Learn Demand Forecasting and Pricing in Excel
Demand Forecasting based on Public Information
Demand forecasting is known as the process of making future estimations in relation to customer demand over a specific period. Generally, demand forecasting will consider historical data and other analytical information to produce the most accurate predictions.
More specifically, the methods of demand forecasting entails using predictive analytics of historical data to understand and predict customer demand in order to understand key economic conditions and assist in making crucial supply decisions to optimise business profitability.
Follow Up Video Guides on Demand Forecasting and Pricing
- Demand Forecasting and Pricing Part 2
- Demand Forecasting and Pricing Part 3
- Demand Forecasting and Pricing Part 4
Demand Forecasting Methods are divided into two major categories :
- Qualitative methods – These are based on expert opinion and information gathered from the field. It is mostly used in situations when there is minimal data available to analyse. For example, when a business or product is newly being introduced to the market.
- Quantitative Methods – Quantitative Methods use data, and analytical tools in order to create predictions. Demand forecasting may be used in production planning, inventory management, and at times in assessing future capacity requirements, or in making decisions on whether to enter a new market.
Demand forecasting Role in Business
It plays an important role For businesses in different industries, particularly in reducing risk in business activities. However, it is known to be a challenge that companies face due to the intricacies of analysis, specifically quantitative analysis. Yet, understanding customer needs is an indispensable part of any industry, so that business plans can be implemented more efficiently and can more appropriately respond to market needs.
If businesses begin to master the concept of demand forecasting, it can result in several benefits. These include, but are not limited to, waste reduction, more optimal allocation of resources and potentially dramatic increases in sales and revenue.
