How Demand Forecasting Is Helping the Retail Industry?

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How Demand Forecasting Is Helping the Retail Industry?

Forecasting is the process of analyzing existing data to determine future events. In the retail sector, forecasting is used to understand the customers’ purchase behavior.

Actual data that is in existence and its related market research might differ by the kinds of products a retailer usually intends to trade for, but the basic denotation of forecasting in retail accompanies similar patterns, even across different product lines.

Demand forecasting is one of the major aspects of running a successful retail business. A retailer cannot accurately predict and prepare for the changing market conditions and customers’ requirements without demand forecasting. And one such indispensable component is demand forecasting. 

Put separately, demand describes the eagerness of consumers to purchase a specific product, whereas, forecasting predicts future performances by utilizing statistics of the pre-existing data. 

Hence, demand forecasting in retail is the insightful prediction of consumers’ purchase actions regarding a specific product, at a specific price and in a specific time area. 

Simply, it is the demand forecasting of future bids that lead the businesses to create a win-win situation for consumers and themselves.

Many small and big companies implement demand forecasting for supply chain control, financial planning, and customer success management. This strategy allows businesses to prevent any sort of loss and ensures client retention while making any necessary and sudden changes.

Without proper implementation of demand forecasting techniques, businesses might find it hard to possess an adequate amount of stocks in hand. Especially, in the COVID times where physical interaction has come to a halt and companies are making rapid changes to their working models.  

It plays a significant role in the growth and survival of the retail market. 

Importance of Demand Forecasting in Retail

Here are the two major points that define the importance of demand forecasting:

1) Cost-efficient

One of the simplest ways to maximize profit in the retail business is to cut down costs.

Initially, you can diminish the amount of money you have invested in unnecessary inventory. That will result in lower carrying costs since you have lesser stock in hand. Plus, this also ensures that you don’t go out-of-stock and capitalize on every sale you make.

While the above ways do work, a systematic approach towards the need for demand forecasting ensures to beef up the profits and business structure. Once you forecast the demand, you can easily have a look over the time period and check if you are close to hitting the anticipated sales. 

If you were left behind on your goals, you can always use marketing and advertising techniques. And, in case you underestimated, you can reorder the stuff and cross-promote a similar product. 

2) Customer Experience

Suppose you visited an e-commerce site to purchase groceries and essentials for your home. Unfortunately, the brand you prefer is currently out of stock. 

What will be your next move? Will you wait for the brand to restock them and then proceed to make a purchase? Or, will you look for another brand that offers similar items? 

The latter, right? 

Enhancing the customer experience is the quickest way to improve profits. Neglecting the “out-of-stock” from your business can retain your consumers and will stop them to entertain your competitors. 

Plus, aiming towards the end-users might lead to more referrals and loyalty, rather than focusing on raising the prices, altogether. 

What Are the Advantages of Demand Forecasting in Retail?

It is necessary to perform demand forecasting in a proper way to stay in the retail industry game. Forecasting may not be easier for both brick and mortar and giant companies, however, the results-driven by it can make a huge impact. 

Here are the advantages of demand forecasting:

1) Better Financial Planning

The demand forecasting formula is used to help you achieve better and smarter financial planning for your retail business. Detailed and accurate information obtained from the forecasting lets retail companies build better financial plans. 

Accurate predictions can easily highlight the peak intervals, demand trends followed by months, dates, or even a specific time of the day, and seasonality. Hence, making it easier for companies to look upon the cash flow and safeguard themselves from peaks and unexpected expenses. 

2) Eliminates Staffing Problems

A well-structured demand forecasting process can result in preventing staffing problems in companies. These issues generally arise during the peak season. It can be easily avoided by anticipating the hike and fall in the demand during different time intervals or days. 

This way, companies can eliminate the guessing and come up with a more structured schedule list. Moreover, managers can also plan the shifts accordingly for the workers. 

3) Enriches the Marketing Plans

Forecasting also plays a vital role in developing effective marketing campaigns. For instance, if a company experiences a loss in sales, it is advisable to put effort into its marketing strategies. 

