Decentralizing Analytics - A Strategy for Organizing Effective Analytics Teams
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Building an Organization for Functional Analytics ---------------------------------------------------------------------- Many organizations are struggling to figure out how to move ahead with strategic use of data and insights to grow their business. A solid Analytics Strategy seems to elude them. Should they focus on a modern data warehouse in the cloud? Do they have “Big Data”? What about reporting and self-service analytics? How do they deliver information to their customers and suppliers? Which tools are right for them? In this presentation, Ken Raetz will address each of these concerns, outlining a simple, yet functional strategy to building a team and growing the use of analytics in their organization. You will learn: 1. Why centralizing analytics in IT doesn’t work. 2. The roles IT and business play in analytics 3. Selecting tools and processes for analytics 4. Building highly functional teams 5. Partnering with outside vendors to augment team and accelerate early work 6. Analytics Adoption – How to ensure the strategy of analytics continues forward in the years to come
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Decentralizing Analytics - A Strategy for Organizing Effective Analytics Teams
- 1. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Decentralizing Analytics A Strategy That Works Ken Raetz CEO Think Data Insights, LLC © 2019 Think Data Insights, LLC
- 2. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC • Data Platform architects; Azure, SQL Server • Data Storytellers • Power BI • Business Consultants – We see the pain in the processes • IT Consultants – We know the challenges • “Data Culture Disrupters” “Data Wranglers” Who are we?
- 3. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Who are you? Programmer/Architect Executive LeaderSales/Marketing IT Manager/Supervisor Recruiting Data Scientist Business Manager IT/Infrastructure
- 4. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC A little about me… • Have lived in Nashville, TN for 32 years • Married 24 years • I have 4 children • I’m a nerd… I really like technology • I am a small business owner • I love helping entrepreneurs
- 5. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Agenda Our time today… • Traditional Analytics teams – Structure, Roles, Challenges • Analytics market trends • Decentralizing Analytics • Customer Examples • Organizational Strategy • Personal/Individual Strategy
- 6. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 6 Analytics in an Organization Data Management Business Intelligence and Reporting Data Science
- 7. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC UX Designer 7 Analytics Team - Roles Director/ Manager Architect Business Analyst Project Manager ETL/Report Developers DBA/Data Modeler Trainer Quality Assurance
- 8. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 8 Analytics Team - Structure 8 Data Services/ BI Team Shared Resources Other Teams • Director/Manager • ETL Developer • Visualization/Report Developer • Architect • Project Manager • Business Analyst • DBA • Data Modeler • UX Designer • QA
- 9. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 9 Organizational Workflow Company determines objectives Business leaders drive requirements Business requests data result IT-owned BI responds BI Team scrubs and prepares data/report BI Content Developed User Testing/Acceptance Deployment
- 10. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC • Insufficient BI team resources • Poor data quality and lack of integration • Insufficient scalability of the team • Limited user skills (and patience to wait) • So Users wait… 10 Challenges and wait… and wait… and wait… and wait… and do it on their own…
- 11. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 11 Big Data/Analytics Market Trends $189b 2019 $274b 2022 Automation Rise of the data citizen Back to the basics 3rd party data Sources: https://www.idc.com/getdoc.jsp?containerId=prUS44998419 https://www.cio.com/article/3251720/4-data-analytics-trends-that-will-dominate-2018.html?upd=1561460668231
- 12. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 12 Big Data/Analytics Predictions Sources: https://blogs.gartner.com/andrew_white/2019/01/03/our-top-data-and-analytics-predicts-for-2019/ 40% Data Science Tasks Automated 90% Large enterprises will generate revenue from data as a service 20% IT specialists reduction by 2023
- 13. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 13 Big Data/Analytics Predictions • By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency. • By 2023, data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs. • By 2022, 30% of CDOs will partner with their CFO to formally value the organization’s information assets for improved information management and benefits. • By 2023, 60% of organizations with more than 20 data scientists will require a professional code of conduct incorporating ethical use of data and AI. Sources: https://blogs.gartner.com/andrew_white/2019/01/03/our-top-data-and-analytics-predicts-for-2019/
