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The Case for Graphs in Supply Chains

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Speaker: Alessandro Svensson, Head of Neo4j Innovation Lab, Neo4j

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The Case for Graphs in Supply Chains

  1. 1. The Case for Graph in Supply Chain Alessandro Svensson Head of Neo4j Innovation Lab A look under the hood when innovating with graphs July 28, 2020
  2. 2. Neo4j Innovation Lab Everything is Naturally Connected Your Organization Context of Behavior Logistics DNA-strings Customers Supply Chain Health Causes Insurance Fraud Purchase Patterns People Events Proteins Traffic Light Patterns Weather Conditions Materials Systems of Records IT-infrastructure Home appliances Knowledge
  3. 3. Neo4j Innovation Lab The organizations that understand and leverage how everything is connected in the context of their domain, enjoy tremendous opportunity
  4. 4. Neo4j Innovation Lab Failure to see or shift to adapting your organization to how everything is connected, means your operating at a deficit —  and puts you at risk of disruption
  5. 5. Neo4j Innovation Lab Case Study: The Consumer Web C 34,3%B 38,4%A 3,3% D 3,8% 1,8% 1,8% 1,8% 1,8% 1,8% E 8,1% F 3,9%
  6. 6. Neo4j Innovation Lab The connected world requires a new way of thinking
  7. 7. Neo4j Innovation Lab
  8. 8. Neo4j Innovation Lab
  9. 9. Neo4j Innovation Lab The companies that succeed in the connected world do so with graphs
  10. 10. Supply Chain Management
  11. 11. Supply Chain is a Graph Neo4j Innovation Lab
  12. 12. • Customers • Employee • Suppliers • Materials • Products • Plants • Distribution Centers • Shipments • Etc… Supply Chain is a Graph Neo4j Innovation Lab
  13. 13. Why Supply Chain Matters Supply Chain Management with Graphs • In the global economy, companies must stabilize their supply chains by working with multiple suppliers, boosting inventories, diversifying customers, and investing in omni-channel distribution. • Effective supply chain management is crucial to mitigate both supply and demand side risk and… • …ultimately as a strategy to optimize revenue.
  14. 14. Data represented as in a relational database Supply Chain Management with Graphs Traditional technology and optimization models cannot account for chain-reactions triggered by major disruptions, because of its inability to handle connections between entities sufficiently. Why graphs?
  15. 15. Data represented as a graph Supply Chain Management with Graphs Traditional technology and optimization models cannot account for chain-reactions triggered by major disruptions, because of its inability to handle connections between entities sufficiently. Why graphs?
  16. 16. How to innovate successfully in the in the age of connected data?
  17. 17. 1. Data Capture 2. Data Modeling & Storage 3. Processing & Analytics 4. End user-applications & Insights Consider these 4 steps: (Collecting the most relevant data for the use case) (Choosing the right technology for the right job) (Queries and Algorithms) (Tangible, end-results)
  18. 18. 1. Data Capture 2. Data Modeling & Storage 3. Processing & Analytics 4. End user-applications & Insights Because of its connected nature, supply chain is a massive data challenge
  19. 19. What are the essential data- points and behaviors relevant to your use case to capture? 1. Data Capture 2. Data Modeling & Storage 3. Processing & Analytics 4. End user-applications & Insights Demand Supply Manufacturing Warehousing Order Fulfillment Transportation Weather Geospatial Third Party On Prem Data Lakes Data Warehouse Cloud IT infrastructure
  20. 20. Disparate Silos Cross-Silo Connections Property Graph Model 1. Data Capture 2. Data Modeling & Storage 3. Processing & Analytics 4. End user-applications & Insights Demand Supply Manufacturing Warehousing Order Fulfillment Transportation Weather Geospatial Third Party
  21. 21. 1. Data Capture 2. Data Modeling & Storage 3. Processing & Analytics 4. End user-applications & Insights Modeling a Supply Chain Graph • Carrier • Shipping Site • Material • Material Group • Location • Customer • DC • Plant • Shipment • Delivery ~16 in the model • ON_DELIVERY • SHIP_CARRIER • SHIP_MODE • CONTAINS • IS_IN_GROUP • SHIPPED_TO • SHIPPED_FRO • SOURCE • HAS_LOCATION Structural Elements Behavioral Elements Relationship Types Temporal Elements • TimeTree — Facilitates point in time queries and versioning
  22. 22. Query (e.g. Cypher/Python) You know what you’re looking for and make a decision in real-time Local Patterns Graph Algorithms You’re learning the overall structure of a network, updating data, and predicting Global Computation 1. Data Capture 2. Data Modeling & Storage 3. Processing & Analytics 4. End user-applications & Insights Input data
  23. 23. Learning through prototyping
  24. 24. Supply Chain Software Prototype
 (Supply Chain Software) Sign in What’s going on under the hood?
  25. 25. What’s going on under the hood? (Conceptual) Prototype
 (Supply Chain Software) Detecting the shortest, cheapest path between a manufacturing plant (in green) and a customer (in blue) in a supply chain. Shortest Path Algorithms
  26. 26. Prototype
 (Supply Chain Software) Detecting the shortest, cheapest path between a manufacturing plant (in green) and a customer (in blue) in a supply chain. Shortest Path Algorithms What’s going on under the hood? (Conceptual)
