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GraphTour 2020 - Neo4j Innovation Lab

GraphTour 2020 Amsterdam
Stefan Wendin, Neo4j

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GraphTour 2020 - Neo4j Innovation Lab

  1. 1. Neo4j Innovation Lab Graph Tour EMEA, 2020
  2. 2. Neo4j Innovation Lab Once upon a time in a galaxy far, far away…
  3. 3. Neo4j Innovation Lab 1. Future Prediction 2. Unlearn 3. Do or Don’t
  4. 4. Neo4j Innovation Lab Values and Beliefs Artefacts and Tools Actions and Behaviours Culture consist of three components Values Beliefs Artefacts Tools Actions BehavioursCulture
  5. 5. Neo4j Innovation Lab – Yoda, The Empire Strikes Back You Must Unlearn What You Have Learned!
  6. 6. Neo4j Innovation Lab It’s about the ability to choose an alternative mental model or paradigm Unlearning is not about forgetting
  7. 7. Neo4j Innovation Lab What most people working with innovation think innovation looks like… Disruption Status Quo Competence Sweater
  8. 8. Neo4j Innovation Lab I love child things because there's so much mystery when you're a child. When you're a child, something as simple as a tree doesn't make sense. Me You
  9. 9. Neo4j Innovation Lab A Decade of Learning from Enterprise Adoption Best in class
  10. 10. Neo4j Innovation Lab Digital Native CompaniesCompanies in Transition A Decade of Learning from Enterprise Adoption Digital Transformation with Graphs
  11. 11. Neo4j Innovation Lab Airline-customer Large telco in Europe Telco Online Retail Consulting Investment Banking Software Financial Services H120172014 2015 2016 H22017 2018 200 A Decade of Learning from Enterprise Adoption Digital Transformation with Graphs
  12. 12. Neo4j Innovation Lab Connecting silos transforms companies A Decade of Learning from Enterprise Adoption
  13. 13. Neo4j Innovation Lab Connected insights leads to revelations you wouldn’t have access to in any other way A Decade of Learning from Enterprise Adoption
  14. 14. Neo4j Innovation Lab Connected Data Use cases spawn more use cases (data-network effects) A Decade of Learning from Enterprise Adoption
  15. 15. Neo4j Innovation Lab How much data do you have over time How much does the value of the product or service increase as a result of the data
  16. 16. Neo4j Innovation Lab
  17. 17. Neo4j Innovation Lab David Dunning and Justin Kruger Dunning–Kruger effect A cognitive bias in which people assess their cognitive ability as greater than it is.
  18. 18. Neo4j Innovation Lab 👋Hi! PLEASE CONNECT: stefan.wendin@neo4j.com linkedin.com/in/stefanwendin Head of Innovation Lab, EMEA Stefan Wendin
  19. 19. Neo4j Innovation Lab Back in 2017…
  20. 20. Neo4j Innovation Lab Create a program that combines the…
  21. 21. Neo4j Innovation Lab Empathic approach of design thinking…
  22. 22. Neo4j Innovation Lab …with hard-core data science and graphs
  23. 23. Neo4j Innovation Lab — with the intention of Accelerating Innovation
  24. 24. Neo4j Innovation Lab Discrete data, as represented in a relational database
  25. 25. Neo4j Innovation Lab Data represented as a graph
  26. 26. Neo4j Innovation Lab A Paradigm Shift in How We Think About Data
  27. 27. Neo4j Innovation Lab Every change comes with a cost
  28. 28. Neo4j Innovation Lab 🤮 💩 😭 😬 🤬 😢 😳 😳 😃 🧐 😒 🤩 🥵 The Kubler-Ross Change Curve
  29. 29. Neo4j Innovation Lab Neo4j Innovation Lab
  30. 30. Neo4j Innovation Lab – Yogi Berra / Jan L. A. van de Snepscheut In theory there is no difference between theory and practice. In practice there is.