With proper demand forecasting solutions, marketing executives can develop properly tailored marketing promotions that can take on the loss. Moreover, making modifications to the pricing index according to the customers can also make an impression. 

Get Started with Demand Planning for your Retail Business

4) Advanced Inventory Management

Not only the inventory but forecasting also helps the companies willing to enhance their production management. Companies strive for inventory overflow whenever their product goes out of stock or sales fall down in peak times. 

Precise forecasting allows them to anticipate and adapt the situation to meet the required demands accordingly. In addition, it also ensures that the company holds the required material, shipping, and labor. 

What Are the Reasons to Use Demand Forecasting in Retail?

The biggest benefit reason to use demand forecasting is to reduce uncertainty in retail operations. Demand forecasting kills uncertainty, substantially, with its predicted calculations and thus, allows retailers to order, allocate, and refill accordingly. 

Additionally, it is also beneficial in terms of workforce scheduling and optimizing capacity management systems

Benefits of Demand Forecasting

Here is the list of benefits driven by demand forecasting:

  • Better product availability results in increased sales 
  • Improved supply chain 
  • Increased inventory turnover since there is a lesser need for safety stock 
  • Better and improved budgeting plans incorporating cash flow, marketing, labor, and more 
  • Cuts down personnel costs using shift optimization tactic 
  • Improved overall margins 
Benefits of Demand Forecasting
Benefits of Demand Forecasting

How Is Demand Forecasting Performed?

Demand forecasting relies on 3 main models that are used in the retail industry. However, each model might possess some flaws since predicting the future can be imprecise. Yet, these models might give you the best possible consumer demand predictions. 

The most precise way of performing demand forecasting accurately is by practicing both internal and external metrics. 

Internal data incorporates the historical sales, time spent on advertisements, and traffic on foot or website. Whereas, the external metrics include industry trends, competitors, industry evolution, etc.

Top brands are already using demand forecasting to increase sales and profits. However, not all small retailers are aware of this concept. Lack of access to resources and knowledge about demand forecasting is another issue. That said, you can always take the first step by contacting the experts in the industry.   

Models of Demand Forecasting

Here are the three models of demand forecasting:

1) Qualitative Forecasting Model

This model is based on qualitative data. Its sources include industry experts, employees, consultants, consumer groups, competitive analysis, and more. This data is often based on intuitions, rather than on factual information and research statistics. 

This type of model is best suited for retail businesses that do not possess any previous or historical data. For example, companies that launch a new product, the drastic time difference between prior and planned period, etc.

2) Causal Model

This model accounts for demand forecasting that may change the initially forecasted demand. In this causal model, data is split into two different factors i.e. controllable and uncontrollable factors. 

Controllable demand factors include marketing efforts, location, pricing, sales, and visual merchandise. Whereas, the uncontrollable demand factors include weather, politics, competitors, natural calamity, and more. 

This model is considered to be a little complex since it acquires a good number of variables to look upon. In addition to that, factors like weather and natural calamity are hard to predict accurately, require guesswork and trust factor in one’s intuition. 

With that said, this type of model is best suited for retailers in the volatile market, multi-channel businesses, data-driven retailers with a lot of metrics over time. 

3) Time Series Analysis

The time series analysis holds more of a quantitative data approach. This model is often considered rigid and depends on a mathematical approach rather than experts’ opinions. 

To utilize this forecasting model, retailers must possess some historical data such as best-selling items, sales numbers, pricing changes, and more.  

Other methods include:

  • Trend analysis 
  • Graphical methods 
  • Seasonal adjustments 
  • Life cycle modeling 

Time series analysis is recommended for retailers that contain a sufficient amount of past sales data, seasonal items, and cyclical sales trends. 

Types of Demand Forecasting

The following are the common types of demand forecasting-

Active Demand Forecasting 

This type is suitable for startups and businesses in the growing phase. It uses market research and external factors to determine customer demand for the products. 

