Lessons Learned from Building a Data Supply Chain
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The document discusses the importance of the data supply chain in information management, highlighting its role in analytics and best practices for building an effective data strategy. Guest speaker George Yuhasz, with extensive experience in various sectors, emphasizes the need for understanding business drivers and aligning data producers and consumers. Key lessons focus on engagement, empowering users, and aligning architecture and governance to optimize data operations.
Lessons Learned from Building a Data Supply Chain
- 1. The First Step in Information Management looker.com Produced by: MONTHLY SERIES In partnership with: Lessons Learned from Building a Data Supply Chain October 4, 2018
- 2. Welcome to Today’s Discussion Understanding the data supply chain How the data supply chain impacts analytics Lessons learned from building a data supply chain − Guest speaker: George Yuhasz Best practices Q&A pg 2© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
- 3. Meet Our Guest Speaker: George Yuhasz George Yuhasz has over 16 years of experience leading enterprise data initiatives in financial services, healthcare, manufacturing, government, military and higher education. His expertise spans areas such as Business Intelligence, Data Governance, Data Architecture and Strategy. Currently, George is overseeing the development and execution of the US Data Strategy at Keystone Foods, a provider of food solutions to the world's finest and most recognizable brands. pg 3© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
- 4. What is a Data Supply Chain? The Data supply chain represents the sources, flows, management and distribution of data and information in an organization. pg 4© 2018 First San Francisco Partners www.firstsanfranciscopartners.com • Steel • Aluminum Raw Material • Supplier • Fabrication Make/ Acquire Parts • Processes • Sequence Assembly • Ship • Store • Sell Distribute •Internal Database •Derived data Raw Material •External File •Clean Data •Standardize and Position Data Make/ Acquire Parts •Populate Sand Box •Develop and Run Models Assembly •Visualization •Publish and Pull •Sell Results Distribute A regular supply chain coordinates material sourcing and assembly to fulfill and deliver goods to customers.
- 5. Data Supply Chain Features of a Modern Data Supply Chain CREATE USE UPDATE MEASURE MODEL ANALYZE DELETE Goods and Services Supply Chain Distribution Purchasing Operations Integration Functions Logistics Compliance Organization Product Mgmt Capabilities Data Push and Pull Data Management Data Operations Data Integration Functions BI, Analytics Governance Engagement Model Product Mgmt Capabilities Data Supply Chain pg 12© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
- 6. How Analytics Must Interact with the Data Supply Chain pg 6© 2018 First San Francisco Partners www.firstsanfranciscopartners.com Data Supply Chain DATA SOURCES Analytics will lie somewhere along your data supply chain. LANDING ZONE STANDARDIZATION ZONE ANALYTICS PLATFORMS DATA GOVERNANCE DATA CONSUMERS DATA OPERATIONS DATA SCIENTISTS DATA MANAGEMENT Create Use Update Measure Model Delete
- 7. Lesson 1: Focusing on the Data Supply Chain Matters pg 7© 2018 First San Francisco Partners www.firstsanfranciscopartners.com What is my Business? Finance, Healthcare, Government, Manufacturing, Food – each have different business drivers, models and markets. − Learn them − Continually validate and update your knowledge − Learn how to model this knowledge visually (Maps, Volumes, Trends, etc.) − Then, align their needs to tried and true frameworks Who are my sponsors/stakeholders? Very often the push is coming from either Operations, Finance or both. Sometimes even Technology or Risk. − Operations tends to create a lot of the organization’s atomic data − Finance tends require a lot of the operational data for it’s trends, forecasting and analyses − These typically manifest as data producers & consumers − Technology may behave as an umbrella solution provider
- 8. Lesson 2: Identifying and Linking The Data Producers and Consumers Along a Lifecycle/Spectrum Breeds Engagement and Stewardship pg 8© 2018 First San Francisco Partners www.firstsanfranciscopartners.com Producers & Consumers MUST PROVIDE Focus Clarity Context and Priority Technology SHOULD PROVIDE the solution that delivers business- defined information as an ongoing service
- 9. Lesson 3: Build an Engagement and Action Plan pg 9© 2018 First San Francisco Partners www.firstsanfranciscopartners.com Data Oversight Committee Launch + Quarterly Meetings Establish & Assign BI Platform Business Data Stewards Pre-Assessment BI Platform Workshop Enterprise BI Platform Assessment & Selection Data Oversight Committee Approves 1st Wave Enterprise Data Draft Enterprise Data Policy & Standards Data Oversight Committee Approves Data Access Design by Subject Purchase and Implement Selected Enterprise BI Platform Publish Enterprise Data Policy & Standards Release 1 – Enterprise Data Access Portal to Self-Service BI Platform Publish Enterprise Business Glossary, Metadata, Lineage, & Quality Rules Improve Existing Keystone Foods Enterprise Reporting Q 1 Q 2 Q 3 2018 Q 4 Business Intelligence & Data Services: 2018 Milestones
- 10. Lesson 4: Know and Empower Your User Community You can call them Stewards, Governors, Quality Admins, Analysts, Report Authors, Developers, Data Scientists. − They each have a role in curation and governance − Some will be primarily seeking to determine value and business insight, others are more operational − Learn how they each prefer to work and what constraints they are bound by − Empower them and listen pg 10© 2018 First San Francisco Partners www.firstsanfranciscopartners.com Figureout a waythat lets yourusersdowhat they MUSTdo,whileboth protecting yourfirmAND providinga promotionpath foreach individual’s insights and discoveries.
- 11. Lesson 5: Align Architecture, Analytics and Governance pg 11© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
- 12. Best Practices Listen & Learn (Empathy) − Build Stakeholder Network Demonstrate Comprehension − Quickly Identify Challenges and Opportunities Be Pragmatic − Execute on Actionable Opportunities Engage with Credibility pg 12© 2018 First San Francisco Partners www.firstsanfranciscopartners.com
- 13. Please Share Your Questions and Comments MONTHLY SERIES
- 14. Thank you for joining us today! Our Thursday, November 1 #DIAnaltyics webinar is: Big Data as a Gateway to Knowledge Management. John Ladley @jladley john@firstsanfranciscopartners.com Kelle O’Neal @kellezoneal kelle@firstsanfranciscopartners.com