Giving Technical Presentations

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Thoughts on presenting technical (scientific) information.

Text of Giving Technical Presentations

  • 1. Giving technical presentationsMaterial prepared by Mike K Smith

2. Inspiration (blogs)Presentations: Nancy Duarte: Duarte blog Garr Reynolds: Presentation Zen Chris Atherton: Finite Attention Span 3. There are 300 millionPowerPoint users in theworld*Death by Powerpoint* Estimate 4. There are 30 millionpresentations every day*Death by Powerpoint* Estimate 5. About a million presentationshappening right now** EstimateDeath by Powerpoint 6. 50% of them areunbearable.** Conservative estimateDeath by Powerpoint 7. Think of a presentation that hasmade an impression on you.Q: What is it about thatpresentation that made it stick inyour mind? 8. PREPARATION!! 9. Preparing effectivepresentations takes time. 10. Your presentation is aboutmarketing 11. Your work / YOU as a brand. 12. Your organisation.Your project team. 13. WHY are you presenting? 14. WHO is your audience? 15. WHAT do THEYwant to know? 16. Peer Reviewvs.Decision Making 17. Peer ReviewYou want: Input and technical review Validation of your work New ideas for future work Recognition for good work / increasedvisibility. 18. Peer ReviewThe audience wants: New ideas Solutions for their problems Recognition for THEIR work / increasedvisibility! 19. Decision MakingThe audience wants: To make a decision based on bestavailable information. A clear recommendation. Impact of making the wrong decision. Confidence that the technical informationis valid / applicable etc. 20. Decision MakingYou want: Your technical input to influence thedecision. Credibility with decision makers Recognition for your work / increasedvisibility. 21. Attention! 22. Your brain is lazy, shallowand easily distractedChris AthertonOoh,look...A hypertextlink! 23. http://www.slideshare.net/CJAtherton/chris-atherton-at-tcuk09 24. However, your brain CANprocess two things at once(even if youre male).http://www.slideshare.net/CJAtherton/chris-atherton-at-tcuk09 25. Dont max out both inpresentations.http://www.slideshare.net/CJAtherton/chris-atherton-at-tcuk09 26. 5/16/2013 Pharsight and Pfizer ConfidentialpPain Relief, P(Y=1), and Recurrence, P(T>t), modelsModel parameters are estimated using nonlinear mixed effects modelanalysis (NONMEM V) Pain Relief Model Logit transformation Placebo model Drug model Effect site concentration Subject specific random effect Recurrence Model Hazard model LikelihoodYedp +)(Cf+t)f=)}Yg{P( (1)-e(Atrialbase)-e(A(t)f dosendtttp)(-kdose2pl,-kpl2plndpl11+= )()()(tCpekeotCeCeslCeftkeond),0(~ 2 N(u)du)(-=S(t)=t)>P(Tt0exp)}1({)log( YPghzhz(t) si))1/(log(}{ xxxg L = P(T,Y| )P( )d = P(T|Y, )P(Y| )P( )di=1Ni=1N YAWN! 27. Feels likehttp://www.flickr.com/photos/pauldrabek/1284981253/ 28. http://www.slideshare.net/CJAtherton/chris-atherton-at-tcuk09Remember! 29. Insects are all around us The cricket is very sensitive totemperature. You can tell the temperature usingcrickets. Count the number of chirps in 15 secondsand add forty. The resulting number is very close to thetemperature in fahrenheit. 30. http://www.slideshare.net/CJAtherton/chris-atherton-at-tcuk09 31. Your brain can read fasterthan the presenter can talk. 32. http://www.flickr.com/photos/26883252@N08/3284112021 33. Technical Presentations Read manuscripts 34. Manuscript structure IntroductionMethods Results Discussion Conclusions 35. Skip to the end... 36. "Technical presentationsshouldnt be a mystery novelwhere you wait to see whodunnit.Having the conclusion upfronthelps people put the informationthat comes next into context". -Olivia Mitchell 37. Peer review structure Introduction / Motivation Premise / Conclusions Methods Results Applicability / Applications Discussion, assumptions, caveats, etc. 38. Decision making structure Introduction / Motivation Recommendation (Suggestedactions) Results (Evidence) Discussion, assumptions, caveats, etc. Methods 39. Clear motivation is important. 