How many inventory units are in stock? How often does inventory have to be replenished? How will demand change over the next few months? If you are unable to answer such questions clearly, this is the right place for you. In the following, we reveal why demand forecasting is important for every company.
What is a demand forecast?
Demand forecasts (in English:”Demand forecasting“) help companies predict future demand for products or services. Demand forecasts, for example, usually use historical data to estimate how many products or services can be sold on the market within a defined period of time. This helps companies make better business decisions — for example to optimize planning, production and inventory (and to minimize risks such as over or underproduction). “The goal of forecasting is not to predict the future. Rather, forecasts tell you what you need to know in order to take meaningful action in the present.” - Paul Saffo, technology forecaster from Silicon Valley.
Why is demand forecasting so important?
Demand forecasting is essential for every company. After all, it is only with a correct understanding of demand that well-founded decisions can be made regarding production, marketing expenditure or personnel deployment — and ensure that market requirements can be met. Let's say we're a retailer. We can only order the exact quantity if we know how many of which items will be in demand in the next few weeks. Whether ordering raw materials, production planning or pricing: Only those who know the demand can make well-founded decisions.
Here are 4 benefits of demand forecasting at a glance:
1) More efficient logistics
With calculated demand, logistical processes can be optimized. For example, bottlenecks and excessive storage costs can be avoided and warehouse utilization can be perfectly adapted to demand.
2) capacity planning
Whether raw materials, employees or machines: With a demand forecast, you can plan capacities more efficiently — and even save personnel costs by adapting employee shifts to demand.
3) Easier production planning
We can also better adjust production to demand with demand forecasts (and avoid overproduction or underproduction, for example). Especially in the food industry, products can spoil quickly if demand is too low.
4) More customer satisfaction
By planning demand better, companies can improve their delivery times and delivery quality. This increases customer satisfaction and increases customer loyalty. And it all leads to? That's right, higher turnover! By making products available at all times and saving costs in production and storage, sales and turnover can be increased.
What forecasting methods are there?
Demand forecasts are usually designed on the basis of historical data. The first step is therefore to collect historical data, which is then processed and purified. After collecting and processing the data, a mathematical model (“machine learning”) is trained. This can then calculate the future development of demand.
Basically, a distinction is made between qualitative and quantitative demand forecasting:
Quantitative forecasting
Quantitative demand forecasting is the most accurate forecasting method. They use objective metrics that can be derived from historical data and statistical analyses — and methods such as regression, time series analysis, artificial intelligence (AI) and machine learning (ML).
Qualitative forecast
Qualitative forecasts are based on subjective metrics such as customer opinions and market trends. Such demand forecasts are less accurate and are usually only used when there is not enough historical data. In return, qualitative forecasts can be implemented faster and more cost-effectively.
3 examples from practice:
These companies use demand forecasting
amazon
The online retailer uses demand forecasts on a large scale. Amazon, for example, uses machine learning models and other analysis tools to analyze demand for products in real time and fulfill orders. The company also uses demand forecasting to optimize inventory. In this way, the company can ensure that there is always enough goods in stock to meet customer inquiries quickly and efficiently.
Coca-Cola
Coca-Cola uses demand forecasting to analyze demand in various regions and markets. This allows the company to plan the production of its beverages more effectively and make decisions about adjusting production capacities. Coca-Cola also uses demand forecasts to optimize production and delivery costs through optimal transport and storage strategies.
walmart
Walmart is one of the biggest retailers in the world. The company uses demand forecasts to optimize inventory management in over 1100 stores in 27 countries. Walmart uses analytical tools and technologies, among other things, to effectively manage order volumes and inventory levels. In this way, Walmart optimizes the supply chain, avoids bottlenecks, achieves more sales and increases its own profitability.
Conclusion
Whether it's inventory planning or supply chain optimization, demand forecasting helps companies make decisions in numerous areas of business. Only with demand forecasting can companies accurately forecast demand for their products or services — and optimize production, inventory, or marketing. For greater competitiveness, lower costs and better customer relationships.