Why BI Projects Fail and What to Do About It


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Business Intelligence is about changing the business, not implementing technology. Here's a review of what typically goes wrong in analytics projects, and what to do about it.
Full PPT available at timoelliott.com.

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Why BI Projects Fail and What to Do About It

  1. 1. WHY BUSINESS INTELLIGENCE PROJECTS FAIL And What To Do About It Timo Elliott, Senior Director Strategic Marketing timo.elliott@sap.com
  2. 2. INTRODUCTION It’s not only about knowing how to climb… You also have to know how not to fall off
  3. 3. BI Improves Business Performance
  4. 4. Barriers to Deployment Integration Ease of use No clear ROI Data quality Cost of licenses Cost of training
  5. 5. IT Underestimates User Difficulties… Just the right amount of Difficult to find information information is available 60% 60% 55% 50% 50% 40% 40% 32% 30% 30% 24% 22% 20% 20% 10% 10% 0% 0% Executives IT Executives IT (credibility) gap Base: 406 U.S. IT Executives, 675 Business Executives Source: BusinessWeek Research Services
  6. 6. …And Underestimates Value Of BI To The Business The percentage of business users seeing the business impact as significant is 15% higher than the percentage of IT professionals saying the impact on company performance has been significant How successful do you consider How much has BI contributed to your BI deployment? your company’s performance? 80% 80% 70% 70% 60% 60% 50% Business 50% 40% gap 40% 30% 30% 20% 20% 10% 10% 0% 0% Failure Moderately Very Not at All Somewhat Significantly Successful Successful Source: Successful Business Intelligence, Cindi Howson
  7. 7. Timo’s Law of BI “Business people will ALWAYS be dissatisfied with their information systems”
  8. 8. 1. Changing the Business 2. People, Not Technology 3. Process, Not Project 4. Value, Not Cost 5. Insight, Not Data 6. Pragmatism, Not Rigid Process
  10. 10. Aim High Not “implement software” Not “keep the business happy” Aim to transform the way the business works Paint the vision
  11. 11. “Follow the Money” Track information to its final destination in any system Why is it being used What might change as a result
  12. 12. Aim For 100% Deployment Target all uses and users “To be successful with BI, you need to be thinking about deploying it to 100% of your employees as well as beyond organizational boundaries to customers and suppliers” — Cindi Howson 60% 50% 40% Perceived Potential 30% Current % 20% 10% 0% Failure Moderately Very Successful Successful Source: Successful Business Intelligence, Cindi Howson
  14. 14. People Skills Make or Break BI Projects Investment Historical Determinant of 75% of success determined Success by things OTHER than data People 2% 20% and technology Process 2% 15% Organization 2% 10% Culture 1% 20% Leadership 1% 10% Data 10% 15% Technology 82% 10%
  15. 15. IT / Business Relationship Business Person Archetype IT Professional Archetype Extrovert Introvert Sociable Solitary Freewheeling Methodical, systematic, disciplined Risk-taking Risk-averse Prefers face-to-face meeting Minimal face-to-face communication, email and instant messaging is fine Trust and respect
  16. 16. Tough Love “I tried being reasonable — I didn’t like it” Dirty Harry
  17. 17. Choose Your Users Carefully
  18. 18. User Adoption 8-28%
  19. 19. User Adoption
  20. 20. Common User Adoption Issues Training for IT Training on data “Even if an Continued training application is intuitive enough to Best practice be usable without instruction, any Culture related process or culture changes Expectation setting should be driven Ease of use home with at least a quick tutorial.” “What dooms IT projects” August 31, 2005
  21. 21. Congratulations! You’re in Marketing! Evangelize  Promote early, promote often  Name the system  Find successes, keep explaining the value  Highly visible dashboards  Internal seminars  Newsletters  Trophies for best projects
  22. 22. Evangelizing
  23. 23. Evangelizing
  24. 24. Evangelizing
  25. 25. Stories Are Good For Business
  26. 26. γνῶθι σεαυτόν Know Thyself
  27. 27. Information Culture
  28. 28. Information Culture
  29. 29. Information Culture 90% 80% 70% 60% Gut-Feel 50% Fact-Based 40% 30% 20% 10% 0% Failure Moderately Very Successful Successful Source: Successful Business Intelligence — Cindi Howson
  30. 30. Process, Not Project
  31. 31. BI is Designed for Change START FINISH
  32. 32. BI Methodology IT Business
  33. 33. Align With Business Processes Triage Patient Status Nurse Exam Patient Patient Assessment and Room Indicator Arrives Registration and Entry Assigned Changed Physician Physician Labs and/or Lab Report(s) Physician Examines Note X-rays are Returned via Consults with Patient Created Ordered EDIM Patient Patient Discharge Physician Note Prescription(s) Patient Referred for Instructions Completed Written Discharged Follow-up Care Created Electronic History File EDIM Reports Patient Chart is Created/ Leaves ED is Completed Created Printed
  34. 34. Applications
  35. 35. BI Competency Center Leadership skills Link to corporate strategy Alter processes Prioritize and set expectations Analysis skills Relationship skills Gather requirements Summarize and analyze Evangelize Discover and explore Monitor satisfaction Identify data Interpret results Extract data Develop alternatives Validate data Engineering skills Store, maintain, integrate data Implement changes
  36. 36. Incentives and Value Tragedy of the commons Internal pricing
  37. 37. BICC Report Card Active usage Satisfaction New requests Standard reports Applications Service Time
  38. 38. VALUE, NOT COST
