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Best Practices to Drive Business Intelligence User Adoption
This document discusses best practices for driving business intelligence user adoption. It recommends taking a consumer-oriented approach that involves defining user personas based on traits like their role and how they interact with data. Examples personas discussed are "Ted the Headliner" who needs visual reports on mobile devices, "The Monk" who is detail-oriented, and "Sergei the Data Scientist" who focuses on data exploration. Defining personas helps tailor reporting, visualization, and tools to individual user needs and avoid issues like poor performance or lack of mobile compatibility.
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Best Practices to Drive Business Intelligence User Adoption
- 1. Best Practices toDrive Business Intelligence User Adoption Notes: If you experience audio issues during the webinar, you can dial in through telephone details provided to you in your registration confirmation email. Please feel free to post questions in the questions dialog and we will try to answer as many as we can at the end. Recording of this session will be shared in next 24-48 hours. You can also write to us at marketing@winwire.com for any clarifications or information.
- 2. Session Speaker Srini Pattabi VP- Analytics & Information Management WinWire Technologies
- 3. Why BI ProjectsFail…
- 4. Sifting from thenoise…
- 5. What is “Business” Afaceless, featureless entity? Business User Power User Executives IT You have a rich choice of 4 to pick from!
- 6. Traditional Approach on‘Users’ Data is the center of universe Users are described based on ‘permissions’ requirement What are the fields and columns required in the report: • Excel is used to create a mock-up • Colors, Navigation and other “minor” details are discussed during UAT What information do you want? Business Analyst and Developer interaction: relatively silo’ed approach Delivery channels are explicitly part of the requirements discussion
- 7. Engineer’s View vs.User’s View
- 8. What is thepoint? Declutter, Organize, Simplify Interaction with the data Amplify Cognition 2 31
- 9. In The ConsumerOriented Approach
- 10. Introducing Personas –User Traits Status Reporting Diagnosis Explanation ExplorationVisual Cues Detail Oriented Monitoring Tracking High Latency Tolerance Low Latency Tolerance • Visualization • Delivery channel • Delivery (Reporting) tool choices • Aggregation strategy
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- 12. Meet “Ted” TheHeadliner Implications • Manages a large team over a wide spread of either geography or business areas • Is always on the ‘Go’: Typically runs from one meeting to another or is on the ‘Field’ • Not a micro-manager but would like to be in the know alwaysBusiness User • High Availability of Reports • Visualization that delivers ‘Headlines’ efficiently • Most likely a Tablet/ Mobile device user – reports/ dashboards should be form friendly • Limited drill down capability required Relies more on visual cues
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- 14. Meet “The Monk”:The Perfectionist Implications • Manages a critical business function – typically manages operations • Highly detail oriented and would like to understand granular data of the report • Spends long hours in office • A high laptop device user • High Availability of Reports • Less visual, more data but efficient navigation • Multi-level drill down to most granular data • Typically high volume data reporting Relies on granular data Business User
- 15. Say Hello toSergei, The Data Scientist! Power User Implications • Likely a direct-report of a ‘powerful’ executive • Does special projects and has the trust of a power center • Very tech-savvy and has good sql and reporting skills – uses prescriptive data analysis tools • A high volume data cruncher • Access to a rich semantic layer and/ or data discovery platform • Need more of data extracts and self-service capabilities than canned reporting • Focus more on data quality and lineage • Tool-sets should data exploration capable Just give them the data!
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- 17. Say Hi toJenny, The Story Teller! Implications • Typically a Business Analyst/ Data Analyst • Answers business questions mostly using descriptive data analytics techniques • Has strong SQL skills but mainly uses Office automation tools for data presentation • Charter to prove / disprove hypothesis than formulating one • Access to a rich semantic layer and/ or data discovery platform • Need strong data visualization tools that help answer business questions • Access to additional sources of data than only Data warehouse Need a Narration tool Power User
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- 19. Interaction with data GoodVisualization Poor Visualization
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- 21. Innovate & IterateMethodology
- 22. Some Pitfalls thisapproach helps avoid The Performance Trap Dashboards that drill into 1000’s of granular records
- 23. Some Pitfalls thisapproach helps avoid Form vs. Function Laptop friendly functions does not meet Tablet friendly form
- 24. Some Pitfalls thisapproach helps avoid Fear of the Unknown Scaling new ‘Skill-set’ entry barrier
- 25. In Summary We demanda personalized attention as consumers!... …Yet end up delivering a mass marketing like treatment Information is also a ‘consumable’ …We as BI Leaders are the purveyors of the same Let us bring ‘Business’ back into BI !
- 26. Who We Are ITsolutions company making information actionable for the enterprises in the mobile-cloud world Collaborative and Analytics solutions leveraging pre-built solution accelerators Cloud, Collaboration & Analytics Technologies Mobility,
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