Demand forecasting forms one of the crucial pillars in the working of a supply chain. For an organization to always have a profitable balance sheet, it employs a demand forecasting process to estimate & predict the customer’s buying behavior. In a more technical definition, this framework uses historical data with predictive analysis, which helps business management make better-informed decisions & ensure that the production always meets the market’s demands while keeping an enterprise on a revenue-generating roadmap.
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Steps in Demand Forecasting
These validated steps in the demand forecasting process help businesses optimize inventory & resources, allow better coordination amongst vertical stakeholders & improve customer experience leading to better brand value. So, here are the key steps involved in the demand forecasting process, which an organization must ensure to plan good production & execute operations even better.
The first & foremost specification to start with is to have clear objectives for which demand forecasting is to be done. The parameters could range from planning long-term or short-term demand, launching a product to a specific market segment, planning a fully-fledged unveiling, and gauging the organization's market share in the industry. These objectives help a company know the precise modus operandi, eventually leading them to better evaluate customer demands based on territories & market response to a new product.
The following step is to decide on the duration of the forecasting process. The tenure could be short (2-3 months) or a year-long period. Management has to ensure that the timeline decided very much regards the nature of the product. For instance, a demand forecasting procedure involving perishable items (such as foods and eateries) will have short-term forecasting, whereas solid commodities carry a long-term prospect. Such astute planning protects an enterprise from wasting its capital & subsequently avoids heavy investment in warehouses & inventory.
After setting the initial parameters of objectives & timeline, the next step is knowing the determinants which drive the demand. These factors are influential and directly affect whether the product will fare well in the market. These determinants range from the price of the good, which will be finalized, to the median income of the targeted group, the current customer behavior, the market trend, and potential user consumption, which directly affect the pricing points of the subjected good. An enterprise must have complete knowledge of the working determinants directly influencing its development to have near-accurate demand forecasting for a new product, especially long-term.
The initiation of the demand forecasting process starts based on the nature of the product. Broadly these methods are divided into two major categories: statistical & survey methods. A statistical form collects & organizes working data relevant to the product type and focuses on identifying trends that eventually help the forecasting groundwork. In contrast, a survey method relies on an opinion poll gauging the current pattern and tapping into the relevant human psyche, which drives the user’s purchasing behavior. Each method has its merit & it's up to the stakeholders to choose which way works best for them.
Post the finalization of the method, the following requirement is to gather pertinent data. This includes collecting both primary & secondary data. Primary data is classified as first-hand information not collected before, whereas secondary data is labelled as information already available. Having such a repository gives a company a starting point to plan out its product blueprint & prepare for both planning & execution.
With data helming the forecasting method, the eventual step is to estimate the demand for upcoming years from the product perspective. The managerial economics of an organization plus a product's run in the market enable the stakeholders to be flexible in their production and drive result-oriented decision-making. Most of the time, companies employing demand forecasting software have their estimates appear in an equation form whose results can be interpreted and presented in a comprehensible manner.
While the above steps in demand forecasting carry the entire approach to analyzing the product's potential run in the market, a few other nuances can be a deciding parameter too. From keeping a tab on competitors' activities to planning promotional campaigns for a new product launch – demand forecasting requires your organization to be a step ahead in scrutinizing what will work best for them.
3SC, with its artificial intelligence framework complemented by machine learning, provides analytical insights to help your business predict accurate product demand while helping outline the required resources from production to delivery. Side-lining inaccuracy to give you an edge in the market, 3SC, with its comprehensive demand forecasting process, drives your revenue towards the better half of the profit-loss statement.