Demand forecasting is a detailed process that goes down to various algorithms that determine and shape demand. More importantly, it can indicate how to put in effective strategies to maximize accuracy. Sometimes also called material forecasting, the process of supply chain forecasting primarily involves recognizing a need for items and communicating it to the proper supplier. There are several methods of demand forecasting applied in terms of the purpose of forecasting, data required, data availability and the time frame within which the demand is to be forecasted.
Intelligent modeling accurately predicts future customer demand and allows for management overrides, all avoiding the costly mismatch of demand and supply. However, that does present the challenge of integrating local market factors into your centralized demand forecasting process. While statistical demand forecasting provides a more sophisticated method of predicting future demand, it does have several prerequisites in order to produce good results.
Fundamental analysis is the process of collecting supply and demand data to establish whether a market is in deficit, equilibrium or oversupply. When forecasting in a demand driven supply model, it is important that your organization focus on channel modeling, use downstream data and do everything possible to reduce latency. Likewise, people measure your organization and its growth by sales, and your sales forecast sets the standard for expenses, profits and growth.
The level of visibility by a customer when an operation is performed, normally when services are performed, is important – you cannot separate a person from the service being provided to them. It is significant from managerial viewpoint as it helps the management in decision-making with regard to your organization’s demand and production. Orchestrating demand at the mature stage of the demand-driven transformation allows organizations to better balance growth and efficiency, cost and customer service, and demand fluctuations.
For example, the extent organizations decide to invest can be predicted by forecasting future demand and by comparing it with present production capacity. An increase of consumption may induce new investment, and the process of estimating the future demand of product in terms of a unit or monetary value is referred to as demand forecasting. Further, some models enable decision makers to estimate future sales based on information collected from sales representatives.
Fulfilling a key objective for economic stability through the reliable supply of cash, forecasting demand is essentially the process whereby predictive analytics are employed to try to understand and predict customer demand for a business so that supply decisions by corporate supply chain and business management can be optimized. Hence, organizations can base forecasts on past sales data, industry-wide comparisons, and economic trends.
Demand forecasting in the lodging industry, for example, has become relatively important because of the nature of the industry and its operational characteristics and difficulties. Accurate forecasting can help you validate the business case for a new product or service and help you build trust among future investors and partners. Through forecasting, your organization can estimate the forces that have a bearing on future production, demand planning, financial operations, and marketing operations.
However, business forecasting is often done poorly, and is frequently confused with planning and goals. Your business must use the information you get from estimation and forecasting to plan production and inventory correspondingly. Thus, business forecasting refers to a tool that helps your organization make decisions in what concerns planning, budgeting, and seeing future growth.
Want to check how your Demand Forecasting Processes are performing? You don’t know what you don’t know. Find out with our Demand Forecasting Self Assessment Toolkit: