Data Science

Why Demand Forecasting is Crucial for Companies

Demand forecasting helps companies predict the future demand for products or services.


How much inventory is in stock? How often does it need to be restocked? How will demand change over the next few months? If one can't answer such questions clearly, this article is a must-read. Learn why demand forecasting is important for any business – and how companies can use demand forecasting to gain a competitive edge.

What Is Demand Forecasting?

Demand forecasting helps companies predict the future demand for products or services. These forecasts are usually based on historical data to estimate how many products or services can be sold on the market in a defined period. This helps companies make better business decisions – for example, to optimize planning, production, and inventory (and hence minimize risks such as over- or underproduction). “The goal of forecasting is not to predict the future but to tell you what you need to know to take meaningful action in the present.” - Paul Saffo, Silicon Valley-based forecaster

Why Is Demand Forecasting So Important?

Demand forecasts are vital for any business. After all, only with a correct understanding of demand, informed decisions can be made – whether it's production, marketing expenditures, or personnel deployment – and ensure that market needs can be met. Let's assume we are a retailer. Only if we know how many of which items will be in demand over the next few weeks can we order the exact quantity needed. Whether ordering raw materials, production planning, or pricing: Only those who know demand can make informed decisions.

Here are 4 benefits of demand forecasting at a glance:

1) Efficient Logistics
With a calculated demand, logistic processes can be optimized. For example, one can avoid bottlenecks and excessive storage costs and perfectly adjust the capacity of the warehouse to the demand.

2) Capacity Planning
Whether raw materials, employees, or machines: With a demand forecast one can plan capacities more efficiently – and even save personnel costs by adjusting employee shifts to demand.

3) Production Planning
We can also use demand forecasts to better match production to demand (and avoid over- or under-production, for example). Especially in the food industry, products can spoil quickly if demand is too low.

4) Customer Satisfaction
By planning demand better, companies can improve their delivery times and the quality of delivery. This boosts customer satisfaction and increases customer loyalty. And all of this leads to? Correct, higher sales! By having products available at all times and saving costs in production and storage, sales and turnover can be increased.

What Are The Forecasting Methods?

Demand forecasts are usually designed based on historical data. The first step, therefore, involves collecting historical data, which is then processed and cleaned. Once the data has been collected and processed, a mathematical model ("machine learning") is trained. This can then calculate the future development of demand. A basic distinction is made between qualitative and quantitative demand forecasting:

Quantitative Forecasting
Quantitative demand forecasting is the most precise forecasting method. Here, one uses objective metrics that can be derived from historical data and statistical analysis – and methods such as regression, time series analysis, artificial intelligence (AI), and machine learning (ML).

Qualitative Forecasting
Qualitative forecasting is based on subjective metrics such as customer opinions and market trends. These demand forecasts are less accurate and are usually only used when there isn't enough historical data. On the other hand, qualitative forecasts are faster and cheaper to implement.

3 Popular Companies That Are Using Demand Forecasts

The biggest online retailer in the world uses demand forecasting extensively. For example, Amazon relies on machine learning models and other analytics tools to analyze demand for products in real-time and fulfill orders. The company also uses demand forecasting to optimize inventory management. This allows Amazon to ensure that there's always enough merchandise in stock to fulfill customer requests quickly and efficiently.

Coca-Cola uses demand forecasting to analyze demand in different regions and markets. This enables the company to more effectively plan the production of its beverages and make decisions about adjusting production capacity. In addition, Coca-Cola uses demand forecasting to optimize production and delivery costs through optimal transportation and warehousing strategies.

Walmart is one of the largest retailers in the world. The company uses demand forecasting to optimize inventory levels in over 1100 stores in 27 countries. To do this, Walmart relies heavily on analytical tools and technologies to effectively manage order quantity and inventory levels. In this way, Walmart optimizes the supply chain, avoids bottlenecks, generates more sales, and increases its profitability.


Whether planning inventory or optimizing the supply chain, demand forecasting helps companies make decisions across a wide range of business areas. Only with demand forecasting companies can accurately predict demand for their products or services – and optimize production, inventory, or marketing. For more competitiveness, lower costs, and better customer relationships.

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