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David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man is king

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David Turnbull, cofounder and CCO Snapshot, at Travel Tech Conference Russia 2017 (http://traveltechcon.ru/eng).
"As the debate surrounding the dominance of OTA's and who truly "owns" the customer intensifies, David takes an amusing but critical look at the current state of data management within the hospitality sector and why this is preventing the significant leaps in customer experience achieved by other industries".
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David Turnbull - Hotel data - In the kingdom of the blind, the one eyed man is king

  1. 1. Where Hotels and Great Technology Get Together Travel Tech Conference Russia Moscow 5th October 2017
  2. 2. 2
  3. 3. 3 How to get value out of this?
  4. 4. In the kingdom of the blind, the one eyed man is king desiderius erasmus
  5. 5. Before Now Once, technology favoured companies – now it empowers customers
  6. 6. 1980 1990 2000 2010 Age of Manufacturing Age of distribution Age of information Age of the customer Beyond The age of the customer
  7. 7. Consumers want to be treated like royalty
  8. 8. BIG Data
  9. 9. Big Data is what you call data when it becomes hard to deal with
  10. 10. www.snapshot.travel 10 YOU: 9AM NEXT MONDAY (PART 1)
  11. 11. 11 Where Big Data is used Marketing Everyone Else Finance Effective Use Source: Own potentially biased observations
  12. 12. 12 Where Big Data is used Marketing Everyone Else Finance Potential Use Source: Own potentially biased observations
  13. 13. Businesses often think of BI, Data, Analytics as a set of historical reports and dashboards
  14. 14. HISTORY FUTURE ….But analytics is also about the future
  15. 15. Big data isn’t just about lakes
  16. 16. r ….its also about raging torrents of data
  17. 17. Analyzing data lakes versus streams • Collects data in real-time • Multiple sources of data • Immediately fed to streaming application • Analytics run continuously • Insights used to proactively adjust immediate and future actions • Ingested and stored data warehouse • Multiple sources of data • Analytics run weekly, daily or hourly • Insights used to modify future actions StreamsLakes
  18. 18. Live data is flowing by and value is slipping away
  19. 19. We call these in-the moment advantages: Perishable Insights Insights that can provide incredible value but the value expires and evaporates once the moment is gone
  20. 20. MACHINE LEARNING
  21. 21. MACHINE LEARNING A machine learning algorithm is a system that derives a set of rules based on a set of data It is based on systematic observation, double-checking and cross-validation There is no magic, just data - and without data there is no magic either Programs that write Programs
  22. 22. “ What do you do when you have a problem you cant solve? ” “Just delegate it and make it someone else’s problem! ”
  23. 23. The cloud. Also know as: “someone else’s problem”
  24. 24. “Show me the money value!”
  25. 25. Data Sanity
  26. 26. Esteem Belonging Safety Physiological Self- Actualisation
  27. 27. “Data has Human Needs, too” - Abraham Maslov probably never said this…. but its true
  28. 28. Analysis Storage Collection Prediction Decision
  29. 29. How Data-Driven Decisions CURRENTLY work Computer Collects Human Decides Computer Stores Human Analyzes Human Predicts
  30. 30. Communication Breakdown, Its always the same. I’m having a nervous breakdown, Drive me insane! Led Zepplin
  31. 31. How Data-Driven Decisions REALLY work Computer Collects Human Decides Computer Stores Human Analyzes COMMUNICATION BREAKDOWN Human Predicts!
  32. 32. How Data-Driven Decisions REALLY SHOULD work Computer Collects Computer Decides Computer Stores Computer Analyzes Computer Predicts
  33. 33. 33 How Data-Driven Decisions ACTUALLY Work Dilbert
  34. 34. How Data-Driven Decisions ACTUALLY work • Drill-down analysis ... misunderstood or distorted • Metrics dashboards ... contradictory and confusing • Monthly reports ... ignored after two iterations • In-house analyst teams ... Overworked and powerless COMMUNICATION BREAKDOWN
  35. 35. “Prejudice against algorithms is magnified when the decisions are consequential.” - Daniel Kahneman
  36. 36. 3 6 99.9% of all business decisions can be automated - Everyone at SnapShot, all the time
  37. 37. 3 7 How Decisions are Being Made
  38. 38. 3 8 90% No Decision is made
  39. 39. 3 9 NEW “Making no Decision is a decision. To do nothing. And nothing always brings you nowhere ” - Robin Sharma
  40. 40. 4 0 Business Rules for Beginners . do nothing. Not doing anything is the simplest business rule in the world – And also the most popular
  41. 41. 4 1 9% Decision Follows Rule
  42. 42. 4 2 Advanced Business Rules . Computers are machines following rules. This means business rules are programs.
  43. 43. 4 3 1% Human Decision Making
  44. 44. 4 4 Human Decision Making has two systems – and only one is rational Left brain Right brain
  45. 45. “ The hard problems are easy and the easy problems are hard” Steven Pinker describing Moravec’s Paradox
  46. 46. 65 5 33 15 23 10 5 80 76 99 45 75
  47. 47. 6 27 48 11 30 55 87 91 76 18 1 64
  48. 48. Correct Result
  49. 49. Correct Result 1.045
  50. 50. Can you spot the odd one out
  51. 51. “ All of us would be better investors if we just made fewer decisions ” - Daniel Kahneman
  52. 52. “ I feel deeply uncomfortable with that but it may be that for some tasks machines can make these decisions more effectively and efficiently ” - Daniel Susskind
  53. 53. They are not just faster and cheaper, they are also better at making decisions
  54. 54. “The best chess players in the world are ‘centaurs’, amalgamated teams of humans and algorithms”
  55. 55. “ More than 40% of the actions people performed each day aren’t actual decisions, but habits ” - Charles Duhigg
  56. 56. Its officially time to FREAK OUT
  57. 57. The Hotel Conundrum
  58. 58. DATA IS THE NEW SOIL David McCandless
  59. 59. YOU: 9AM NEXT MONDAY (PART 2) Where is the updated budget? I emailed it, but use the 9am one, not the 8:55 am one… Is that the one called “final”? No, the one called “FINAL FINAL”. Never mind, I’ll send it again.
  60. 60. Friction
  61. 61. Take Aways
  62. 62. KEEP CALM AND CURATE YOUR DATA YOUR DATA
  63. 63. Analysis Storage Collection Prediction Decision
  64. 64. Gather all your data for one arrival date and prepare it for deeper analysis
  65. 65. Now analyze the heck out of it – every which way
  66. 66. Executability Understandability Predictability Data Availability
  67. 67. DATA IS THE NEW SOIL David McCandless
  68. 68. 7 3 w w w . s n a p s h o t . t r a v e l

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