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Jonathan Moxham, Head of Analytics and Data Strategy, British Red Cross - CDO Europe 2017

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Implementing Data-Centric Transformation at British Red Cross

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Jonathan Moxham, Head of Analytics and Data Strategy, British Red Cross - CDO Europe 2017

  1. 1. 1 Implementing a Strategy for Data Centric Transformation at the British Red Cross
  2. 2. 2 Introduction and context - Red Cross and Red Crescent
  3. 3. 3 British Red Cross – What we do and why we do it
  4. 4. 4 What does that mean in terms of data? Complexity and variety Disparate systems of capture Data quality, people and culture Sensitivity Medical records Destitute individuals personal details Large volumes of individuals and financial transactions 6million supporters on our fundraising database 100millions of marketing approaches and financial donations Data privacy and consent
  5. 5. 5 Earning the Right to Data Centric Growth Revenue growth through Individuals
  6. 6. 6 Earning the Right to Data Centric Growth Change in Leadership
  7. 7. 7 Earning the Right to Data Centric Growth Approach Define the roadmap Build the vision Business Analysis Review Source Systems and Data Planning
  8. 8. 8 Earning the Right to Data Centric Growth Vision Output & Outcome Financial & People Performance Audience Engagement “We will use data to understand outputs, improve outcomes and increase impact” “We will use data to increase access to time, talent and treasure" “We will use data to ensure we are targeting our financial and people resources effectively"
  9. 9. 9 Earning the Right to Data Centric Growth Principles GOVERNANCE STANDARDS ITERATIVE TECHNOLOGY PEOPLE
  10. 10. 10 Earning the Right to Data Centric Growth Key user groups served Pyramid shows recommended breakdown for information consumption. Analyst / Producer User Profile: Analysts derive insight for others to consume Consumption Types: Ad-hoc analytics, data science, report and dashboard creation Example Teams: Innovation and Insight, Fundraising BI Analysts, Finance, Retail, HR and Digital Analysts . Estimated Number of Users: 30 - 50 Insight Consumer User Profile: Role based content with some flexibility where appropriate Consumption Types: Dashboards / Mobile / Some Ad-hoc reporting. Example Teams: Exec Board Directors Regional and Line Managers Estimated Number of Users: 300- 500 Information Consumer User Profile: Extended users with standard output with role specific detail Consumption Types: Role Specific fixed content Example Teams: Service delivery teams Volunteers Estimated Number of Users: 1000+
  11. 11. 11 Earning the Right to Data Centric Growth How it may feel Potential impact on the different roles in the business. CIO CEO I can see that impact we are having with our services across the UK. Exec Director of Services I can see which services are performing well and where we have unmet need. Director of Individual Giving Service Delivery CFO I can effectively measure the financial performance of our social enterprises and cost to deliver our services. I can leverage data from across different Red Cross departments to drive increased fundraising and engagement. Data is secure and well governed. Business users and analysts are enabled through self service. I can see simple metrics on the output and outcomes we are delivering as a team. Service Analyst Finance Accountant I can get quick and easy access to financial data and can drill down to individual transactions to identify route cause. I can quickly access appropriate data across the organisation and my time is spent deriving insight rather than moving and integrating data.
  12. 12. 12 Earning the Right to Data Centric Growth Foundations People TechnologyProcesses & Frameworks People with the requisite skills will maximise the potential of our data. Frameworks and processes will protect the data and ensure we have the right level of quality. The deployment of the right technology will unlock the opportunity to use our data to help us grow.
  13. 13. 13 Earning the Right to Data Centric Growth Summary 1. Vision 2. Understand the current situation – technology, data, people and processes 3. Gain credibility through POC’s - be aware of how to operationally deliver too! 4. Be bold and fearless – you are a change agent 5. Build foundations – data access, data quality, limited data 6. Watch for in-flight data projects – work with your PMO 7. Change is always going to hit some resistance – focus on the change culture 8. Search for a quick visible early momentum – as a lot of the data foundations will take time
  14. 14. 14 Impact of Digital and Data - “Big Data”
  15. 15. 15 Impact of Digital and Data – DW Approach “…data warehousing has reached the most significant tipping point since its inception. The biggest, possibly most elaborate data management system in IT is changing.” GARTNER, “THE STATE OF DATA WAREHOUSING IN 2012”
  16. 16. 16 Impact of Digital and Data – The Challenges
  17. 17. 17 Impact of Digital and Data - the 5 drivers of technology change These factors open up a wealth of different options for storing, analysing and understanding data but they also mean that traditional approaches are no longer optimal…. + + + + Lots of data Fast Networks Commodity Storage Elastic Compute ’Free’ software
  18. 18. 18 Impact of Digital and Data - Evolving Approaches to Analytics EDWs to Data Platform ETL Tool (SSIS, etc) EDW (SQL Svr, Teradata, etc) Extract Original Data Load Transformed Data Transform BI Tools Data Marts Data Lake(s) Dashboards Apps
  19. 19. 19 Impact of Digital and Data - Evolving Approaches to Analytics EDWs to Data Platform ETL Tool (SSIS, etc) EDW (SQL Svr, Teradata, etc) Extract Original Data Load Transformed Data Transform BI Tools Data Marts Data Lake(s) Dashboards Apps Ingest (EL) Original Data Scale-out Storage & Compute (HDFS, Blob Storage, etc) Transform & Load Streaming data
  20. 20. 20 Impact of Digital and Data - Evolving Approaches to Analytics EDWs to Data Platform ETL Tool (SSIS, etc) EDW (SQL Svr, Teradata, etc) Extract Original Data Load Transformed Data Transform BI Tools Data Marts Data Lake(s) Dashboards Apps Ingest (EL) Original Data Scale-out Storage & Compute (HDFS, Blob Storage, etc) Transform & Load Streaming data
  21. 21. 21 SYSTEMS IDENTITY + SECURITY OPTIMISATION STREAM ANALYSIS LOGGING British Red Cross Data Platform – Proof of Concept BRCS MANAGED TOOLSORCHESTRATION DATA LAKE POWER PIVOT / QUERY DATA FACTORY BROWSER LOG ANALYTICS AZURE SQL DATABASE (DATA WAREHOUSE) DATA LAKE ANALYTICS TRANSFORMATION BLOB STORAGE (RAW) REFERENCE DATABASE DATA LAKE STORE (CLEAN & PREPARE) 3RD PARTY / PUBLIC DATA TABLEAU PUBLIC DATA MOBILE LOB’S AZURE ACTIVE DIRECTORY POWER BI EVENT HUB STREAM ANALYTICS BRCS DONATIONS WEBSITE (AWS) STREAMANALYTICS WEB DONATION
  22. 22. 22 Case Study - Website Transformation
  23. 23. 23 Case Study - Website Transformation
  24. 24. 24 Case Study - Website Transformation Real and Near Real Time Data Blob Storage (raw) AWS and Azure API Connector Azure Data WarehouseSQL Database
  25. 25. 25 Case Study - Missing Maps A mapping revolution that is saving lives
  26. 26. 26 Case Study - Missing Maps A mapping revolution that is saving lives
  27. 27. 27 Case Study - Missing Maps A mapping revolution that is saving lives
  28. 28. 28 Thank you For more information, please contact jmoxham@redcross.org.uk | Jonathan Moxham LinkedIn

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