  31. 31. Neo4j Innovation Lab
  32. 32. Neo4j Innovation Lab Bansi Nagji and Geoff Tuff The Innovation Ambition Matrix
  33. 33. Neo4j Innovation Lab Process – Process – Process The importance of
  34. 34. Neo4j Innovation Lab IBM Design Thinking Model Google Design Sprint Process Ideo Human Centered Design Model Stanford D School Design Thinking Zurb Design Thinking Model The Double Diamond Model of Design Design Council Everybody has a “Sprint”
  35. 35. Neo4j Innovation Lab IdeationInspiration Implementation Discover Concept Design Do Envision Explore Create Inspire Express Prepare Form Harden Fire& Glaze Research Modeling, Scenarios Framework Design Communicate Discover Design Deliver Discover Define Design Do Explore Discover Concept & Design Implement & Assess Discovery Interpretation Ideation Experimentation Evolution Empathise Define Ideate Prototype TestSTANDFORD IDEO XPLANE CHESKIN BITOMI COOPER FROG FITCH MELVILLE IDEO ED Everybody has a “Sprint”
  36. 36. Neo4j Innovation Lab – Murray Walker (BBC motorsport commentator) The lead car is unique, except for the one behind it which is identical
  37. 37. Neo4j Innovation Lab Neo4j ❤ Design Thinking
  38. 38. Neo4j Innovation Lab Neo4j Innovation Lab Accelerate Innovation Through Graph Thinking
  39. 39. Neo4j Innovation Lab • Speed up time-to-validation • Comprehensive learning through prototyping • Craft meaningful value propositions Innovation Task Neo4j Innovation Lab Sweet spot
  40. 40. Neo4j Innovation Lab Help companies accelerate innovation and digital transformation through graph thinking. What we do We generate and prototype graph projects together with customers and prospects. How we do it Expected Outcome To provide a deep understanding of graph thinking and the new possibilities in innovation and digital transformation that is enabled by adopting Neo4j and graphs. Innovation Lab: Sprint — 4 day workshop Accelerator Program — Four consecutive Lab Sprints MethodologyNeo4j Innovation Lab Sweet spot
  41. 41. Neo4j Innovation Lab Innovation Lab Sprint The Methodology Generate Data ModelDefine Target Use Case Related “Graph Questions” Executive Feedback PresentationBuild Prototype/Wireframes
  42. 42. Neo4j Innovation Lab Innovation Lab Sprint The Methodology Generate Data Model Areas of Significance Define Target Use Case Challenges & Opportunities Related “Graph Questions” Use Case Generation & Whiteboard Model Day 1 Identify Data Sources
  43. 43. Neo4j Innovation Lab Source data to populate model Build QueryImport Data Innovation Lab Sprint The Methodology Generate Data Model Areas of Significance Define Target Use Case Challenges & Opportunities Related “Graph Questions” Materialize Model Day 2
  44. 44. Neo4j Innovation Lab Source data to populate model Storyboarding/ Mockups Identify Stakeholders / Personas / Synopsis Build QueryImport Data Innovation Lab Sprint The Methodology Areas of Significance Related “Graph Questions” Generate Data Model Define Target Use Case Challenges & Opportunities Craft Scenario Day 2 Materialize Model Day 2
  45. 45. Neo4j Innovation Lab Build Prototype/Wireframes Source data to populate model Storyboarding/ Mockups Identify Stakeholders / Personas / Synopsis Build QueryImport Data Innovation Lab Sprint The Methodology Areas of Significance Related “Graph Questions” Generate Data Model Define Target Use Case Challenges & Opportunities Build Prototype Day 3
  46. 46. Neo4j Innovation Lab Executive Feedback Presentation Source data to populate model Storyboarding/ Mockups Identify Stakeholders / Personas / Synopsis Build QueryImport Data Innovation Lab Sprint The Methodology Areas of Significance Related “Graph Questions” Generate Data Model Define Target Use Case Challenges & Opportunities Build Prototype/Wireframes Finalize & Present Day 3.5
  47. 47. Neo4j Innovation Lab 1. Defining Use Case UX/UI Lead Data Scientist Head of Innovation Developer CIO Business Analyst Head of Customer Success
  48. 48. Neo4j Innovation Lab 2. Data modeling Adam Cowley, Neo4j Field Engineer Director of AI Data Scientist Eric Monk, Neo4j PS- consultant Innovation Lab Leader
  49. 49. Neo4j Innovation Lab 3. Crafting Prototype
  50. 50. Neo4j Innovation Lab Innovation Lab Sprint Explorations and new insights Using Neo4j and graphs to explore new insights from a customer support perspective
  51. 51. Neo4j Innovation Lab “If you build a polished prototype, others will see flaws.
