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Analytics and Witch Doctoring: A Cure for the Black Box Mentality

Analytics and Witch Doctoring: A Cure for the Black Box Mentality. February 1, 2011 O’Reilly Strata Conference J.C. Herz, Batchtags LLC jc@tripledex.com. Analytics: An Intervention. Original Sin. Enterprise Pathologies. Critical Questions. Analytics: Occult Phenomenon. Very powerful

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Analytics and Witch Doctoring: A Cure for the Black Box Mentality

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  1. Analytics and Witch Doctoring: A Cure for the Black Box Mentality February 1, 2011 O’Reilly Strata Conference J.C. Herz, Batchtags LLC jc@tripledex.com

  2. Analytics: An Intervention • Original Sin Enterprise Pathologies Critical Questions

  3. Analytics: Occult Phenomenon Very powerful Don’t understand it Practitioners possess arcane knowledge

  4. Alchemy

  5. SecretAlgorithms

  6. Greek Letters Are Your Kryptonite

  7. High Status Helplessness • If you understood the technology, you’d be one of those people whose job it is to make technology work. • You know, underlings

  8. Executive ADD - Kaching! • Re-starts are where consulting shops make their money

  9. Mid-Life Crisis

  10. Shiny Pebble Syndrome • Infoviz Porn: Visualization with no use case • Ex: Social Network visualization. Why? • START with a use case and work forward • Demo Envy: just because it looks slick doesn’t mean it’s possible, or even advisable, to pipe your data into it.

  11. A Ballad of Spectacular Information Display • Time Magazine 1976 • Telex text routing: information off the wire goes to terminals, properly foldered • Z8 terminal display awes executives • Pneumatic system not eliminated

  12. Technical Reality vs. Leadership Attention Span

  13. Half Ass Syndrome • Halfway into the project, jump off into the next problem. • Haven’t refined results or hypothesis • Failure blamed on technology, but it’s really loss of interest and desire for instant gratification

  14. Shelfware Syndrome • The guy who was driving the program left... • Approach-Avoidance conflict --> pilot-itis • A US agency has $30M of software that hasn’t been installed…some of it with maintenance contracts. • Base Model vs. Fully Loaded • One enterprise bought $12M worth of Autonomy before figuring out that the add-ons they needed would be another $22M.

  15. Customization Before Testing

  16. Critical Question: What is the Validation Test? • Formulating the validation test keeps both the customer and the developer focused - and honest • Suggest pay for performance, and see if the developer or vendor freaks out. • Make sure validation is ongoing - in case the ground is shifting

  17. Data Due Diligence & Auditing

  18. Shame Shame

  19. Ugly Babies

  20. Critical Question: Data Quality • How complete is it? • Ex: 600 custom fields, only two have more than 50% coverage • How accurate is it? How do you know? • How consistent is it? • Good test: make three calls to different parts of the company, to get an answer to a factual question that doesn’t require calculation.

  21. Critical Question: Half-Life of Data • How long is the data accurate? • How long is the data useful?

  22. Critical Question: Real World Context • Without real world data, “behavioral” metrics are misleading • Where is the transactional data that validates insights from non-transactional data? • How would you prove the magic analytics WRONG?

  23. Data: Gut Check • Are you prepared to spend painful amounts of money cleaning up your data? • Crack heads if people don’t share data? • Make business units accountable for their data? • Play hardball to make sure data is not stored in single-application proprietary formats?

  24. Critical Questions: Workflow • What workflow changes will this proposed capability require? • People hate changing their workflow, even if it’s an improvement • Never attribute to stupidity what can be attributed to laziness • What is your plan for changing workflow? How do you enforce it?

  25. The perfect application that no-one uses is still worthless

  26. Process

  27. Politics

  28. What are you prepared to do?

  29. Critical Question: Consequences • What actions are you willing to take on the basis of validated analytic insight? • Change your product? • Change your marketing budget? • Change people’s job descriptions? • Re-allocate R&D budgets? • What actions are you not willing to take?

  30. Stakes

  31. Critical Question: Tempo • How fast will a decision be made on the basis of analytic insight? • Quarterly? • Daily? • Within seconds? • Milliseconds? • Never? • Realtime vs. Continuous vs. Batch

  32. Precision vs. Accuracy When precision exceeds accuracy, you’re setting yourself up for analytic failure

  33. OODA Loop Which of these does an analytic tool/technology do?

  34. Before You Rip ‘n’ Replace:What is the exit cost of this technology?Does “turnkey” mean monoculture?

  35. Business Payoff vs. Intellectual Appeal Market Segmentation 360º Lead Scoring Operations Research Competitive Intelligence Validate Marketing Effectiveness Social Network Analysis Pilots to test new analyst tools with tiny amounts of generic data

  36. Questions? • J.C. Herz jc@tripledex.com (202) 213-3151

  37. Base Model vs. Fully Loaded

  38. “Never attribute to stupidity what can be explained by laziness.”

  39. Ugly Babies & Pretty Babies

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