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Order history: definition and important aspects for buyers
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Order history in a nutshell:
The order history is a chronological documentation of all procurement transactions carried out, including relevant data such as prices, quantities, suppliers and conditions. It enables the purchasing department to analyze past transactions for strategic decisions and negotiations.
Example: An automotive supplier analyzes its order history of the last 24 months and realizes that the prices for electronic components from supplier A were on average 12% lower than from supplier B, which leads to a redistribution of the order volume of 2.5 million euros.
Contents
What is the order history?
The order history is a detailed record of all orders that a company has placed with its suppliers. It includes information such as order dates, article numbers, quantities, prices and supplier information. The order history enables companies to track previous procurements, analyze expenditure and identify patterns in order management. It forms the basis for well-founded purchasing decisions and supports the optimization of procurement processes.
Core elements of the order history
Importance of order history in purchasing
In procurement management, order history is an essential tool for transparency and efficiency. It enables purchasers to analyze historical data and derive strategic decisions from it. By evaluating the order history, potential savings can be identified, supplier relationship management optimized and purchasing processes improved. It also supports demand forecasting and helps to avoid excess stock or bottlenecks.
Order history: from manual recording to AI-supported order analysis
The order history forms the basis for well-founded purchasing decisions by providing detailed records of all orders placed. Traditionally, this history was maintained manually, which was time-consuming and error-prone. However, with the advent of digital technologies, there is a need to transform the ordering process to increase efficiency and secure competitive advantage.
Old: Manual order recording
Traditional approach: In traditional procurement, orders were often recorded using paper documents or simple spreadsheets. Procurement staff manually documented purchase order data, archived delivery bills and invoices in physical folders and manually reconciled purchase orders and deliveries. This process was characterized by redundant tasks, a lack of real-time transparency and an increased susceptibility to errors. In addition, isolated data silos made it difficult to analyze procurement activities holistically, which meant that potential savings remained untapped.
New: AI-supported order analysis
Advanced procurement analytics: Modern companies rely on AI-supported systems to automatically record and evaluate their order history. By integrating ERP systems, e-procurement platforms and big data analyses, order data is processed in real time. Artificial intelligence recognizes patterns in spending trends, forecasts future requirements and identifies potential savings. This enables strategic supplier selection, optimized warehousing and reduced procurement costs. Automation minimizes manual intervention, reduces error rates by up to 90% and significantly increases the efficiency of purchasing processes.
Practical example: Increasing efficiency at ABC AG
ABC AG, a leading manufacturing company, transformed its procurement processes by implementing an AI-supported purchasing system. Before the changeover, orders were recorded manually, which led to delays and a lack of overview. After introducing the new technology, the company was able to reduce process throughput time by 40%. The error rate for orders fell by 85%, and by analyzing the order history, ABC AG identified potential savings of 15% in procurement costs. In addition, the real-time data analysis enabled a better negotiating position with suppliers and optimized warehousing.
Conclusion on the order history
The order history is an indispensable tool for strategic purchasing decisions. It not only enables the systematic analysis of procurement processes and cost structures, but also forms the basis for future-oriented optimizations. Through the intelligent use of historical order data, companies can make their purchasing processes more efficient, reduce costs and sustainably improve supplier relationships. In the age of digitalization, data-based management of purchasing is becoming a decisive competitive factor.
