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Network analysis: definition & important aspects for buyers
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Network analysis in a nutshell:
Network analysis is a systematic method for examining and visualizing relationships and dependencies between different actors or elements in a system. In purchasing, it enables the strategic evaluation of supplier-customer relationships and the identification of risks and optimization potential in the supply chain.
Example: A car manufacturer conducts a network analysis of its 250 main suppliers and identifies 3 critical Tier 2 suppliers that influence 65% of its just-in-time production, whereupon targeted risk management measures are implemented.
Contents
Introduction to network analysis
What is network analysis?
Network analysis is a methodical approach to analyzing relationships and interactions within complex procurement networks. It views suppliers, customers, products and other players as nodes in a network and analyzes the connections between them. This analysis enables companies to identify patterns, increase efficiency and make more informed strategic decisions.
Core elements of network analysis
Importance of network analysis in purchasing
In the area of procurement, network analysis enables an in-depth understanding of supplier relationships and supply chain structures. It helps to identify critical suppliers, recognize risks at an early stage and manage relationships strategically. By analyzing network dynamics, buyers can develop more effective negotiation strategies and improve the efficiency of procurement processes.
Application of network analysis in purchasing
Network analysis helps buyers to understand and evaluate the relationships between suppliers. The analysis can be used to identify critical connections and develop strategies to optimize the supply chain.
Example: Identification of key suppliers using centrality measures
Situation:
A company works with 8 suppliers (A to H). The suppliers are networked with each other, e.g. through sub-deliveries or joint projects.
Steps of the network analysis:
1. Create a network diagram: Draw the suppliers as nodes and connect them according to their relationships.
2. Calculate the degree centrality: Count the direct connections of each supplier.
- Supplier A: 3 connections
- Supplier B: 5 connections
- Supplier C: 6 connections
- Supplier D: 2 connections
- Supplier E: 4 connections
- Supplier F: 1 connection
- Supplier G: 2 connections
- Supplier H: 3 connections
3. Analysis of the results: Supplier C has the highest centrality with 6 connections and is therefore a critical node in the network.
4. Strategic measures: Focus on Supplier C for strategic partnerships, as its failures would have a significant impact on the network.
Conclusion:
Through network analysis, the buyer identifies key suppliers and can proactively minimize risks and strengthen the resilience of the supply chain.
Evaluation and strategic findings
✓ Critical success factors
→ Data quality and granularity: Precise recording of all supplier relationships and dependencies down to the lower supply chain levels
→ Dynamic updating: Continuous maintenance of network data to map changing supplier relationships
→ Visualization skills: Effective representation of complex network structures for better decision-making
⚠ Challenges and limitations
→ Data availability: Difficult to obtain information on tier-2 and tier-3 supplier relationships
→ Mastering complexity: The complexity of analysis increases exponentially with large supply networks
→ Interpretation effort: High need for expert knowledge to correctly interpret the network metrics
Future trends and strategic implications:
"The integration of AI and real-time data will transform network analysis from a static to a dynamic management tool."
→ Predictive analytics for network risks
→ Automated early warning systems for supply chain disruptions
→ Integration of ESG factors into the network valuation
→ Blockchain-based transparency in multi-level supply chains
Conclusion on the network analysis
Network analysis is an indispensable tool in modern purchasing that enables strategic decisions to be made by systematically analyzing supplier relationships. It helps to identify critical suppliers, minimize risks and optimize procurement processes. Despite challenges such as data availability and complexity, it offers enormous potential for effective supply chain management, especially in combination with new technologies such as AI and blockchain.
