Leifer strelka moscow sides 11jul2011
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Prof. Larry Leifer presentation on design thinking at Strelka Institute

Prof. Larry Leifer presentation on design thinking at Strelka Institute

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  • 1. !"#$%#&(%)*"+,%&-%). !"#$#$%!&()$*+),-$-"+) .+/&()$*&0&()&)123#) ) /"00./1%210 2+$+"),#").+/&()"+/+1"2*)4)/$1,#".)-&5+"/&$%) /$"+6017)8#/2#93::);-6%)<=::)
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  • 9. accelerated learning
  • 10. defying gravity
  • 11. $01"7#&"+,%&-%).
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  • 13. 6*9-/!%,1 "# :=< 6*"41! 90 :;< 6*"41! 41069# )9!".
  • 14. 6*"41! :=<In-depth knowledge
  • 15. Design Thinking Behavior In-depth knowledge :;< 6*"41!
  • 16. (*.%6%)69*"0! Design Thinking Behavior In-depth knowledge )9,1"&%/1"!"4781:;<41069#6
  • 17. FORESIGHT DESIGNthinking & doing thinking & doing people have different ways of thinking, working, doing, and learning (Lande 2009)PRODUCTION ENGINEERINGthinking & doing thinking & doing
  • 18. BRIEF BENCH RESET NEED IDEATEFORESIGHT DESIGN EXPERI way points PROTO along the TEST passage from a concept to the functional CFP proof-of-concept FUNKY prototypePRODUCTION ENGINEERING SYS SEND FUNCT OUT SYS PRE- PROD
  • 19. BRIEF BENCH NEED IDEATE FUTURE DESIGN CNCPT PROTO team-B’s EXPERI PROTO EXPERI PROTO 9 month passage through the thinking and doing space FUNKYPRODUCTION ENGINEERING SYS FUNCT SYS
  • 20. BRIEF BENCH RESET NEED team-A’s IDEATE FUTURE DESIGN 9 month EXPERI PROTO passage through the thinking and TEST doing space CFP A earned a wow FUNKYPRODUCTION ENGINEERING SYS SEND FUNCT B earned a thank you OUT SYS PRE- PROD <<)
  • 21. >?@ABC290+-/"5A1D)01+1!16%&#)*%#E%#&%#"$79# (*9%69#)*1)1"+)
  • 22. &/9,"/&0"!-")1!16%&#%##98"79#)1"+6 Munich Stanford Team Team
  • 23. &/9,"/+%D1!5!%6$%4/%#1)1"$*%#&)1"+6 Munich Stanford Team Team Teaching Team Teaching Team
  • 24. &/9,"/4092166%9#"/!16%&#)1"+$9"$*16Project Coach Project Coach Munich Stanford Team Team Teaching Team Teaching Team
  • 25. %#)10#"79#"/$-/)-01$9"$*16Project Coach Project Coach Munich StanfordCulture Coach Team Team Culture Coach Teaching Team Teaching Team
  • 26. 01"/ $90490")1409F1$)6Project Coach Project Coach Munich Stanford Team Team Class CoachClass Coach Corporate Partner Teaching Team Teaching Team
  • 27. Some of Our !Neighbors!
  • 28. GHI@AB56)"#290!4"0)#106*%46JBAB5JBAA GJBI)9)"/@AB5&/9,"/)1"+6#1)(90E(%!1 IJB!7)RL)UV6+1) @$1,#".FG+6/&0&)C<)#,)HE) IJB!7)QRG)@$#20*#68) @$1,#".FI1"&/)C:)#,)WE) @$1,#".FGIJ)C<)#,)KE) LMNA+?&2#FA-&2*)C<E) @$1,#".F@$>S166+)C:)#,)TE)@$1,#".)AB)CDE) @$1,#".FP16&)C<)#,)KE) @$1,#".FLMNA+?&2#)C:OKE)
  • 29. John Gedge Michael Amine Sushi Keven Bellakrid Karsch Richly Suzuki Tomoya Yamamoto Amina Alaoui Marcelo Lopez Sarah Philipp Chakib Matthias Fathallah Dobrigkeit Thomas EL Haouzia Vesa U acker Kowark Alexander Lindroos Zeier Véronique Alejandro Ole Hillen Ramirez Rienow Florencia Fernando Julien Denti Gonzalez Mauroy Tuukka Kingelin Roukaya El Houda Olmo Villegas Arturo Christoph Treviño Francisco Thiele Acosta Tobias Rawald Stefan Paul Hampel Mauduit Shogo Suzuki Anthony Falk Khaled Zhu Benke Sellami Susanna Raphael Didier Ollila Mathieu Mikelis Jenn Marwan Chabasse Kenji Khiat Studers Claudio Peterson Nishito Hansberg Ryan Keijiroh Brooks Aurélien Nagano Matt Sibiril Kandler Youssef Joules Shashank Sharma Ahizoune Gould Quin Lai Isaac Panu Castaneda Min Ming Josh Keski-Pukkila Lo Ga ord Jessica Ji Guillaume Svante Thrierr Suominen Rafael Mayani Jack Esa Antti Ng Nummijoki Sonninen Miguel Ángel Katie Aaswath Velázquez Planey Pauliina Raman Sara Travis Tenho