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Crowdsourcing - everything you ever wanted to know
 

Crowdsourcing - everything you ever wanted to know

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    Crowdsourcing - everything you ever wanted to know Crowdsourcing - everything you ever wanted to know Presentation Transcript

    • The  crowdsourcing  compendium  
    • Crowdsourcing:  The  act  of  taking  a  job  tradi2onally  performed    by  a  designated  agent  (usually  an  employee)  and  outsourcing  it  to  an  undefined,  generally  large  group  of  people,  in  the  form  of  an  open  call  Jeff  Howe,  Crowdsourcing  
    • The  logic:  Given  the  right  set  of  condi2ons,    the  crowd  has  the  poten2al  to  outperform    any  number  of  employees  
    • More  and  more  companies  are  becoming    aware  of  this  logic,  and  are  aEemp2ng  to    exploit  it  by  tapping  into  the  excess  capacity    and  collec2ve  brainpower  of  the  crowd  –  usually,  for  liEle  or  no  compensa2on  
    • Making  crowdsourcing  possible  •  Emergence  of  open  source  soIware  movement  •  Tools  of  produc2on:  widely  available,  faster,   cheaper,  easier  to  use  •  Rise  of  online  communi2es  •  Renaissance  of  amateurism/DIY  
    • Why  does  the  crowd  do  it?  •  Intrinsic  mo2va2ons   –  A  belief  in  a  project   –  Obliga2on  to  community   –  Enjoyment     –  Fulfillment  (crea2ve  or  other)   –  Altruism   –  Showing  off  (prove  how  smart/crea2ve  you  are)   –  Reputa2on  enhancement   –  OCD  •  Extrinsic  mo2va2ons:     –  Financial  reward   Non-­‐comprehensive  list,  of  course.  Usually  several  mo2va2ons  will  coexist.  
    • 5  types  (some  overlap)  1.  Collec2ve  intelligence  2.  Crowd  crea2on  3.  Crowdtasking  4.  Crowd  filtering  5.  Crowdfunding  Jeff  Howe,  Crowdsourcing  [except  for  #3]  
    • 1.  CollecBve  intelligence  Asking  people  inside  and  outside  the  company    to  help  solve  problems  and  suggest  new  products  
    • No  maDer  who  you  are,    most  of  the  smart  people    work  for  someone  else  Bill  Joy,  Sun  co-­‐founder  
    • 3  types  of  collecBve  intelligence  •  Problem-­‐solving  networks  •  Idea  jams  •  Predic2on  markets  Jeff  Howe,  Crowdsourcing  
    • 3  types  of  collecBve  intelligence  •  Problem-­‐solving  networks  •  Idea  jams  •  Predic2on  markets  
    • In  the  beginning…    
    • The  longitude  prize  
    • John  Harrison  Picture  source  needed  
    • Eric  von  Hippel:  DemocraBzing  InnovaBon  Users  leading  companies  to  the  cubng-­‐edge  •  Scien2fic  instruments  •  Computer  chips  •  Sports:  windsurfing,  snowboarding,  mountain  biking  •  Many  other  areas  
    • The  collaboraBon  imperaBve  •  The  current  R&D  model  is  “broken”   –  In  some  cases,  R&D  expenses  rising  faster  than  sales     –  e.g.,  10-­‐15  years  and  $Bns  to  develop  a  new  drug  •  With  the  escala2on  in  R&D  costs,  collabora2on     is  becoming  an  aErac2ve  economic  solu2on  •  Businesses,  research  ins2tu2ons,  government  labs,   universi2es  are  moving  towards  collabora2on
    • If  I  can  tap  into  a  million  minds  simultaneously,    I  may  run  into  one  that’s  uniquely  prepared.  Alpheus  Bingham,  Eli  Lilly  [at  the  2me]  
