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Mike Palladino: Adapt, Adopt and Thrive: The Robot Revolution, Agile and their Impact on Your Profession

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Mike Palladino: Adapt, Adopt and Thrive: The Robot Revolution, Agile and their Impact on Your Profession

Mike Palladino: Adapt, Adopt and Thrive: The Robot Revolution, Agile and their Impact on Your Profession

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Mike Palladino: Adapt, Adopt and Thrive: The Robot Revolution, Agile and their Impact on Your Profession

Global Online PMDay 2022 Summer

Website: https://opmday.org
Youtube: https://www.youtube.com/channel/UCeHtPZ_ZLZ-nHFMUCXY81RQ
FB: https://www.facebook.com/edunomicaone

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Mike Palladino: Adapt, Adopt and Thrive: The Robot Revolution, Agile and their Impact on Your Profession

  1. 1. UA Project Management Day 2022 1 Adapt Adopt and Thrive: The Robot Revolution, Agile and the Impact on Your Profession Mike Palladino, PMP, CSM Ø Director, Enterprise Agility, Bristol Myers Squibb Ø International Keynote Speaker | Webinar Presenter Ø Adjunct Professor, Villanova University Ø Author, Data Management University Ø Past President, PMI-DVC chapter
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  5. 5. UA Project Management Day 2022 5 Adapt Adopt and Thrive: The Robot Revolution, Agile and the Impact on Your Profession Mike Palladino, PMP, CSM Ø Director, Enterprise Agility, Bristol Myers Squibb Ø International Keynote Speaker | Webinar Presenter Ø Adjunct Professor, Villanova University Ø Author, Data Management University Ø Past President, PMI-DVC chapter
  6. 6. Welcome to 4th Industrial Revolution!!! 6
  7. 7. In-depth Research Watched one movie So, what becomes of the humans? 7
  8. 8. Batteries for Robots 8
  9. 9. Conclusion? The Robot Overlords will take over in the future Some time in the future Humans are Free Human are Batteries Stop 9
  10. 10. Not Good Enough 10
  11. 11. Results 539 Movies Negative outlook Happy outlook 532 7 11
  12. 12. Got Me Thinking 12
  13. 13. Value of Humans? • Adapt to environment • Adopt new change • Thrive in the future Some time in the future Humans are Free Human are Batteries Stop Humans adapt, adopt and thrive X 13
  14. 14. No Humans, AI is Still Pretty Stupid “Our most advanced AI systems are dumber than a rat” AI Humans 14
  15. 15. Recent Automation at West Coast Ports “West coast ports added automation 10 years ago. There are now more jobs than before automation.” “How to balance a higher demand with a labor shortage.” From a conversation with Anthony Chiarello, former CEO of TOTE Maritime, May 6, 2022 15
  16. 16. Areas that are Difficult to Automate 16
  17. 17. AI Doesn’t Think the Same Way Increase Speed 17 • Don’t lose level 2 • Don’t lose at all • Don’t get killed
  18. 18. Additional Articles - Concerns “Labor vs machines. An employment puzzle” “A revolutionary decade in machinery emphasizes anew the discarding of men displaced in history” “President ranks automation first as job challenge. Burden of finding work for youths and those displaced by machines” “Automation report sees vast job loss” “In concrete constructing, building materials are mixed, like dough, in a machine and literally poured into place without the touch of a human hand” Jun 1, 1930 Feb 15, 1962 Feb 26, 1928 New York Times articles 18
  19. 19. Forgotten Past Revolutions What happened to the previous jobs? 19
  20. 20. Horses in New York City - 1900 A Lot of Horses • 200 000 horses in New York City • 7 - 16 kg of manure per day • 1.4 – 3.2 million kg of manure per day • 1500 – 3500 tonness per day • In 1880, 15 000 dead horses removed New Jobs Created 1908 Cars started to arrive – Panic. What will all these people do? 20
  21. 21. Job Loss vs Job Gain New Technology Expand Lower Prices Lost Jobs New Jobs New Jobs New Jobs Tech Suppliers New Industries We Buy More We Buy Other Things Higher Productivity 21
  22. 22. New Jobs and Industries Created 22
  23. 23. Quick Math - Driverless Car • Ukraine: 9 100 000 cars on the road • Replacement rate: 1% per year Ø 82 000 vehicles per year • How long to convert? Ø 110 years • Real challenge: 110 years with both human and automated drivers Question: What about Motorcycles? 23