Delgado Bow Xiao Tuukka Heikki Andrea Trevor Yukino Säteri Ge Laurila Delgado Clark JodaiMarco Antonio KellyCruz Carolina Johnson Gomez Maria Kulse April Rafat Tiia Alexander Adrit Je Mehdi Suomalainen Manian Lath Mark Juan Cutkosky Harri Ruiz Toivonen Santhi Elayaperumal Abhishek Andrés Hector Henrik Stephany Shiwalkar Tuuli Cuellar Cuellar Amberla Heikki Fernández Julia Utriainen Soininen Andrés Pettersson Hakava Torres Larry Leifer Peter George Tuomas Toye Kardassakis Sahramaa Daniel Lassi Jaramillo Mark Laitinen Schar Manny Alice Hundal Brooks Lauri Tom Repokari Zhuang Alex Granieri Alejandro Lopez Kat Nguyen Shantanu Garg Daniel Andres Mamiko García Mercado Nagao Yair Laura Vikas Timosaari Agrawal Kollmann Ryan Anderson Sakari Haruna Castren Kawashima Dominic Carlos Schlegel Serrano Jaime Mayoral Maria Camacho Deborah Schaub Caroline Petra Tiziana Dohle Monn Mauchle Rico Matthias Manuel Rinderknecht Huebner Schoeni Marc Schlegel Patrick Keil Christian Jaime Haueter Aguilar Stephanie Petersen Tiziana Aiol Andreas Stockburger Amanda Friederike Fabian Bachmann Falk Ho mann Bischof Uebernickel Marco Brunori Philipp 2010 - 2011 Skribanowitz Pascal Dominic Kappeler Widmer Pasqual Christophe Vossberg Vetterli
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  • 53. #9((1"01&1_#&810.01"/
  • 54. &1_#&01"/9#)*1941#09"! from concept to reality
  • 55. K-%!!.#"+%$60158%6%)1! base case OpenRoad re-circulation "+F2&"2-613()[1.F1&"))creates bad-air &/)+6&8&1$+.)[%)$*+) in the cabin (##.F1&");+$)/$"+18)
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  • 57. `9#$/-6%9#a better convertible, problem eliminated
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  • 64. )*149(10929,6108"79# R1(7)I*Z`]D)
  • 65. !16%&#)*%#E%#&0161"0$*%#$9#)1D) CU+&,+"`=WE) Design Activity ProductRequirements Design Team Product Specifications Process Instrumentation Human Variables Product Instrumentation Technical Variables
  • 66. triple-loop-learning in complex teams FORMAL INFORMAL knowledge knowledge Learning Loop 2 facts, syntax Curriculum what? how? faculty Learning Loop 3 concepts, semantics, architecture when? why? Course instructor Team Product Coach learning by learning by Knowledge mediating doing Learning Loop 1 reflective action does it work?[Ozgur Eris, Larry Leifer, Ade Mabogunje, 2003]
  • 67. 1800! $01"781/"#&-"&1+"d106 ) #-F!*"1/+/)&),#"816).#2-8+$/) 1600! !"+.&2$)191"./)&)!++"F"+5&+9+.) .+/&()2#8!+33#/) Best A1[#(-;+7)I*Z`Da) 9#9) Silve Meri Number of Distinct Noun Phrases! 1400! A! #1200! of A! A! A Meri unique noun 1000! A! A! Meriphrases A! 800! Bronz Bronz 600! A minus! B A minus! B! 400! B! 200! 0! December fall! March ! win! June! spr! Report Report Academic Quarter! Report
  • 68. 9-0"d1#79#7+1$9#6)"#) CY1%1`DTE) S115 S2 S3 S4 S5 S610 M)/+2#./) Mode = most frequent deltat = 5.4 seconds ) .+/&()&,#"813#),"1(8+$).-"13#)) 12"#//)/&?)1235&$%)21$+(#"&+/) C<)+12*)b)"+2+!35+7)+?!"+//&5+7)/+1"2*E)50 0 10 20 30 Duration of Information Fragment (deltat seconds)
  • 69. e-1679#6!0%81410290+"#$1 CB"&/`=<E [+g+") LB)) e-1679#6f*9-0) ) 1[/$"12$)O)2#2"+$+)CY"+"+$#`D<E) "+1/#&()O)2#2+&5&()CB"&/h=<E) .+/&()) $+18)) )!+",#"812+)) ) /2#"+) ) 2#8[&+.)"1$+)#,)ZcdeSZd)Cf-+/3#/O*#-"E) )Zcd)b).++!)"+1/#&()f-+/3#) ) )SZd)b)(++"135+).+/&()f-+/3#) )
  • 70. !16%&#)*%#E%#&%6 )*120"$)"/%)10"79#92)*%6,"6%$$.$/1 C1 C2Requirements Divergent C3 Convergent Decisions Thinking Thinking C4 C5 Design Concepts C1, C2, C3, C4, C5…
  • 71. (*")!9(1E#9(",9-))1"+6 @2*1")<=:=)
  • 72. J)1"+692g6)-!1#)61"$*166)#,)$*+)/18+)!"#[6+8)/#65&()!"+,+"+2+) ^P#5+"(+"_) ^Z&5+"(+"_) R+18) R+18) GYZJFN) GYZJFZ) QNJFN) QNJFJ)
  • 73. +"E%#&!16%&#!1$%6%9#6)9&1)*10 %#)*1!16%&#9,6108")90.
