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The Ultimate Guide to Demand Forecasting in Retail Industry
We are living in exceptional times where a global pandemic has resulted in the disruption of supply chains across the globe. With the economy being artificially inflated as a result of the increasingly questionable quantitative easing by the federal reserve and unemployment rates hitting pre-pandemic levels despite a major labor shortage in the US has everyone stumped. The stress on the supply chain is evident by the fact that most companies in the world are somewhat demand-constrained right now. Gaming consoles are being flipped on Ebay by scalpers for twice the MSRP(s) and cars are lying in parking lots waiting for electronic component fittings. Everything can be attributed to a single issue, improper demand forecasting. No one had anticipated the retail industry bouncing back so soon after a complete shutdown back in 2020. An effective way to become profitable in the highly-competitive retail industry is by doing accurate demand forecasting. Many retailers have failed and many will continue to fail because of their inability to forecast customer demand well. Demand for products can be driven by seasonality, random weather events, or even social media. In today's retail environment, demand forecasting is at the heart of every advanced retail analytics solution, and accuracy is critical to the survival of most retailers. With this guide, you will gain important insights into how demand forecasting in the retail world works.
What is demand forecasting and why is it important for retailers?
Demand forecasting is the process of predicting future consumer demand for a product or service at a specific price within a specific time frame using statistical methods. This information is important for retailers because it allows them to plan inventory and pricing strategies accordingly. There are multiple methods for forecasting demand. Some of the most popular methods include market research, simulation, extrapolation, and vicinity models. The inability of the retailers to accurately forecast demand and optimize supply chains accordingly has led to them losing a ton of business to retailers like Amazon. Demand forecasting is central to profitability and the overall customer experience that a retailer provides. There are different types of demand forecasting, each with its own strengths and weaknesses. The most common types of demand forecasting are:
- Passive Demand Forecasting
- Active Demand Forecasting
- Short-term Demand Forecasting
- Long-term Demand Forecasting
- Macro & Micro Demand Forecasting
- Internal Demand Forecasting
Benefits of Accurate Demand Forecasting
Demand forecasting is one of the most underappreciated profit-boosting tactics. Accurate forecasting will assist your company in a variety of ways, all of which will enhance your bottom line. Accurate demand forecasting can help your business navigate through tough times. Here are some of the benefits of accurate demand forecasting:
- It can help retailers in adapting to seasonal trends, stock-outs, and adjusting supply based on the demand at different stages in the product life cycle.
- It enables the optimization of staffing requirements and shift timings to ensure maximum productivity within the organization.
- It allows the retailer to create optimal financial plans for the future to ensure positive cash flows and maximum profitability.
- Anticipating customer demand can help create great in-house private label brands to maximize profitability exactly like how Amazon and Costco have done with Amazon basics and Kirkland signature respectively.
- It allows for efficient supply chain management which can alleviate stress and help the business get through tough times.
- An optimized customer experience ensures customer satisfaction which ultimately leads to a lower churn rate.
How is demand forecasting done?
It involves assessing current and past market conditions, industry standards and regulations, and the economic situation in the country where the product will be sold. This information is used to create a demand curve (also known as an aggregate demand curve or market demand curve) that predicts the number of units of a particular good that will be demanded at various prices in the future. An essential component of forecasting is being able to assess the reliability of the data used for making predictions. Here are some of the primary methods used to predict the retail demand accurately:
- Statistical Methods
- Market Research
- Delphi Method
- Analyzing Macro and Micro Economic Environments
What are the limitations of statistical demand forecasting?
Statistical demand forecasting is limited in its ability to predict future demand because it relies on historical data that may not be indicative of future trends. Newer methods employ the use of machine learning algorithms to forecast demand. A new machine learning algorithm developed by IBM forecasts real-time demand based on social media posts and other online activity, offering businesses insights into how much they can sell their products for. The new tool, called Smart Demand, is trained using data from mobile phone companies and uses a novel technology called geolocation to identify people’s location based on their online activity. It then predicts future consumer behavior by applying past consumer patterns and social science research. Such tools are at the forefront of the digital transformation for retailers. Shopify, which allows millions of retailers to sell their products online, has such functionalities built into their merchant app.
How Atidan Technologies Can Help You Accurately Forecast The Demand for Your Products and Services
Atidan specializes in helping your business realize its true potential with the help of the latest technologies to make sure that you come out ahead. With decades of experience and a tremendously powerful platform, our goal is to help you realize the full potential of today's cutting-edge technologies. With a presence in over 14 countries, We have software engineers that can help you maximize your technology investments and bring new efficiencies to your business. With access to Atidan’s premium staffing services, you can hire vetted statisticians and machine learning engineers that can improve the productivity of your business. Our team of developers, architects, and specialists bring a diverse array of technology frameworks and a rock-solid approach to ensure your application works seamlessly. In addition, Atidan’s expert consultants will work actively with your business process managers, IT staff, and executive leadership to identify your requirements and help you reach your business goals.