  27. 27. Detecting the shortest, cheapest path between a manufacturing plant (in green) and a customer (in blue) in a supply chain. Shortest Path Algorithms Weights to relationships that indicates cheapest paths Prototype
 (Supply Chain Software) What’s going on under the hood? (Conceptual)
  28. 28. Detecting the shortest, cheapest path between a manufacturing plant (in green) and a customer (in blue) in a supply chain. Shortest Path Algorithms Prototype
 (Supply Chain Software) 🔥 Weights to relationships that indicates cheapest paths What’s going on under the hood? (Conceptual)
  29. 29. Prototype
 (Supply Chain Software) Calculate all possible routes PATH_0 (green) is the shortest path through the supply chain nodes. PATH_1 (orange) and PATH_2 (blue) are the next most cost-effective paths. What’s going on under the hood? (Conceptual)
  30. 30. Prototype
 (Supply Chain Software) Calculate all possible routes PATH_0 (green) is the shortest path through the supply chain nodes. PATH_1 (orange) and PATH_2 (blue) are the next most cost-effective paths. “Best” paths based on relevant criteria What’s going on under the hood? (Conceptual)
  31. 31. Prototype
 (Supply Chain Software) Centrality Algorithm Graph depicting the centrality scores of nodes based on incoming and outgoing shipments. What’s going on under the hood? (Conceptual)
  32. 32. Prototype
 (Supply Chain Software) Centrality Algorithm Graph depicting the centrality scores of nodes based on incoming and outgoing shipments. What’s going on under the hood? (Conceptual)
  33. 33. Prototype
 (Supply Chain Software) Node Similarity I.e. Jaccard similarity, overlap similarity, cosine distance, euclidean distance etc. Centrality Algorithm Calculating centrality scores What’s going on under the hood? (Conceptual)
  34. 34. Under the hood Applications INPUT DATA + Analytics Pipeline + AI/ML-pipeline 1. Data Capture 2. Data Modeling & Storage 3. Processing & Analytics 4. End user-applications & Insights Dashboards Route-planningExploration
  35. 35. Under the hood Applications INPUT DATA + + Analytics Pipeline (AI/ML-pipelines) It’s what happens under the hood that determine the potential of your applications. If you have a connected data problem — make sure to solve it with graphs! 1. Data Capture 2. Data Modeling & Storage 3. Processing & Analytics 4. End user-applications & Insights
  36. 36. If you want to learn more…
  37. 37. The Applied Use Case Training Program Learning graphs in the context of a use case Brought to you by: Neo4j Innovation Lab & Neo4j Graph Academy
  38. 38. 1. Data Capture 2. Data Model & Storage 3. Processing & Analytics 4. Applications & Insights Micro Batches Micro Batches Real-Time Transactions Graph Algorithm Feedback Cypher Workbench Modeling & Code Gen Hop ETL Apache Kafka Event Streams GRAND Stack Dashboard Bloom & Linkurious Graph Visualizations Neo4j BI Connector SQL BI Tools Neo4j Browser SQL BI Tools DBC HDFS ETL CSV JSON Neo4j Graph Database Graph Data Science Library Cypher Keymaker Analytics Pipelines Micro Batches Micro Batches Real-Time Transactions Graph Algorithm Feedback Cypher Workbench Modeling & Code Gen Hop ETL Apache Kafka Event Streams GRAND Stack Dashboard Bloom & Linkurious Graph Visualizations Neo4j BI Connector SQL BI Tools Neo4j Browser SQL BI Tools DBC HDFS ETL CSV JSON Neo4j Graph Database Graph Data Science Library Cypher Keymaker Analytics Pipelines Neo4j Supply Chain Solutions Framework
  39. 39. 1. Data Ingestion 2. Data Model & Storage 3. Processing & Analytics 4. Applications & Insights Micro Batches Micro Batches Real-Time Transactions Graph Algorithm Feedback Cypher Workbench Modeling & Code Gen Hop ETL Apache Kafka Event Streams GRAND Stack Dashboard Bloom & Linkurious Graph Visualizations Neo4j BI Connector SQL BI Tools Neo4j Browser SQL BI Tools DBC HDFS ETL CSV JSON Neo4j Graph Database Graph Data Science Library Cypher Keymaker Analytics Pipelines Neo4j AML Solutions Framework
  40. 40. Keymaker Analytics Pipelines Cypher Workbench Modeling & Code Gen Hop ETL Apache Kafka Event Streams Neo4j Graph Database Graph Data Science Library Cypher GRAND Stack Dashboard Bloom & Linkurious Graph Visualizations Neo4j BI Connector SQL BI Tools Neo4j Browser SQL BI Tools The Property Graph Model The Case for Graphs Curriculum Module Graphs in Supply Chain Module Graph Queries & Algorithms Module Building Applications
  41. 41. Curriculum Module The Case for Graphs Module Graphs in Practice Module Solutions Framework • The Case for Graphs in Supply Chain • Property Graph Model • Money Queries • Modeling • Data Loading Techniques • Cypher • Graph Algorithms • Supply Chain Solutions Framework • Keymaker Analytics Pipeline • Application building examples
  42. 42. About the program A training program that teaches graphs in the context of a use case What? Enterprise developer & architect teams at large/midsize organizations Who should participate? 12 hour instructor lead curriculum combined with self- paced assessments and exercises. How? Fast, and inexpensive, way to learn how to apply graphs from best practice in preparation for a more robust POC. Why? Use Case Training POC
  43. 43. Please feel free to reach out to me for more information! alessandro.svensson@neo4j.com Alessandro Svensson, Neo4j
  44. 44. Thank you for listening! " alessandro.svensson@neo4j.com Alessandro Svensson, Neo4j

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