  • 74. KINETIC Concept Views Shoe Design! Task! MERRELL Designs
  • 75. Shoe Design! Task!:U%810&106<
  • 76. Shoe Design! Task!:`9#810&106<
  • 77. “Shoe Design”! Task! O-,F1$)c09-4 U%810&106 `9#810&106:U%810&106< =#290+"79# =)1+6U%6$-661!h R"$)6 DO:<)CTHiE) DO:<)CTHiE) i-1679#6 TO:<)CH]iE) <O:<)C:TiE) ;9)"/ AgfJLGgMjI AAfJLGLgjI =#290+"79# =)1+T"7#& R"$)6 K>W<) K><a):`9#810&106< i-1679#6 K>K<) <>Da) U%k101#$1 e>:=) e>K:) ^G#9)&8!#"$1$)91/)$*+)&,#"813#j)) )CH)k)J8!#"$1$7):FM#$)J8!#"$1$E)
  • 78. Q?Z;TSc?QP)@$%6&()B//+2+) Product Selection! Task! N) Y) P) R#"#$#)) R"+[[&)) R&1;&))
  • 79. “Product :U%810&106< Selection”! Task!=)) <=)) 8&-$+/)
  • 80. Product Selection! :`9#810&106< Task!=)) <=)) 8&-$+/)
  • 81. Product Selection! Task! N) Y) P):U%810&106< O-,F1$)c09-4 U%810&106 `9#810&106 =)1+6U%6$-661!h `9++9# aOa)C:==iE) HOa)C]KiE) Z#%e-1 HOa)C]KiE) HOa)C]KiE) ;9)"/ AAfAJGHJjI ABfAJGl@jI U1$%6%9#>"E%#&h:`9#810&106< B61!/+.) Agh^B alHK) T18%1($*+) T")1 I"#2+//) U1$%!1 $*+)T18%1(
  • 82. 2#661[#"13#)"+/+1"2*),-6%#166409$166+9!1/%#&-6%#& )"#&%,/1+1!%" ) Grosskopf, Weske, Edelman, Leifer 2010 Hasso Plattner Institute, Potsdam Stanford University, California)
  • 83. Universitätsklinikum Jenawith scenario consultantDr. Markus Güntert
  • 84. storming the clincial scenario ]T)
  • 85. extending the storm using tangible plastic process blocks ]])
  • 86. a physician joins and the model,grows beyond the space availablepaper representations are added ]D)
  • 87. day 1 – outcomea prototype process modelin paper and block media D=)
  • 88. day 2 – re-bootwith IT modeling toolintroduction D:)
  • 89. !".m@$/%#%$"/409$166+9!1/%#&1D10$%61(0"46-4"*1"!926$*1!-/1(%)*$9#61#6-6$"4)-01!%#=`;)99/ D<)
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  • 107. UNDERSTANDING INNOVATION Plattner · Meinel · Leifer (Eds.) UNDERSTANDING INNOVATIONH. PlattnerC. MeinelL. Leifer (Eds.)Design inking“Everybody loves an innovation, an idea that sells.” But how do we arrive at suchideas that sell? And is it possible to learn how to become an innovator? Over Hasso Plattnerthe years Design inking – a program originally developed in the engineering Christoph Meineldepartment of Stanford University and o ered by the two D-schools at the Hasso Larry LeiferPlattner Institutes in Stanford and in Potsdam – has proved to be really successfulin educating innovators. It blends an end-user focus with multidisciplinarycollaboration and iterative improvement to produce innovative products, systems, 1 Editorsand services. Design inking creates a vibrant interactive environment that pro-motes learning through rapid conceptual prototyping. In 2008, the HPI-Stanford Design ThinkingDesign inking Research Program was initiated, a venture that encourages Design Thinkingmultidisciplinary teams to investigate various phenomena of innovation in itstechnical, business, and human aspects. e researchers are guided by two generalquestions:• What are people really thinking and doing when they are engaged in creative design innovation? How can new frameworks, tools, systems, and methods aug- ment, capture, and reuse successful practices?• What is the impact on technology, business, and human performance when design thinking is practiced? How do the tools, systems, and methods really Understand – Improve – Apply work to get the innovation you want when you want it? How do they fail?In this book, the researchers take a system’s view that begins with a demandfor deep, evidence-based understanding of design thinking phenomena. eycontinue with an exploration of tools which can help improve the adaptiveexpertise needed for design thinking. e nal part of the book concerns designthinking in information technology and its relevance for business processmodeling and agile so ware development, i.e. real world creation and deploymentof products, services, and enterprise systems. ISBN 978-3-642-13756-3 9 783642 137563 123› springer.com