- 14. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 14 Big Data/Analytics Predictions • By 2022, more than half of major new business systems will incorporate continuous intelligence that uses real-time context data to improve decisions. • Through 2020, 80% of AI projects will remain alchemy, run by wizards whose talents will not scale in the organization. • By 2021, analytic projects using quantum computing infrastructure will have outperformed traditional analytic approaches by at least a factor of 10 • By 2022, 30% of consumers in mature markets will rely on AI to decide what they eat, what they wear or where they live. • By 2022, 30% of organizations will use explainable AI models to build trust with business stakeholders, up from almost no usage today. Sources: https://blogs.gartner.com/andrew_white/2019/01/03/our-top-data-and-analytics-predicts-for-2019/
- 15. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 15 Big Data/Analytics Predictions • By 2023, a Fortune 1000 antitrust case will hinge on whether tacit cooperation among autonomous AI agents in competitive markets constitutes collusion. • By 2023, over 75% of large organizations will hire AI behavior forensic, privacy and customer trust specialists to reduce brand and reputation risk. • By 2022, 50% of cloud buying decisions will be based on the data assets provided by cloud service providers rather than on the product capabilities. • By 2023, AI-enabled automation in data management will reduce the need for IT specialists by 20%. • By 2023, 75% of all databases will be on a cloud platform, reducing the DBMS vendor landscape and increasing complexity for data governance and integration. Sources: https://blogs.gartner.com/andrew_white/2019/01/03/our-top-data-and-analytics-predicts-for-2019/
- 16. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 16 Big Data/Analytics Predictions • By 2022, organizations … that dynamically connect, optimize and automate data integration processes will reduce time to data delivery by 30%. • By 2021, enterprises using a cohesive strategy incorporating data hubs, lakes and warehouses will support 30% more use cases than competitors. • Through 2023, computational resources used in AI will increase 5x from 2018, making AI the top category of workloads driving infrastructure decisions. • Through 2022, only 15% of use cases leveraging AI techniques (such as ML and DNNs) and involving edge and IoT environments will be successful. Sources: https://blogs.gartner.com/andrew_white/2019/01/03/our-top-data-and-analytics-predicts-for-2019/
- 17. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC • Data/BI work is often not as exciting • People want to be challenged • Organizational frustration – IT vs. Business • Companies looking for ways to cut costs; reduce traditional teams • When you do your job, BI/Reporting becomes “stable” 17 Ken’s Organizational Observations There is a better way…
- 18. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 18 Decentralizing Analytics – The team of the future Director/Manager Analytics Consultant Data Science Data Storytellers Citizen Data Scientists
- 19. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Citizen Data Scientist
- 20. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Citizen Data Scientist “A person who creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics.” Gartner
- 21. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 21 Organizational Strategy – Where do I start? Approach • Identify/hire/train Citizen Data Scientists in the organization • Build data foundations for clean, accessible and scalable data • Agile, iterative development • Solve immediate challenges • Build toward future strategy • Lean Data Services/BI team – Fewer specialties, more diversity of skills • Commitment to pursue deeper data science • Repair/build relationship between IT/Business
- 22. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 22 Customer Examples – Restaurant/Hospitality West Coast Restaurant Chain • Financial Reporting/Forecasting/Planning App • IT Team involved Finance team (Sr. Financial Analyst) throughout project • IT Team built integrations, central data platform, calculation library Sr. Financial Analyst – Patrick Sr. Operational Analyst – John Citizen Data Scientists in the making
- 23. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 23 Customer Examples – Commodity/Manufacturing Milling – 15 Locations in US • Centralized ERP solution • IT team building one report per request • Deep SQL and SME knowledge required for each report Now? • IT Team led with vision for next generation platform • Move to cloud data platform • Selected different analytics/reporting tool • Focus shifting to strategic approach; • Multiple Citizen Data Scientists developing now
- 24. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Individual/Personal Strategy Executive • Identify data opportunities (monetization, productize) • Topgrade your IT/Business leadership • Budget for exploratory data science • Find/keep Data Services or “BI” Director • Promote culture of Citizen Data Science with peers
