Demand forecasting in retail industry

How does demand forecasting help with decision-making in the retail industry?


How does demand forecasting help with decision-making in the retail industry?

How demand forecasting helps with decision-making in retail industry?

The main element to every thriving and evolving retail business is demand forecasting—one of the easiest methods to maximize profit and boost customer satisfaction. A retail industry’s main aim is to sell the goods or services directly to the consumer; therefore, it is crucial to focus on the most impactful ways to meet the consumer demands. 

What is demand forecasting, and how does demand forecasting contribute to growing retail business and consumer decision-making process? This article below will explain demand forecasting methods and how it helps the retail industry’s decision-making process.

1. What is a demand forecasting?

To understand what is demand forecasting is, first, we need to learn both words separately. Demand is a concept that refers to the eagerness of the consumer to buy a product or to use services at a specific price. Forecasting is an analytical process that uses existing data to predict future performance. Thus, demand forecasting in retail refers to developing a process of forecasting the future demand of products in the market during a specified period. The demand forecasting objectives are to help the retailers understand when the peak sales times will hit so that they can stock the inventory enough to satisfy the consumer’s demand and prepare them to handle the load.

2. What are the demand forecasting uses and techniques?

The need for demand forecasting is increasing day by day because the retail business is growing and its competitors. Forecasting can vary from one retailer to another according to their nature of the business, the products they sell, and the factors affecting their business.
To deal with such factors, two techniques have been developed to help the retailers forecast their business in the future — Qualitative and Quantitative Methods of demand forecasting.

  • Qualitative methods of demand forecasting

The qualitative forecasting method is a calculation methodology that practices expert opinions from different departments rather than the mathematical analysis method. 

It entirely relies on expert business consultant’s knowledge to shed light and provide insight into future outcomes. Qualitative forecasting helps the retail industry owners think open-mindedly according to the market demand without any numerical limitations. 

There are two common ways to carry out qualitative forecasting — Consumer Survey and Delphi method of demand forecasting.

In consumer surveys, the retailers perform the market study by design the questions polls to get a better insight of what the consumer needs and whether the products they are selling will hold a future in the presence of strong competitors or not. 

The Delphi method relies more on assumptions from a group of experts who contribute to the forecasting task. The suggestion can carry between five to twenty-panel members who have diverse experience in particular industries on which the forecasting is to be made. 

  • Quantitative methods of demand forecasting

The quantitative method is a statistical plan of forecasting that uses past numerical data to predict future events. The quantitative approach is considered one of the easiest ways of prediction because it is based on the underlying past information. 

Quantitative methods carry two types of analysis methods that predict the future — Time-series analysis and associative analysis.

In time-series analysis, it compares the past few year’s data to get the pattern and a clear sense of whether the product has grown or not.

For example, a small retailer deals in the socks business for three years and wants to forecast the 2021 business plan. He could use the last two years, i.e., 2019 and 2020 moving average. If in 2019 there were 2000 pairs of socks sale and in 2020 it grows to 4000 pairs of socks, then in 2021 the sale could get in between 5000–6000 pairs. 

The associative analysis collects the several period’s data based on the historical relationship between independent and dependent variables. The associative analysis is a collective data research method, time analysis, and market research to have forecast results. It generally takes several months to get the result.


Forecasting is half an art and half-mathematical solution that addresses the problem and provides valuable information for future business. Demand forecasting involves a lot of time and effort. If the demand forecast is inaccurate, it involves a considerable risk and can crush the business in no time. Therefore it is necessary to have pieces of accurate information’s to get help the business flourish. It is advisable to invest in forecasting software to reduce the hours and efforts on manual data collections.