    • Used  by  more  than  150  corpora2ons:  Eli  Lilly,  Boeing,  DuPont,  P&G,  Colgate-­‐Palmolive…  
    • PolyvaBon:  mulBple  sources  of  innovaBon  
    • InnoCenBve  and  The  value  of  diversity  •  Harvard  research:  166  problems  from  26  different  companies  •  The  odds  of  a  solver’s  success  were  higher  in  fields  in  which   they  had  NO  formal  exper2se   –  The  farther  a  challenge  is  from  the  solver’s  specialty,  the   more  likely  it  is  to  be  solved  •  75%  of  solvers  already  knew  the  solu2on  to  the  problem   –  The  problem  simply  needed  a  diverse  enough     set  of  minds  to  have  a  go  at  it  The  Value  of  Openness  in  Scien2fic  Problem  Solving,  Karim  R.  Lakhani,  Lars  Bo  Jeppesen,  Peter  A.  Lohse    and  Jill  A.  PaneEa,  Technology  and  Opera2ons  Management,  January  2007  
    • innocen2ve.com  
    • Example:  Ed  Melcarek  •  Problem  from  Colgate-­‐Palmolive:     how  to  inject  fluoride  powder  into  a  toothpaste  tube     without  the  powder  dispersing  into  the  surrounding  air  •  Solu2on:  impart  an  electric  charge  to  the  powder     while  grounding  the  tube  •  An  electrical  solu2on  to  a  seemingly  chemical  problem  
    • People  whose  networks  span  structural  holes    have  early  access  to  diverse,  oTen  contradictory,    informaBon  and  interpretaBons  which  gives  them    a  good  compeBBve  advantage    in  delivering  good  ideas...    This...  is  creaBvity  as  an  import-­‐export  business.    An  idea  mundane  in  one  group    can  be  a  valuable  insight  in  another.  Ronald  Burt,  The  Social  Origin  of  Good  Ideas  
    • wired.com  
    • The  trailblazer  
    • In  2000,  we  decided  to  stop  being  Fortress  P&G,    and  move  to  an  open  innovaBon  system  that  could  aDract  innovaBons  of  all  stripes  from  the  outside.    Great  invenBon  is  going  on  anywhere  and  everywhere    in  the  world.  [We  have]  about  8,500  researchers,  and    we  figured  there  are  another  1.5M  similar  researchers  with  perBnent  areas  of  experBse.    Why  not  pick  their  brains?  A.G.  Lafley,  CEO,  P&G  
    • When  I  became  CEO  of  P&G  in  2000,  we  were  introducing  new  brands  and  products  with  a  commercial  success  rate  of  15  to  20  percent…    Today,  our  success  rate  runs  between  50  and  60  percent.  That’s  as  high  as  we  want  [it]  to  be.  If  we  try  to  make  it  any  higher,  we’ll  be  tempted  to  err  on  the  side  of  cauBon.    Over  the  same  period,  we’ve  reduced  R&D  spending  as  a  percentage  of  sales;  it  was  about  4.5%  in  the  late  1990s  and  only  2.8%  in  2007.  [We]  focused  on  creaBng…  open  innovaBon:  taking  advantage  of  the  skills  and  interests  of  people  throughout  the  company  and  looking  for  partnerships  outside  P&G.  In  essence,  we  are  building  a  social  system  with  the  purchasers  (and  potenBal  purchasers)  of  our  products,  enabling  them  to  co-­‐design  and  co-­‐engineer  our  innovaBons  A.G.  Lafley,  P&G’s  Innova2on  culture,  Strategy  &  Business  magazine    
