Optimal order quantity 

Definition

Optimal order quantity is a term used in supply chain management. The optimal order quantity refers to the amount of goods that a company should order in order to reduce its overall costs and maximize its efficiency.  

The optimal order quantity is influenced by various factors, such as 

• the demand for the product 
• the delivery times of the supplier  
• the storage costs  
• the order costs  

Determining the optimal order quantity is an important element in minimizing inventory and ordering costs and making the company's supply chain more efficient. 

Calculation of the optimal order quantity  

The optimal order quantity is usually calculated using the "Andler formula": Square root of (annual demand x order cost x 2) / (product value x inventory cost rate). 

Artificial intelligence (AI) can be used for calculation and help analyze large amounts of data for determining the optimal order quantity. In doing so, the AI accesses historical data on demand, delivery and storage, for example, and derives patterns and trends from this. 

Based on these findings, models are determined to calculate the optimal order quantity. The models take into account several factors, such as delivery time, ordering costs and storage costs. 

Using Artificial Intelligence to calculate the optimal order quantity leads companies to achieve better business results and improve their forecasting and decision-making. By predicting demand more accurately, excess inventory and shortages are avoided while reducing inventory and ordering costs. 

Importance of the optimal order quantity for the food industry 

The optimal order quantity is of great importance for the food sector, as many perishable food products have to be ordered every day. The optimal order quantity ensures that no unnecessary costs are incurred, because overproduced goods must be disposed of and ordered fresh for the next day. Too low an order quantity can lead to shortages and lost sales. Too high an order quantity leads to unnecessary warehousing costs and food waste.