Forecasting is even more critical now for companies engaged in mass production. A good estimate helps a company to make better planning for its business targets. A good estimate helps production planning, process selection, capacity planning, facility layout planning, inventory management, accurate pricing and defining advertisement strategies.
The scope of demand estimates depend on the current sphere of activity of the company and the future suggestions. If the sphere of activity is international, then the estimate may be made at international level. If the company is supplying its products and services in the local market, estimate will be made at the local level. The scope should be decided comparing time and money spent with the benefits of the information that will be gained through demand forecasting. The forecasting cost and the benefit flows should be balanced.
Demand Forecasting is generally performed via various software systems today. Thus, there are many important factors to consider while selecting the required software system. Generally, it would be better to use a fast, reliable product that can integrate smoothly with data sources, make reporting based on forecast analysis and machine learning methods. Therefore, analytical tools with the ability to forecast demand using machine learning classifications stand out as better options. As Consulta, we use such an advanced analytic tool named Alteryx. Alteryx is a data analysis program offering comprehensive self-service solutions for business data analysts. By setting machine learning models with Alteryx, we can forecast the demand with regression, decision tree, bayes, neural networks, randomForest, ARIMA and ETS.