    • This  was  important  to  us  for  several  reasons:    First,  we  needed  to  broaden  our  capabiliBes…    Second,  building  an  open  innovaBon  culture  was  criBcal  for  realizing  the  essenBal  growth  opportunity  presented  by  emerging  markets…    A  third  reason…  had  to  do  with  fostering  teams…    For  all  these  reasons,  we  consciously  set  in  place  a  series  of  measures  for  building  an  open  innovaBon  culture…  A.G.  Lafley,  P&G’s  Innova2on  culture,  Strategy  &  Business  magazine    
    • pg.com  
    • pg.com  
    • brandchannel.com  
    • The  Diversity  Trumps  Ability  Theorem  A  randomly  selected  collec2on  of  problem  solvers    will  outperform  a  collec2on  of  the  best  individual  solvers  
    • Why  is  a  community  a  more  efficient?  •  BeEer  at  iden2fying  talented  people   –  The  community  doesn’t  need  to  find  the  person     most  suited  for  the  task,  because…   –  The  person  with  the  right  combina2on  of  talent,  willingness     and  spare  2me  will  self-­‐iden2fy  for  the  task  –  and  undertake  it     without  permission,  contract  or  instruc2on   –  Transac2on  costs  =  zero  •  BeEer  at  evalua2ng  output   –  If  the  contributor  has  overes2mated  his  or  her  own  abili2es  –     the  community  will  iden2fy  that,  too  Clay  Shirky,  Here  comes  everybody  
    • CondiBons  for  diversity  to  trump  ability  •  Scale  of  diversity  =  a  large  enough  pool     to  guarantee  a  diverse  array  of  approaches  •  Qualified  members  (“not  just  subway  passengers”)  •  Method  of  aggrega2ng  and  processing     individual  contribu2ons  •  A  real  problem  (=challenging)  Clay  Shirky,  Here  comes  everybody  
    • More  network  examples  (Some  overlap  with  idea  jams)  
    • Challenges  and  prizes  (A  few  examples)  
    • wired.com  
    • readwriteweb.com  
    • techcrunch.com  
    • techcrunch.com  
    • •  44k  entries  •  5k  teams  •  186  countries  
    • •  The  mining  firm  made  its  proprietary  data  about  a  mining  site  in  Ontario  public,   then  challenged  outsiders  to  advise  where  to  dig  next  •  The  par2cipants  suggested  more  than  a  hundred  possible  sites  to  explore,  many  of   which  had  not  been  mined  by  Goldcorp  –  and  that  yielded  new  gold  
    • 3  types  of  collecBve  intelligence  •  Problem-­‐solving  networks  •  Idea  jams  •  Predic2on  markets  
    • •  Idea  genera2on  by  employees  •  Set  up  in  1996  •  Annual  seed  funding  budget:  $40M  •  Employees  receive  $300k-­‐$500k     for  proposals  that  turn  into  business  plans  
    • ibm.com  
    • •  2006:  The  biggest  ever  jam  •  150k  minds  in  104  countries  •  Clients,  consultants,  employees,  families  •  4  subject  areas:  transporta2on,  health,  environment,  finance  &  commerce  •  46k  ideas;  $100M  invested  in  10  of  them  
    • The  world  is  my  lab  now.  John  Kelly,  Director  of  IBM  Research,    discussing  IBM’s  collaboratories  (=open  innova2on  laboratories)    
    • •  The  Linux  pre-­‐installment  idea  was  brought  up     on  the  day  of  the  launch  (February  16  2007)  •  30k  users  quickly  gave  it  a  thumbs  up  •  In  May,  Dell  launched  3  such  models  