  52. 52. Neo4j Innovation Lab — Baba Shiv Stanford Graduate School of Business “If you build a polished prototype, others will see flaws. If you build a rough prototype, others will see potential”
  53. 53. Neo4j Innovation Lab Who should participate?
  54. 54. Neo4j Innovation Lab Customer’s Team (Between 3-8 participants) “Technical users” “Business users” Neo4j Field Engineer • Facilitates graph modeling exercises • Expert in Neo4j/Architecture & Data Science • Cypher-queries for prototype UX-designer • Facilitates storyboarding/wireframing • Builds UI-tool for prototype Labs Leader • Head facilitator & Team Leader • Facilitates the use case generation-segment • Project manages prototyping Neo4j Innovation Lab Team + Facilitation Engineering/ Data Science Design The Workshop Neo4j Innovation Lab Team Digital Transformation /Innovation Teams Key sponsor Example: • Developers • Architects • Data engineers • Data Scientists Example: • Use Case-specific experts • Analysts • Strategists • Innovation Team
  55. 55. Neo4j Innovation Lab Data Preparations
  56. 56. Neo4j Innovation Lab ✓ Thousands of nodes/relationships ✓ Multiple Data Sources ✓ Captured Network Complexity of Use Case ✓ Simulated Sample Data Simulated Data ✓ Millions of Nodes/Relationships ✓ Multiple Data Sources ✓ Captured Network Complexity of Use Case ✓ Real Sample Data (ingested with accurate properties) ✓ Data ingestion through CSV-files ✓ Data ingested at scale Real Sample Data at Scale ✓ Hundreds of Thousands of Nodes/Relationships ✓ Multiple Data Sources ✓ Captured Network Complexity of Use Case ✓ Real Sample Data (ingested with accurate properties) ✓ Data ingestion through CSV-files Real Sample Data CSV CSV Data preparations Type of Data used
  57. 57. Neo4j Innovation Lab Simulated data Real Sample Data Domain Specificity Great Data Quality Poor Data Quality Intuitive datasets Obscure Data Sets (i.e. a product catalogue where all products are translated to article numbers) Data QualityTime to access Data preparations Real or Simulated Data? It depends – but while prototyping we almost always opt for speed versus granular detail. Cumbersome and time consuming to access Readily Available
  58. 58. Neo4j Innovation Lab Sample Data Sample Data Simulated Simulated Simulated Simulated Simulated Sample Data Sample Data NODE NODE NODE NODE NODE NODE NODE NODE NODE NODE HAS_INVITATION RELATIONSHIP RELATIONSHIP RELATIO N SH IP RELATIO N SH IP RELATIONSHIP RELATIONSHIP RELATIONSHIP RELATIONSHIP RELATIONSHIP RELATIONSHIP RELATIONSHIP RELATIONSHIP RELATIO NSHIP RELATIONSHIP RELATIONSHIP IS_NEXT… Sample Data Example Data model
  59. 59. Neo4j Innovation Lab Software Companies Heavy Industry FMCG Cruising Companies Logistics Financial Services Media Health Care Energy Telco Industries Use Cases Recommendation Engines Smart Cities Personalization Fraud Detection Data Lineage Construction Planning Regulatory Compliance Media Advertising Systems Supply Chain Preventive Health Care Tools Churn Prediction Customer Service Automation Customer Journey Mapping Full view 360 Retail Bill of Materials Knowledge Graph Crypto Currency Fraud ChatBot NLP Payment Solutions Enhanced AI/ML Pipeline
  60. 60. Neo4j Innovation Lab “Very impressed. Intense and fun! We got a lot done in just a week. Great experience and super effective.” — Santander Consumer Bank “Unexpected and pretty incredible that it’s possible to achieve such relevant and applicable results in such a limited time period.” — Schibsted Media Group “The productivity and output enabled by how the days were structure and the exercises within the sessions has been an eye-opener.” — Procter & Gamble FEEDBACK RECEIVED “Involving. Knowledge building. Fun! Extremely valuable and mind opening” — Alfa Laval
  61. 61. Neo4j Innovation Lab
  62. 62. Neo4j Innovation Lab Madrid, 13 February Tel Aviv, 18 February Fortum – Stockholm, 03 March Planethon – London, 11 March BMW – Munich, 17 March Eriks – Paris, 26 March Rome, 31 March Eriks – Amsterdam, 04 February
  63. 63. Neo4j Innovation Lab Neo4j Innovation Lab, EMEA

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