Examples of Demand Forecasting

examples of demand forecasting

Demand Forecasting Examples

The term demand forecasting refers to the process of using historical sales data to predict future customer demand. Demand forecasting influences a wide variety of business operations including-

  • Supply chain management
  • Inventory control
  • Decision making
  • Capacity planning
  • Cash flow forecasting
  • Inventory management
  • Sales forecasts
  • Warehouse management
  • Market research
  • Financial planning
  • Inventory planning
There are many different forecasting techniques available for business professionals to use. Some businesses choose to use a combination of different forecasting types including-

  • Trend projection forecasting method
  • Econometric forecasting model
  • Barometric forecasting technique
  • The market research forecasting process
  • Delphi forecasting method
An accurate demand forecast helps a wide range of business professionals, from small business owners to sales teams staff members, to make informed decisions and increase sales. Businesses may struggle to figure out which demand forecasting models are the most appropriate for their business's needs and objectives. To better understand what the forecasting process actually entails reference case studies and theoretical examples.

Real-world demand forecasting examples might look like-

Example 1

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A food manufacturing industry business wants to predict future sales for new products they recently developed. Due to a lack of historical data available, the company decides to undertake market research initiatives to better understand how consumers will react to their new products and identify any significant issues that each new product contains.

Business leaders at the food manufacturing company decided to independently research case studies that referenced the new product type. While obtaining expert opinions on one of their new product designs, they made suggested improvements which resulted in increased customer demand estimations.

The business found an effective way to use data gathered during their market research to develop a more accurate sales forecast method. Their demand forecasting informed them on their supply chain management and inventory planning for the new products to successfully transition into the market.

Example 2

An e-commerce cosmetics brand has developed a solid fan base and wants to make informed decisions about potentially opening a small business storefront. The business owner does not feel comfortable with her financial planning skills but does want to better understand her own customers so she decides to perform a demand forecast.

Factoring in her sales data and planned promotions, she realizes that fulfilling future sales at the same rate may be a problem due to the supply chain and current vendors she contracts with. As she is known for her amazing customer service and fast shipping speeds, she applies the information from her demand forecast to assist with supply chain management and inventory planning processes.

She decides to open her storefront in two years so that she can build her bottom line profitability and gather more data on sales trends and the life cycle of her products. In the short term she will redirect her cash flow towards building her brand in order to build long term customer loyalty.

After two years of using demand forecasting methods she feels confident enough in her financial planning skills to transition her ecommerce business into a small business storefront in a larger, more profitable location than she originally intended.

Due to the massive success and outstanding brand reputation she built in her ecommerce business over the past two years she knows that her cash flow will keep her stable even if the small business location hits snags.

Example 3

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For the last two years, a small business owned by an older couple has been the only local option for holiday meal supplies. The grocery small business has enjoyed the luxury of being able to price items at their discretion as their geographical location is not easily accessible for an eCommerce business to deliver to.

However, a large chain grocery store recently opened in their area that offers lower prices on many items that they carry. The grocery small business owners are unsure about how the competition will affect their customer demand or future sales potential.

Using historical data alone, the business would not likely make any adjustments to their marketing strategy. However, after performing a combination of demand forecasting methods they decide to make some changes.

With a low cash flow due to stocking their inventory levels abundantly in anticipation of the holiday season, the business is unsure how to make their short term demand increase. They research some case studies they find online and meet with a small business owner in their area for advice.

The small business decides on offering extra discounts to customers for a short time period and their Thanksgiving sales exceed their original projections. As a result, they decide to develop a customer loyalty program that even further increases long term customer retention.

Key Takeaways

  • Demand forecasting is a crucial part of sales forecasting and demand planning initiatives. A demand forecast is used to predict future customer demand based on historical sales data.
  • Various demand forecasting process types include the market research forecasting technique and the Delphi forecasting method.
  • Accurate forecasts help with a wide range of operations from making crucial business decisions to developing inventory management techniques.

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