  24. 24. Sewing Machines First commercial models 1844-1851 Women spent time sewing clothes, or hiring a seamstress Time to Create Before Sewing Machines After Sewing Machines Shirt 14 hours 1 hour 15 minutes Dress 10 hours 1 hour Pants 3 hours 38 minutes 24
  25. 25. The Great Sewing Machine Riots of 1830 1830, Barthelemy Thimonnier had a factory with over 80 machines Factory was destroyed by a riotous group of French tailors 25
  26. 26. Problem with Predictions • Missing the context • May not include the bigger picture • ”Those who don’t know history are doomed to repeat it” – Edmund Burke • Example: What can happen if we use data from only the past few months 26
  27. 27. The Great Sunlight Leakage Crisis • Started in July • Ukraine is loosing about 2 minutes of daylight per day • AI model predicts total darkness by June • Affects the entire Northern Hemisphere • Daylight is leaking to the Southern Hemisphere • They are gaining about 2 minutes of daylight per day • We must “Do Something”!!!!!! • Give me money, I might be able to reverse the trend by December 27
  28. 28. Time Savers - Prediction In Progress 40 years ago - Paperless Society 29 “I’ve had it with this kitchen!” “I don’t think I’m quite ready for society to go totally paper-less!” “Ding. You’ve got mail” “436 unread emails” 29 50 years ago - Laborless Kitchens
  29. 29. Poor Track Record for Predictions Professional stock pickers Monkeys throw darts to pick stocks Results? “How are those revised projections coming along?” 30
  30. 30. Poor Track Record for Predictions American football • Each division has 4 teams • Eliminate the obvious bad choice • Chances of picking the correct team: 33% • Accuracy of Professional Football Analysts? 36% 31
  31. 31. Predicting the End of the World 100 AD 2000 2022 The latest Predictions - 2022: Nostradamus - large meteorite or asteroid - 2026: Asteroid collisions or over population - 2030: Mass extinction - 2017: to 2113: Several predictions about Asteroids - 2280: The world will simply end, no reason given - 2525: Either human race is extinct, or may take another 7,475 years 1000 Hundreds Accuracy? 0% 32
  32. 32. Padding Predictions With Extra Time Predictions are made far into the future Nov 8, 2017 - Stephen Hawking: “…less than 600 years until Earth becomes a sizzling fireball” “ NASA - Galaxies will collide in 4 billion years” “ The END is Thursday. The END is Near. ‘Amateur’ ” 33
  33. 33. Excuses • “Unpredictable factors, such as the weather” • “No one else could have predicted …” • “My prediction was right, but my timing was off” • “Nobody knows the time of doom in a strict manner” • “The evidence was not incorrect, but was not fully predictive of what was going on” • People’s fears don’t add up • 80% of people à robots will take over 50% of the jobs • 80% of people à but not their jobs 34
  34. 34. Why Are We So Bad at Predictions? • Strong incentives to make extreme predictions • Must be original, different, and stand out • Only need one correct extreme prediction • What are the penalties for bad predictions? • None • Romania to punish bad predictions - 2 years in jail 35
  35. 35. Perspective – More Complicated 36 “Something’s just not right – our air is clean, our water is pure, we all get plenty of exercise, everything we eat is organic and free-range, and yet nobody lives past thirty.” “Should we pick up something for the folks who don’t eat red meat?” 36
  36. 36. We Don’t Know What We Think We Know Pyramids – 2750 BC Walking on the Moon – 1969 AD Cleopatra – 69 BC Cleopatra lived 700 years closer to present day than the pyramids Nationality à Greek! 37
  37. 37. We Don’t Know What We Think We Know Population Size • 7 Billion people fit within Ukraine with 86 sq. meters each • The United States alone can feed 9 Billion people • 100 Year land give back Population Growth 1939 London 8.6 M à 2015 London 8.7 M 1921 Paris 2.9 M à 2009 Paris 2.2 M 1939 Berlin 4.3 M à 2015 Berlin 3.5 M 38 38
  38. 38. We Are not Good with Amounts and Sizes 103 1015 1018 106 109 1012 1021 1024 Grains of sand on all beaches Stars in the visible universe Insects for every human Trees on Earth Stars in the Milky Way Galaxy Synapses in the brain Atoms in a molar gram of matter 200 x 106 100 x 109 3 x 1012 125 x 1012 1.0 x 1024 6.02 x 1023 7.5 x 1018 39
  39. 39. Nor Graphs 40 Population replacement rate: 2007: 2.10 2022: 1.64 “There are not enough people” – Elon Musk, April 15, 2022
