Big Data for Recruiting | SourceIn New York


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From SourceIn New York, Jim Stroud explains why big data is a critical tool for recruiters.

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Big Data for Recruiting | SourceIn New York

  1. 1. @jimstroud #SourceIn
  2. 2. I was for big data before I was against it.
  5. 5. And let them have the right amount of experience and be willing to accept the salary we offer and… <-­‐-­‐-­‐-­‐-­‐-­‐  Post  and  pray  method.*   *This  method  is  gathering  steam  these  days.   Are  you  hearing  me   recrui8ng  gods?  
  6. 6. WHY IS THAT?
  7. 7. Umm… IDK!
  8. 8. Just kidding. ;-)
  9. 9. 2 Reasons why there is a lot more posting and praying these days…
  10. 10. #1 TALENT SHORTAGE #irony
  11. 11. WHY  EMPLOYERS  ARE  HAVING  DIFFICULTY  FILLING  JOBS?   At  a  global  level  hiring  managers  report  that  talent  shortages  are  most  likely  to  reflect  a   lack  of  technical  competencies  or  a  more  general  lack  of  applicants  for  a  par8cular  post,     as  was  the  case  in  2012  
  12. 12. “…the  United  States  ranks  near  the  middle   in  literacy  and  near  the  boGom  in  skills  with   numbers  and  technology.”   Yikes  
  13. 13. "The  Northern  hemisphere  faces  talent  shortages   in   a   wide   range   of   occupa8onal   clusters   largely   because   popula8ons   are   ageing   rapidly   and   educa8onal   standards   are   insufficient.   "The   United   States,   for   example,   will   need   to   add   more  than  25  million  workers  to  its  talent  base   by   2030   to   sustain   economic   growth,   while   Western  Europe  will  need  more  than  45  million.   In   Germany,   according   to   a   recent   assessment,   70%   of   employers   are   hard-­‐pressed   to   find   the   right  people."   The   skills   deficit   is   exacerbated   by   the   fact   that   baby   boomers   will   be   reTring   and   young   people   are   not   pursuing   the   professional   skills   the   world   will   need.   People  skilled  in  professional  posi8ons  such  as  doctors,   scien8sts,   technicians,   health   care   professionals,   IT   professionals,  computer  scien8sts,  global  managers,  and   skilled  trades  such  as  plumbing  will  be  high  in  demand   but  severe  shortages  are  an8cipated.       Yikes!  (Again)  
  14. 14. #2 Retention issues #headache
  15. 15. August  2012  
  16. 16. Are  you   showing  your   people  love?   January    2014  
  17. 17. May  2014  
  18. 18. Are you feeling the pain of this staffing storm? Survey says… Yes.
  19. 19. Job  saTsfacTon  among  recruiters  and  leaders  is  not  especially  high.     Most   respondents,   including   hiring   managers   and   company   execuTves,   believe   jobs   are   at   least  as  hard  to  fill  this  year  as  in  2013,  and,  by  large  percentages,  believe  filling  jobs  will   be  even  harder  next  year.    
  20. 20. So what are companies doing about it?
  21. 21. Umm… IDK!
  22. 22. Just kidding. ;-)
  23. 23. BIG Boo-­‐yah!   This is how the war for talent will be won. DATA BABY!Boo-­‐yah!  
  24. 24. Data is the future. Data is now.  
  25. 25. So, what is big data?
  26. 26. Paul   F.   and   Warren   S.   Miller   Professor   of   Economics;   Professor   of   Finance   and   Sta8s8cs;  and  Co-­‐Director,  Financial  Ins8tu8ons  Center,  University  of  Pennsylvania   “Big   Data   refers   to   the   explosion   in   the   quanTty   (and  someTmes,  quality)  of  available  and  potenTally   relevant   data,   largely   the   result   of   recent   and   unprecedented  advancements  in  data  recording  and   storage  technology.”  –  July,  2000   OFFICIAL DEFINITION
  27. 27. My definition… “Big Data is a whole bunch of information.“
  28. 28. Of   course,   all   the   data   in   the   world   means   nothing   if   you   can’t  make  sense  of  it  all.    
  29. 29. Some companies are masters of big data!
  30. 30. Did  you  know  this?!  (A  clever  use  of  big  data.)   Based   on   big   data,   Target   can   assign   a   “pregnancy   predic8on”  score.  
  31. 31. Early Weather Warnings Understanding traffic patterns with GPS data Predicting 2nd Heart Attacks with EKG data Detecting credit card fraud Decoding human genome