Passive Demand Forecasting

As the name suggests, passive demand forecasting involves the use of historical/ past data to predict future demand for a product. Businesses that are already in the market for a long time and have enough historical data use this method. 

Long Term Projections 

This involves forecasting the demand for more than a year. It can extend up to four years. Long term projections are considered more as roadmaps to expand the business as the market conditions can change anytime. Market research and sales data are used for long term projections.

Short Term Projections

Short term projections are limited to forecasting the demand for the next three months or the upcoming quarter. Real-time sales data is used to get a comprehensive idea about whether a product would be in demand or go out of demand during the coming months. 

External Macro Forecasting 

We know how external factors can influence demand and sales. This type of demand forecasting focuses on such external and uncontrollable aspects to prepare and streamline the supply chain in advance. 

Internal Micro Forecasting 

The more control you have over your business operations, the better will be the returns. Internal micro forecasting takes care of this by reviewing the day-to-day operations and identifying areas for improvement. 

Demand Forecasting Techniques
Demand Forecasting Techniques

How to Avoid Common Demand Forecasting Pitfalls?

Demand forecasting has the potential to bring wonders if done correctly. However, it can also sink your business and take up a good number of bucks when done with a casual approach. 

Below is the list that comprises the most common pitfalls and mistakes made in demand forecasting: 

1) Exaggerated Sales

Overestimating sales figures might feel like being on the safer side as it prevents underspending. But, it can result in capital losses which can hamper long-term opportunities. 

2) Avoiding Previous Data

Keeping the historical data handy, while building plans and projections, is essential. It is necessary to utilize previous data for future forecasting and plan the predictions on prior results. 

3) Depending on Predictions Only

Following decisions that are merely based on predictions is the wrong way to approach a business. Aspects such as sales forecasting reports are only estimates but still, they should be kept at a certain level and revolve around data or facts and appear realistic. 

4) Inadequate Flexibility

An effective sales plan and budget are made considering the abrupt changes. Regardless, developing one is not an easy task. However, enabling flexibility in forecasting might provide you the possibility of avoiding unpredictable circumstances. 

5) Using Various Spreadsheets

Using traditional ways to handle the data is not a smart choice. Manually entering data and calculations is a straight call to human errors. The ideal way of forecasting and budgeting is to automate and streamline processes using software that is made to save time and effort.

6) Not Modernizing Forecasts Frequently 

It is necessary to update and refine the pre-existing data even if the managers or supervisors are confident about it. It is important to provide up-to-date and most accurate information. 

How to Choose the Right Demand Forecasting Software

There is a wide variety of demand planning software in the market that works well. However, there are several things to notice while choosing the right fit for yourself and that is:

  • Initially, make sure that the software is AI-powered and can handle the internal and external data sources. 
  • You need to provide enough relevant data to the demand planning software if you aim for a good forecast result. 
  • The software must be AI-driven since the data required to make predictions is too complex for humans to operate. 
  • The software must provide a clear picture of how it calculated the forecast to support the long and short-term planning goals. 
  • It must possess a fast, reliable, and modern database since retailers end up generating huge amounts of sales data on a daily basis. 

Some of the demand planning software are as follows:

  • SAP Integrated Business Planning 
  • Demand Planning 
  • Logility Solutions 
  • StockIQ
  • Forecast Pro


Demand forecasting is one of the essential elements of the retail industry. Suppose, you have an X number of products in your warehouse and the demand falls down to less than that. 

That is where the possibility of experiencing the loss comes into the business. 

Similarly, the demand can rise as well, and not having enough products at that time can build up the same situation. 

Know more about our AI Driven Solutions for Demand Forecasting

Demand forecasting is a way to manage the volatile market. It helps you to be fully prepared to handle the increase and decrease in demand for products in the near future. It is a sure way to minimize the risk of loss and increase returns by making most of the market opportunities. Demand forecasting software streamlines the retail operations and increases business accuracy. The right time to invest in demand forecasting is now. 

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