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Data analysis in purchasing: definition and important aspects for purchasing specialists
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Data analysis in a nutshell:
Data analysis is the systematic examination and evaluation of data sets using statistical and analytical methods to gain usable insights. In purchasing, it enables fact-based decisions in supplier selection, cost optimization and demand forecasts as well as the identification of potential savings.
Example: An automotive supplier analyzes its purchasing data from the last 24 months and, by evaluating 50,000 order items, realizes that consolidating from 12 to 3 suppliers for C-parts leads to process and cost savings of EUR 120,000 per year.
Contents
What is data analysis in purchasing?
Data analysis in purchasing refers to the systematic collection, evaluation and interpretation of purchasing-relevant data. The aim is to make better purchasing decisions based on sound information. Data on supplier management, prices, procurement volumes and market trends are analysed in order to reduce costs, optimize processes and minimize risk management.
Core elements of data analysis in purchasing
Significance for purchasing
Data analysis is an essential part of modern procurement management. It enables companies to make informed decisions and gain a competitive advantage. By using data, buyers can conduct better price negotiations, strengthen supplier relationships and identify market risks at an early stage.
Whitepaper: Data analysis in purchasing - methods and best practices for strategic decisions
Data analysis in purchasing: from manual evaluation to advanced analytics
Data analysis in procurement has changed fundamentally in recent years. While manual processes used to dominate, digitalization now enables in-depth and precise analysis of large volumes of data. This transformation is crucial in order to remain competitive, reduce costs and make informed strategic decisions. The need to react quickly to market changes and manage supply chains efficiently is driving the shift from traditional to modern approaches.
Old: Manual data evaluation in purchasing
Traditional approach:
In the past, data analysis in purchasing was mainly done manually. Purchasing employees collected data from various sources, kept Excel spreadsheets and created reports by hand. This method was time-consuming and error-prone. The limited data processing capacity made it difficult to recognize patterns and trends. In addition, the data was often not available in real time, which meant that decisions were based on outdated information. The lack of integration of different data sources led to inconsistencies and made it difficult to gain a holistic view of the purchasing organization.
New: Advanced analytics in purchasing
Advanced Analytics:
The modern approach uses advanced analytics to efficiently process large volumes of data and generate valuable insights. By using big data technologies, artificial intelligence and machine learning, data from ERP systems, supplier portals and external sources can be integrated. Real-time analyses make it possible to react quickly to market trends and create predictive models. This leads to proactive decision-making, optimized procurement strategies and an improved supplier relationship. Automated data processing minimizes errors and increases the efficiency of purchasing processes.
Practical example: Increasing efficiency through data analysis at an automotive manufacturer
A global automotive manufacturer implemented advanced analytics in its purchasing system. By integrating real-time data from production facilities and supplier portals, the company was able to reduce its stock levels by 18%. Predictive analytics helped to identify supply bottlenecks at an early stage and proactively initiate countermeasures. The improved data quality led to cost savings of 12% in procurement. In addition, transparent data analysis enabled a stronger negotiating position with suppliers and contributed to a 25% increase in the efficiency of purchasing processes.
Conclusion on supplier evaluation through data analysis
Data analysis in purchasing has become an indispensable tool for modern companies. By systematically recording and evaluating supplier data, costs can be reduced, risks minimized and strategic decisions optimized. Success lies in the combination of technological infrastructure, trained personnel and standardized processes. Only those who bring these factors together in a targeted manner can remain competitive in an increasingly complex procurement environment.