40. Why is this important?Why does it deserve apresentation?Why am I giving up my time? 41. What do you need me to do?Is this for information?Do you expect a decision?Do you want input? 42. Engagement! 43. Huh? What was he saying? 44. Make your message sticky. 45. You CAN engage your audienceon technical stuff without losingtheir attention. 46. Story / NarrativeA sequence of unconnected factsis hard to hold in your head. 47. Symphony / GestaltWhat is the whole?AKA The BIG PICTURE 48. EmpathyWhy should we care about makingthe right / wrong decision?Why does matter? 49. Simple languageConversational.NOT corporate. 50. What are the 4-5 things you wantthe audience to recall later? 51. Everything else is backup. 52. But what about the details? 53. If you need to share LOTS oftechnical info, write amanuscript (or an executivesummary) 54. If you show tables / graphs... 55. Make them legible. 56. Make them intelligible 57. Avoid the audience asking:What the **** is that picture?ORWhy the **** is that picture there? 58. 01020304050607080901st Qtr 2nd Qtr 3rd Qtr 4th QtrEastWestNorthInterpret this graph in the next 10 seconds 59. 01020304050607080901st Qtr 2nd Qtr 3rd Qtr 4th QtrEastWestNorthIs THIS important? 60. 01020304050607080901st Qtr 2nd Qtr 3rd Qtr 4th QtrEastWestNorthIs THIS important? 61. 01020304050607080901st Qtr 2nd Qtr 3rd Qtr 4th QtrEastWestNorthDe-emphasise what you dont need 62. Are equations EVERREALLY necessary?Keep em simple.Highlight the key points. 63. 5/16/2013 Pharsight and Pfizer ConfidentialpPain Relief, P(Y=1), and Recurrence, P(T>t), modelsModel parameters are estimated using nonlinear mixed effects modelanalysis (NONMEM V) Pain Relief Model Logit transformation Placebo model Drug model Effect site concentration Subject specific random effect Recurrence Model Hazard model LikelihoodYedp +)(Cf+t)f=)}Yg{P( (1)-e(Atrialbase)-e(A(t)f dosendtttp)(-kdose2pl,-kpl2plndpl11+= )()()(tCpekeotCeCeslCeftkeond),0(~ 2 N(u)du)(-=S(t)=t)>P(Tt0exp)}1({)log( YPghzhz(t) si))1/(log(}{ xxxg L = P(T,Y| )P( )d = P(T|Y, )P(Y| )P( )di=1Ni=1N 64. Same for tables of numbersWhich numbers changed?By how much?Why? 65. HELP the audienceto understand 66. IN SUMMARY: 67. Prepare Know your audience Know why youre presenting Know what the audience expects 68. Attention Dont fire-hose your audience withinformation. Keep slides simple Back up presentation with additionalmaterial (exec summary / manuscript /blog) 69. Engage How do you want your audience to recalllater? Make it as easy as possible to recall Slide format Story / gestalt / empathy / simple language 70. Further reading (blogs)Presentations: Garr Reynolds: Presentation Zen Nancy Duarte: Duarte blog Chris Atherton: Finite Attention SpanOther: Guy Kawasaki: How to change the world Seth Godin Kathy Sierra: Creating Passionate Users 71. BackupAKA: Mikes rants aboutpresentations 72. Things I hate to hear inpresentations:(And how it translates to theaudience) 73. Most of you will have heardthis talk before 74. Im going to have to skip ahead,because time is short[Followed by in-depth discussionof every bullet point] 75. OK, lets skip to theconclusions[Skips fifteen slides] 76. What you say: I know thisslide is hard to read 77. This slide intentionally blank 78. You dont have to use thetemplateThe following templates areHONESTLY straight fromPowerpoint default templates 79. 16/05/2013 80How to communicate bad news State the bad news Be clear, dont try to obscure thesituation 80. 16/05/201381Goal and Objective State the desired goal State the desired objective Use multiple points if necessary 81. Is the slide background hideous? 82. Avoid comedy fonts. 83. Will yourdocumentbe viewed bythe public?Should I use theComic Sans font?Dont use Comic SansNOYES 84. Are you colour-blind?Is your audience? 85. Pie charts are mostly useless 86. Pie charts are mostly uselessLooks likePacmanDoes not looklike Pacman 87. 3D charts are even more useless 88. ABSOLUTELY NO animation.BTW what the HECK is that?!and WHY is it in my slide? 89. Keep builds to a minimum.Theyre distracting.Really distracting.And they confuse the presenter. 90. DO NOT use random. EVER.dont use more than oneWhatever you dotype of effect.