- 25. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Individual/Personal Strategy BI Director/Manager • Engage business • Recruit Citizen Data Scientists in business • Data quality and Data governance initiatives • Reduce BI workload/feature requests • Move to Agile approach • Learn the art of data storytelling • Recruit data storytellers
- 26. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Individual/Personal Strategy Operational/Financial Director/Manager • Engage IT and Data Services team • Identify your existing “Power Analysts” • Create backlog of data quality issues; • Take ownership of data quality/governance • Promote best practices to business • Recruit data storytellers
- 27. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Individual/Personal Strategy BI Developer • Learn data science (school, online video) • Learn business – MBA, books, videos • Sharpen data quality, data governance skills • Learn UX principles • Master the art of data storytelling
- 28. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Individual/Personal Strategy Analyst • Learn languages: SQL, DAX, Python, R • Communication skills • IT principles (scale, security, standardization) • Sharpen data quality, data governance skills • Learn UX principles • Master the art of data storytelling
- 29. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC History Lessons
- 30. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC History Lessons
- 31. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC History Lessons
- 32. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC 32 • Speaks business and IT • Rapid solutions • Growing in data science • Adheres to standards • Support data quality initiatives • Trains/mentors others • Promotes culture of Data Democratization Citizen Data Scientist (aka “Data Wrangler” or “Data Analyst”) Analytics – A New Role
- 33. © 2019 Think Data Insights, LLC© 2019 Think Data Insights, LLC Decentralizing Analytics A Strategy That Works Ken Raetz CEO Think Data Insights, LLC QUESTIONS? © 2019 Think Data Insights, LLC
Editor's Notes
- We are a team of seasoned business and technical consultants helping you solve real-world data issues by rapidly delivering high-value data analytic solutions that give your organization a competitive advantage. We shape data culture by rapidly delivering high-value data analytic solutions that solve real-world business challenges and give our customers the competitive advantage they need to thrive in today’s economy.
- Director/Manager Architect Project Manager Business Analyst Database Administrator Data Modeler ETL Developer Visualization/Report Designer User Experience Designer Quality Assurance Trainer
- Full-Time Director/Manager ETL Developer Visualization/Report Designer Shared Architect Project Manager Business Analyst Owner by other teams Database Administrator Data Modeler User Experience Designer Quality Assurance
- Company determines objectives Business leaders/consumers drive requirements IT organization owns data Requests route to BI organization Data Preparation Model development (including semantic layer) Report(s) developed
- Enormous spend Automation of data insights/integrations Outside of IT Basic blocking and tackling (BI/Reporting) Use of 3rd party data
- Est. $22.8b Spending in BI/Analytics Software by 2020 Traditional BI spending declining Modern BI/Analytics platforms emerging Complex datasets driving investment in data prep Streaming/real-time data Cloud platforms Data monetization/productizing
- Est. $22.8b Spending in BI/Analytics Software by 2020 Traditional BI spending declining Modern BI/Analytics platforms emerging Complex datasets driving investment in data prep Streaming/real-time data Cloud platforms Data monetization/productizing
- Est. $22.8b Spending in BI/Analytics Software by 2020 Traditional BI spending declining Modern BI/Analytics platforms emerging Complex datasets driving investment in data prep Streaming/real-time data Cloud platforms Data monetization/productizing
- Est. $22.8b Spending in BI/Analytics Software by 2020 Traditional BI spending declining Modern BI/Analytics platforms emerging Complex datasets driving investment in data prep Streaming/real-time data Cloud platforms Data monetization/productizing
- Est. $22.8b Spending in BI/Analytics Software by 2020 Traditional BI spending declining Modern BI/Analytics platforms emerging Complex datasets driving investment in data prep Streaming/real-time data Cloud platforms Data monetization/productizing
- Team Director/Manager Analytics Consultants (Architects, DBAs, Developers, UX, BA, Designers) Data Science Expertise – Dedicated role or expertise among consultants) Distributed Power Users – aka “Citizen Data Scientists” Data storytellers
- We are a team of seasoned business and technical consultants helping you solve real-world data issues by rapidly delivering high-value data analytic solutions that give your organization a competitive advantage. We shape data culture by rapidly delivering high-value data analytic solutions that solve real-world business challenges and give our customers the competitive advantage they need to thrive in today’s economy.