    • By  July  2009:  ~12k  ideas,  ~85k  comments,  ~675k  vo2ngs,  354  implementa2ons  
    • •     
    • Idea  jam  plajorms  
    • Google  
    • •  Powered  by  Google  Moderator  •  More  than  125,000  users  submiEed  over  44,000  ideas  and  cast  1.4M  votes
    • Powered  by  Google  Moderator  
    • Other  examples  (Not  all  of  them  100%  crowdsourcing)  
    • L  Genius
    • guardian.co.uk  
    • mashable.com  
    • 3  types  of  collecBve  intelligence  •  Problem-­‐solving  networks  •  Idea  jams  •  PredicBon  markets  
    • [Nearly  every  individual]  has  some  advantage  over  all  others  because    he  possesses  unique  informaBon  of  which  beneficial  use  might  be  made.  Each  member  of  society  can  have  a  small  fracBon  of  the  knowledge  possessed  by  all,  and  each  is  therefore  ignorant  of  most  of  the  facts    on  which  the  working  of  society  rests…    One  of  the  ways  in  which  civilizaBon  helps  us  overcome  that  limitaBon…  is  by  conquering  ignorance,  not  by  the  acquisiBon  of  more  knowledge,  but  by  the  uBlizaBon  of  knowledge  which  is  and  which  remains    widely  dispersed  among  individuals…  CivilizaBon  rests  on  the  fact    that  we  all  benefit  from  knowledge  that  we  do  NOT  possess.  FA  Hayek,  1974  Nobel  Prize  in  Economics.  From  The  use  of  knowledge  in  society,  1945  
    • Nobody  knows  everything.  But  everybody  may  know  something.  James  Surowiecki,  The  Wisdom  of  Crowds  
    • •  Correct  on  80%  of  Oscar  nomina2ons  •  Never  missed  more  than  one  top  award     since  1996  launch  
    • Drawbacks  of  internal  predicBon  markets  •  Not  using  real  money   –  Lower  credibility   –  Skewed  incen2ves  •  Thin  markets   –  Not  enough  trades/traders   –  Not  enough  diversity  
    • No  longer  with  us  (Some  of  them  predicted  it)  
    • Marketocracy  [ini2al  incarna2on]  The  Masters  100  mutual  fund  was  comprised  of  the  leading  100  porzolios  out  of  100,000  virtual  porzolios  managed  on  the  Marketocracy  website.  Masters  100’s  performance  consistently  “beat”  the  S&P500  .
    • 2.  Crowd  creaBon  
    • The  1%  rule   Geek     0.01%   gods   Content  creators   1%   Content  contributors   10%   Content  downloaders   70%   Casual  surfers   100%  Source  needed  
    • How  it  all  began  
    • The  free  soTware  movement  •  Free  as  in  free  speech,  not  free  beer  (liberty,  not  price)  •  Started  well  before  Linux  was  created,     but  it’s  probably  the  most  widely-­‐known  example  
    • Some  lessons  •  Given  a  large  enough  beta-­‐tester/co-­‐developer  base,   almost  every  problem  will  be  fixed  quickly   –  “Given  enough  eyeballs,  all  bugs  are  shallow”  (Linuss  Law)  •  More  users  find  more  bugs  –  because  adding  more  users   adds  more  different  ways  of  stressing  the  program    •  The  next  best  thing  to  having  good  ideas  is  recognizing   good  ideas  from  your  users.  Some2mes  the  laEer  is  beEer.    Eric  Steven  Raymond,  The  Cathedral  and  the  Bazaar  
    • Crowd-­‐created  soTware  Apps,  app  stores  and  app  challenges.  Here’s  a  (really)  par2al  sample.  