  39. 39. What’s the ROI? BI ROI
  40. 40. ROI is Hard to Know in Advance “One of the key contributors to poor IT investment performance is an unbalanced approach taken by executives at the project approval stage. Too often, the overriding emphasis is on quick payback or demands for the return on investment (ROI) to be demonstrated in financial terms.” Gartner, “Total Value of Opportunity — The Real Measure for BI”
  41. 41. Business People Have Short Memories
  42. 42. BI is Becoming Mission-Critical “Many warehouses are now a risk to mission-critical systems that rely on them for data” Gartner, Key Issues for Delivering a Data Warehouse Project, 2008:
  43. 43. Finding Value 4% Technology- related benefits 54% 42% Business process Productivity- enhancements related benefits Previous projects
  44. 44. Finding Value Doing things FASTER
  45. 45. Finding Value Minimizing RISK
  46. 46. Align With the Goals Of the Organization Link BI goals to what executives care about Source: Accenture
  47. 47. Sales Techniques Techniques for understanding executive needs Providing answers to problems, not technology infrastructures Getting your projects to “top of mind”
  48. 48. Turn Information into a Profit Center “Our extranet produced $60M in incremental sales in the first year.” Don Stoller, Owens & Minor
  49. 49. Profitability: a Foundation For Strategic BI “I don’t care about profitability”
  50. 50. Play on Doubt Start asking questions about the numbers that drive the business “You don’t know?!”
  51. 51. INSIGHT, NOT DATA 101011011101001011101011010111010110101011001011010101 101011011101001011101011010111010110101011001011010101 101011011101001011101011010111010110101011001011010101 101011011101001011101011010111010110101011001011010101
  52. 52. Data Integration “This is the aspect that most businesses underestimate drastically — often by 100 percent or more.” Gartner
  53. 53. Lack of Trust 43% of users say they’re not sure if internal information is accurate 77% said bad decisions had been made because of lack of information 5 out of 4 people don’t believe statistics in presentations Business Week study, 2005
  54. 54. Dater Qwality “Poor-quality customer data costs U.S. businesses $611 billion a year. Yet nearly half of the companies surveyed admit they have no plans to improve data quality” The Data Warehousing Institute study © SAP 2009 / Page 58
  55. 55. Data Profiling
  56. 56. Justifying Data Quality Call it Data Governance Risk, Productivity 36% Time Spent on Data Quality 15% 12% 10% 9% 5% 6% 6% 1 hour 2 hours 5 hours 3-4 hours Not Sure 6-10 hours 21+ hours 11-20 hours Source: Harris Interactive Poll
  57. 57. Data Lineage
  58. 58. Go Faster
  59. 59. Faster = Higher Business Value Source: DM Direct, Nigel Pendse, March 2006
  60. 60. Data Misuse and Interpretation
  61. 61. FLEXIBLE PRAGMATISM, NOT RIGID PROCESSES “No plan survives first contact with the enemy” Claus von Clausewitz
  62. 62. Finding An Executive Sponsor Why Should I Care? Track record of IT success Evangelism Company goals His / her career Likely that sponsor will change: build broad base of support
  63. 63. Staying Zen Do “less” Keep it simple Clean up BICC efficiencies IT dashboards Standardize SOA / Web Services SaaS
  64. 64. BI Standardization Calculator
  65. 65. Succeeding Despite Adversity Keep the project up to speed Structure the project into smaller ones Ensure alignment at all times Admit problems fast Stick with it!
  66. 66. CONCLUSION
  67. 67. Selected References “Competing on Analytics” and “Analytics at Work: Smarter Decisions, Better Results” by Thomas Davenport “Successful Business Intelligence: Secrets to Making BI a Killer App” by Cindi Howson “Business Intelligence Competency Centers: A Team Approach to Maximizing Competitive Advantage” by Gloria J. Miller et. Al. “Business Intelligence: The Savvy Manager's Guide” by David Loshin TDWI Best Practices Report 2008: “Pervasive Business Intelligence: Techniques and Technologies to Deploy BI on an Enterprise Scale”
  68. 68. Conclusion BI is not (only) about  Technology  Projects  Cost  Data  Plans
  69. 69. Thank You And Good Luck! Timo Elliott Senior Director, Strategic Marketing timo.elliott@sap.com www.timoelliott.com Twitter/timoelliott
  70. 70. THANK YOU! Timo Elliott timo.elliott@sap.com BI Questions Blog: www.timoelliott.com Twitter/timoelliott
  71. 71. Respect
  72. 72. Mission-Critical
  73. 73. Performance Management “Often we measure the wrong things, in the wrong ways and frequently we measure too much” Andy Neely, Cranfield school of management
  74. 74. Staying Zen Do “less” Keep it simple Clean up BICC efficiencies IT dashboards Standardize SOA / Web Services SaaS
  75. 75. Staying Zen Getting the time and money Do “less” Clean up BICC efficiencies IT dashboards Standardize SOA / Web Services SaaS
  76. 76. Succeeding Despite Adversity Keep the project up to speed Structure the project into smaller ones Ensure alignment at all times Admit problems fast Stick with it!
  77. 77. Competitive Edge is Gained With Analytics High performing companies are 50% more likely to use analytic information strategically Have significant decision- 65% support/analytical capabilities 23% Value Analytical insights to 36% a very large extent 8% Have above average analytical 77% capability within industry 33% Use analytics across their 40% High Performers entire organization 23% Low Performers Source: Competing on Analytics, Thomas Davenport
  79. 79. CFO and IT relationship?
  80. 80. Process, Not Project
  81. 81. WHY BUSINESS INTELLIGENCE PROJECTS FAIL And What To Do About It Timo Elliott, Senior Director BI Strategy timo.elliott@sap.com