  40. 40. Irrational Decision Making • People make irrational decisions • ”Gut” feel • Emotional appeal • Perceived value • Relative decisions easier than absolute decisions 41 “How Marketing Works” 41
  41. 41. Picking Magazines Digital only Version: ₴ 3300 /year Digital and Paper Version: ₴ 3300 /year 10% 0% 90% The Economist Paper only Version: ₴ 1600/year 42
  42. 42. Picking Magazines Paper only Version: ₴ 1600 /year Digital only Version: ₴ 3300 /year Digital and Paper Version: ₴ 3300 /year 60% 0% 40% X X The buying habits changed The Economist 43
  43. 43. Picking Magazines Paper only Version: ₴ 1600 /year Digital only Version: ₴ 3300 /year Digital and Paper Version: ₴ 3300 /year 10% 0% 90% The buying habits reverted to the original Even though no one buys the Digital only Version The Economist 44
  44. 44. Where Does This Leave Us? • The world is changing. It has always changed • People cannot reasonably predict the future • People have always worked together • And will continue to work together • How do we… • Interact better • Solve problems better • Communicate better 45
  45. 45. Continual Learning Are we… • Continually learning in our profession? • Continually learning in our industry? • Trying new approaches? • Improving existing techniques? Or are we ”too busy” 46
  46. 46. Agile Manifesto While there is value in the secondary items, we value the primary items more Individuals and interactions over processes and tools Working solution over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan Agile Manifesto 47
  47. 47. Agile Principles 48
  48. 48. Communicating Clearly • Summarize complex data • 80% communicating • Understand and speak to the audience • Short and to the point • Simple, clear words 49
  49. 49. Warning: Dangerous Chemical!!!! Dihydrogen monoxide (DHMO) • Also known as hydroxyl acid, and is a major component of acid rain • Can cause sever burns • Contributes to the erosion of our natural landscape • Accelerates corrosion and rusting of many metals • May cause electrical failures and decreases effectiveness of automobile brakes Often used in: • Industrial solvent • Nuclear power plants • Distribution of pesticides. Even after washing, the product remains contaminated by this chemical • Additive in certain junk food and other food products • Has been found in every single household around the world http://www.dhmo.org 50
  50. 50. More Warnings 51
  51. 51. Unbelievable!!! 52
  52. 52. Danger!!! 53
  53. 53. Ban Dihydrogen Monoxide Who will sign a petition with me to ban Dihydrogen Monoxide? • Di – hydrogen, Mono - oxide • 2 Hydrogen, 1 Oxygen • 2H, O • H2O • Water 54
  54. 54. More Warnings Water Water 55
  55. 55. Unbelievable!!! Water 56
  56. 56. Danger!!! Water Water 57
  57. 57. Status Reporting • Audience: sponsors, stakeholders and executive leadership • What are the key risks and issues they need to know • What do I need them to understand? • What do I need them to do? • Time spent reading is inversely proportional to content 58
  58. 58. Influencing Others Still need to work with people • Build trust early and often • “Help me understand…” 59
  59. 59. Trust - Getting to Know Each Other • Initial Introductions • Thank-you card • Thank you at work • Team “group photo” 60
  60. 60. Name Role Name Role Name Role Name Role Name Role Name Role Name Role Name Role Name Role Name Role 61 The Team!
  61. 61. Conclusion - Predictions • So, don’t worry • Unrecognizable change will occur and has occurred • Top 10 jobs didn’t exist 10 years ago • “We are currently preparing students for jobs that don’t yet exist… • Using technologies that haven’t been invented… • In order to solve problems we don’t even know are problems yet.” – Fisch and MeLeod 62
  62. 62. Conclusion - Predictions • Beware of predictions made by “professionals” • Predictions ß à Guessing • Extreme predictions are amplified 63
  63. 63. Conclusion – Our Benefits and Learning • Still comes down to how we interact with people • Build trust • Work as a team • Communicate simpler • Continue learning to stay relevant 64
  64. 64. Conclusion Adapt Adopt And Thrive 65
  65. 65. UA Project Management Day 2022 66 Thank you! Questions ??? Comments ??? Дякую www.linkedin.com/in/mikepalladino

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