    • In  the  beginning…   marke2ngvox.com  
    • Now  at  more  than  18Bn  
    • Not  just  mobile,  of  course…  (Many  in  the  form  of  app  challenges)    
    • mashable.com  
    • marke2ng-­‐interac2ve.com  
    • Crowd-­‐created  journalism  
    • We  think  of  our  members  as  an  army    of  eyes  and  ears.  But  we’re  not  asking  them    to  be  journalists.  The  phrase  ‘ciBzen  journalism’    makes  about  as  much  sense  as  ‘ciBzen  denBst.  Leonard  Brody,  CEO,  NowPublic.com  
    • InvesBgaBve  reporBng  milestones  •  Ft  Myers  News-­‐Press:  contribu2ng  to  serious  journalis2c   inves2ga2ons   –  2006  housing  development,  bid-­‐rigging •  Talking  Points  Memo  and  the  firing  of  state  aEorneys,  March   2007   –  Awarded  the  George  Polk  Award  for  Legal  Repor2ng  for  “tenacious   inves2ga2ve  repor2ng”   –  When  Dept.  of  Jus2ce  dumped  3,000  pages  of  documents  on  the   press,  site  members  divided  the  pile  into  50-­‐page  slices  and  made   stunningly  quick  work  of  the  subject
    • guardian.co.uk  
    • Crowd-­‐created  maps  
    • readwriteweb.com  
    • Picture  source  needed  
    • techcrunch.com  
    • techcrunch.com  
    • mashable.com  
    • techcrunch.com  
    • Crowd-­‐created  markeBng  Flavors,  ads,  plazorms  
    • Crowd-­‐created  flavors  
    • Walker’s  Do  Us  a  Flavor:  1.2M  ideas  [no,  that’s  not  a  typo]  –     profit  sharing  is  a  great  incen2ve…  
    • Crowd-­‐created  ads  A  few  of  the  pioneers  
    • The  chain  thing   caught  on  J  
    • mashable.com  
    • In  a  class  by  itself  
    • •  The  compe22on   generated  1Bn   impressions  (=  media   investment  of  $36M)  •  During  and  aIer  the   compe22on,  the  ad   garnered  600M  views •  Cost  of  the  winning  ad:   $12.80  
    • Success  led  to  implementa2on  in   more  countries  
    • 2nd  year  was  a  flop  
    • Back  to  basics  in  3rd  year  +  more  money  
    • news.bostonherald.com  
    • If  it  ain’t  broke,     don’t  fix  it  
    • mashable.com  
    • MarkeBng  crowdsourcing  plajorms    
    • Where  art  thou?  
    • Formerly  XLNT  Ads  
    • Crowd-­‐created  content  (Just  a  few  examples)  
    • Those  were  the  days   marke2ngvox.com  
    • Crowd-­‐created  (physical)  products  Lego,  crowdsourced  hardware,  Threadless  &  Etsy  
    • Lego  
    • The  company  wrote  a  “right  to  hack”  into  the  mindstorms  soIware  license  
    • Source:  LEGO  
    • Source:  LEGO  
    • Source:  LEGO  
    • Source:  LEGO  
    • With  Lego  Factory  we  can  expand    beyond  our  100  in-­‐house  designers    to  marvel  at  the  creaBvity  of  more  than  300,000  designers  worldwide.  Mark  Hansen,  Director,  Lego  Interac2ve  Experiences  
    • •  Lego  provides  a  community-­‐like   environment  where  users  can   share  their  Lego  experience  and   the  company  can  get  feedback   as  well  as  new  ideas  •  In  Lego  Creator,  users  upload   their  own  crea2ons;  other  users   vote,  and  Lego  turns  the  most   popular  ones  into  real  products.  •  The  company  brings   ‘high-­‐spenders’  to  the  more   advanced  Brickmaster  program  
    • Crowdsourced  hardware  Open  source  +  P2P  (and  not  really  new…)  
    • Dozens  of  hardware  inventors  around  the  world    have  begun  to  freely  publish  their  specs.    There  are  open  source  MP3  players,    VOIP  phone  routers,  mobile  phone,  laptop…  Clive  Thompson,  Wired  
    • wikipedia.org  
