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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
Data analysis in purchasing
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 suppliers, prices, procurement volumes and market trends are analysed in order to reduce costs, optimize processes and minimize risks.
Core elements of data analysis in purchasing
Significance for purchasing
Data analysis is an essential part of modern purchasing 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-driven supplier evaluation
Systematic data analysis enables buyers to objectively evaluate the performance of their suppliers. Key figures such as delivery punctuality, quality rate and price development are used to increase the efficiency of the supply chain and identify potential for cost reduction.
Calculation example: Supplier performance
A company analyzes the delivery punctuality of its three main suppliers over the last quarter:
- Supplier A: 48 out of 50 deliveries on time → 96% delivery punctuality
- Supplier B: 45 out of 50 deliveries on time → 90% delivery punctuality
- Supplier C: 40 out of 50 deliveries on time → 80% delivery punctuality
Through the data analysis, the buyer recognizes that supplier C has the lowest delivery punctuality. This leads to production delays and additional costs of €5,000 per month on average. These costs can be reduced through discussions and negotiations with Supplier C or by searching for alternative suppliers.
Evaluation and strategic findings
✓ Critical success factors
→ Systematic data collection: implementation of standardized processes to record relevant supplier KPIs such as delivery reliability, quality and cost compliance
→ Analytics expertise: building up expertise in the purchasing team for the effective use of analytics tools
→ Supplier integration: establishing transparent communication channels for data-based supplier management
⚠ Challenges
→ Data quality: Ensuring consistent data collection across different procurement categories
→ System complexity: integration of different ERP and procurement systems for holistic analyses
→ Change management: overcoming traditional decision-making patterns in favor of data-based strategies
◆ Future trends
Development prospects 2024+:
→ Predictive analytics for proactive supplier management
→ AI-supported early risk detection in the supply chain
→ Automated performance scorecards
○ Strategic implications
→ Investment focus: prioritization of data analysis tools to optimize supplier evaluation
→ Capacity building: targeted training of purchasing employees in data-driven methods
→ Process customization: Integration of analytics insights into standard purchasing processes
"The transition to a data-driven procurement strategy is not optional, but essential for the survival of future-proof purchasing organizations."
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.