    • Threadless  &  Etsy  P2P,  really  (especially  Etsy)    –  but  I  couldn’t  resist  
    • Customers  as  R&D,  designers,  sales  force,  employees  
    • 3.  Crowdtasking  
    • Crowdsourced  science  
    • •  Iden2fying  and  measuring  landforms  (craters,  ridges,  valleys)  –     in  order  to  find  evidence  of  water  •  As  a  pilot,  an  already-­‐categorized  dataset  was  put  online  –  88k  images   –  Within  a  month  all  were  categorized  accurately  by  the  community   –  Took  a  professional  geo-­‐scien2st  two  years  
    • •  Observa2ons  grown  10-­‐fold  in  a  period  of  5  years  •  “You  don’t  need  a  PhD  to  count  the  birds  in  your  backyard”  •  Ornithology,  like  astronomy,  is  by  now  highly  dependent  on  amateurs   for  gathering  and  siIing  through  raw  data  
    • Crowdsourced  weather  
    • readwriteweb.com  
    • Crowdsourced  patent  review  
    • Outsourcing  patent  review  •  The  system  is  broken   –  On  average,  2.5  years  between  filing  and  decision   –  Backlog  of  1M  patent  applica2ons,  ~470k  in  2007  alone   –  5,500  examiners  –  only  20  hours/applica2on   –  Patent  parking –  Overlapping,  dubious  patents     (e.g.,  system  for  crea2ng  a  note  related  to  a  phone  call  –  MicrosoI)  •  Solu2on:  open  the  review  process  to  public  comment  
    • IBM,  MS,  GE,  US  Patent  &  Trademark  Office  
    • Crowdsourced  law  
    • Crowdsourced  surveillance  
    • Crowdsourced  translaBons  
    • mashable.com  
    • readwriteweb.com  
    • techcrunch.com  
    • Crowdsourced  transcipBon  
    • springwise.com  
    • Crowdsourced  fact-­‐checking  
    • ps•.com  
    • Crowdsourcing  along  the  value  chain  
    • springwise.com  
    • ps•.com  
    • Crowdsourced  microtasks  
    • Crowdsourced  crisis  informaBon  
    • 4.  Crowd  filtering  Passively  and  ac2vely  filtering    the  exponen2ally-­‐increasing  catalogue  of  the  Web  
    • Mass  amateurizaBon  has  created  a  filtering  problem    vastly  larger  than  we  had  with  tradiBonal  media,    so  much  larger  that  many  of  the  old  soluBons    are  simply  broken.  The  brute  economic  logic  of  allowing  anyone  to  create  anything  and  make  it  available  to  anyone    creates  such a  staggering  volume  of  new  material    that  no  group  of  professionals  will  be  adequate  to  filter  [it].    Mass  amateurizaBon  of  publishing  makes    mass  amateurizaBon  of  filtering  a  forced  move.  Clay  Shirky,  Here  comes  everybody  
    • The  acBvity  of  the  10%  [who  filter]…    is  as  valuable  to  any  online  community  as    the  acBons  of  the  [1%  of]  ‘supercontributors’.    Bradley  Horowitz,  former  VP  of  Advanced  Development  Division,  Yahoo  
    • Filtering  websites  
    • fortune.com,  techcrunch.com  
    • Filtering  news  
    • Those  were  the  days  
    • Those  were  the  days  
    • readwriteweb.com  
    • Filtering  media  content  
    • paidcontent.org  
    • Filtering  soTware  
    • Filtering  people  
    • Filtering  locaBons  
    • Product  reviews  
    • If  an  appliance  manufacturer  finds  a  reviewer    on  buzzilions.com  saying  that  his  oven’s  door    melts  on  the  self-­‐cleaning  cycle,  then    the  manufacturer  has  a  quality  problem,    not  a  review  problem.  Groundswell  
    •  Amazon  has  branded  itself  by  gathering  informa2on  from  consumers  –     and  then  returning  it  to  them  in  the  form  of  services  such  as     product  recommenda2ons,  sales  ranking  and  client  reviews.    
    • Up  to  23  collabora2ve  features     on  any  Amazon  product  page  Picture  source  needed  
    • emarketer.com  
    • emarketer.com  
    • emarketer.com  
    • Web  2.0  companies...  build  systems    that  get  beDer  the  more  people  use  them...    The  architecture…  is  such  that  users  pursuing    their  own  “selfish”  interests  build    collecBve  value  as  an  automaBc  byproduct.    An  architecture  of  parBcipaBon.  Tim  O’Reilly  
    • The  crowd  produces  mostly  crap.  The  crowd  finds  the  best  stuff.  The  rise  of  Crowdsourcing,  Wired  Magazine  
    • The  filtering  sequence  has  been  reversed    From    Filter-­‐then-­‐Publish  To  Publish-­‐then-­‐Filter      Clay  Shirky,  Here  Comes  Everybody  
    • 5.  Crowdfunding  
    • huffingtonpost.com  
    • cnet.com  
    • guardian.co.uk  
    • alleyinsider.com  
    • readwriteweb.com  
    • techcrunch.com  
    • businessinsider.com  
    • techcrunch.com  
    • thenextweb.com  
    • Summary  
    • 5  types  (some  overlap)  1.  Collec2ve  intelligence:  what  the  crowd  knows   –  Solu2on  networks,  idea  jams,  predic2on  markets  2.  Crowd  crea2on:  what  the  crowd  creates   –  The  1%  rule  3.  Crowdtasking:  what  the  crowd  does  4.  Crowd  filtering:  what  the  crowd  thinks   –  The  10%  rule  5.  Crowdfunding:  what  the  crowd  finances  Jeff  Howe,  Crowdsourcing  [except  for  #3]  
    • Crowdsourcing  rules  1.  Pick  the  right  model  out  of  the  5  (or  a  combina2on)  2.  Pick  the  right  crowd  (=target  audience)  3.  Offer  the  right  incen2ves   –  Personal  glory,  sense  of  community  –  or  even  cash  4.  Ask  not  what  the  crowd  can  do  for  you,     but  what  you  can  do  for  the  crowd   –  Crowdsourcing  works  best  when  the  individual/company     give  the  crowd  something  it  wants   –  Create  a  horizontal  rela2onship  within  the  community.  It  could  be   more  important  than  a  ver2cal  rela2onship  between  the  company     and  the  individual  contributors.  They  want  to  talk  to  each  other  5.  Keep  the  pink  slips  in  the  drawer  Jeff  Howe,  Crowdsourcing  
    • Crowdsourcing  rules  [cont.]  6.  Keep  it  simple  and  break  it  down   –  Be  clear  on  what  you  want  your  contributors  to  do   –  Get  the  division  of  labor  right   –  “While  crea2ve  capacity  and  judgment  are  universally  distributed  in  a   popula2on,  available  2me  and  aEen2on  are  not”  (Yochai  Benkler)   –  “Because  everyone  already  knew  what  an  encyclopedia  entry  was”     (Jimmy  Wales,  when  asked  why  Wikipedia  has  done  so  well)  7.  The  dumbness  of  crowds,  or  the  benevolent  dictator  principle   –  Have  someone  there  to  greet  them  when  they  show  up   –  Someone  needs  to  guide,  and  some2mes  decide  8.  Remember  Sturgeon’s  Law  9.  Remember  the  10%  rule,  the  an2dote  to  Sturgeon’s  Law  10.  The  community’s  [almost]  always  right   –  Don’t  try  to  control  the  discussion  –  provide  the  plazorm  for  it  
    • If  you’re  not  conducBng  an  exercise  like  that  in  your  organizaBon,    you  risk  missing  the  boat  on  a  sea  change  that’s  transforming  business.    You  must  overcome  natural  organizaBonal  resistance  to  the  idea    of  relinquishing  significant  control  to  people  outside  the  company.  Even  without  knowing  your  business,  I’d  be  willing  to  bet    that  contribuBon  systems  can  address  one  or  more  of  the  business  challenges  you  face  beDer  than  the  methods  you  currently  use.    Your  company  probably  has  advantages  that  start-­‐ups  can  only  dream  of:  exisBng  customers,  traffic  to  your  website…    Naturally,  adopBng  those  methods  is  easier  when  compeBtors    have  beaten  you  to  the  punch...  But  what  if  you  want  to  lead  your  rivals?  ScoE  Cook,  Intuit  Founder  &  Chairman,    The  contribu2on  revolu2on,  Harvard  Business  Review