  32. 32. Do  you  see  it  now?    We  are   meant  to  be  together.     Shut  up  and  kiss  me.     Big Data HR
  33. 33. G o o g l e ’ s     W o r k f o r c e   Predic8on   Algorithm   was   ambi8ous  and  controversial.     2009
  34. 34. Now   Google   has   a   “People   AnalyTcs”   department   made   up   of   data   miners,   psychologists  and  MBAs.     -­‐Kathryn  Dekas,  Manager,  People  Analy8cs  Team  at  Google  
  35. 35. PROJECT  OXYGEN   Google   figured   out   the   traits   of   good  and  bad  bosses.  They  used   that   data   to   improve   the   work   performance   of   struggling   managers  by  75%.  
  36. 36. The  People  Analy8cs  team  was  also  helpful  in  dispelling  myths.  Namely,  employees  believed  that   when   you   worked   at   Google’s   headquarters   you   were   promoted   more   quickly   than   those   in   other  Google  offices,  or  the  Googlers  who  worked  on  “shiny  projects”    were  more  likely  to  be   promoted  than  those  who  were  just  regularly  working  on  the  day  to  day  opera8ons.  The  data   showed   that   neither   of   these   hypotheses   was   actually   true,   but   the   analysis   did   reveal   that   geing  feedback  from  senior  peers  was  the  most  important  factor  if  you  wanted  to  be  promoted   within  Google.  
  37. 37. Think is the only one doing this?
  38. 38. Luxoica  Group  used  data  analy8cs  to  disprove  assump8ons  about  the  company's  recrui8ng   strategy.   Data   showed   that   it   took   on   average   96   days   to   fill   a   posi8on   with   an   external   candidate.    The  management  team  believed  that  the  company's  recruiters  acted  too  slow,  but   a  sta8s8cal  analysis  found  that  the  hiring  managers  dragged  their  feet  about  making  decisions   about  who  to  hire.  Aner  making  a  few  tweaks  they  went  from  96  days  to  fill  a  posiTon  to  46   days.    
  39. 39. Capital   One   creates   automated   data   reports   on   employee   aGri8on,   headcount   and   promo8ons.   Its   also   beginning   to   analyze   the   characterisTcs   of   its   most   successful   employees,  like  what  schools  they  went  to  and  what  their  majors  were.    
  40. 40. By   keeping   track   of   the   saTsfacTon   levels   of   delivery   associates,   a   company   called   Sysco   improved   their   retenTon   rate   from   65%   to   85%,   saving   nearly   $50   million   in   hiring   and   training  costs.  Very  impressive.    
  41. 41. BIG DATA IS COOL!
  42. 42. Umm… Wait a sec’… But,  I  kept   reading.  
  43. 43. Tracking  collar  
  44. 44. Cubist  PharmaceuTcals   •  Sensor  data  tracked   movement  and  voice  tones.   •  Merged  sensor  data  with   email  traffic-­‐data  and  weekly   surveys  on  how  produc8ve   employees  felt.       End  result?   •  More  face  to  face  interac8on   equals  higher  produc8vity.   •  Company  revamped  cafeteria   to  improve  group  interac8on.     Produc8vity  improved.  
  45. 45. Just  in  case  you  want  to  check  your  office  chair  when  you  get  back.  This  is  a  mo8on   sensor  designed  by  a  company  called  –  Herman  Miller.  (     Just  FYI…  
  46. 46. BIG DATA IS scary? Maybe  I  should   stop  reading?  
  47. 47. All very interesting, but what has that have to do with HR today?
  48. 48. Two things to worry about when it comes to recruiting and big data! Just  in  case  you  needed   more  to  think  about.  
  49. 49. #1 Unintended Consequences #irony
  50. 50. #2 More Government Regulation
  51. 51. •  Advance  a  consumer  privacy  bill  of  rights  to  provide  be<er  informa=on  and  standards  for   protec=ng  privacy   •  Pass  legisla=on  for  protec=ng  data  from  breaches   •  Prevent  discrimina=on  based  on  automated  profiling  of  race  or  other  sensi=ve  characteris=cs   RecommendaTons  that  caught  my  eye  
  52. 52. So how do I get the benefits of big data while avoiding the negative consequences?
  53. 53. I don’t know.
  54. 54. Nobody knows (for sure) because it’s a new territory.
  55. 55. But I have some suggestions… •  Big data is not good or evil. Its just a tool. Use it. •  Be transparent about the data you are collecting. •  Set clear rules around what it will be used for •  Keep a constant vigil for unintended consequences.
  56. 56. Subscribe  to  stay  current  on  this  stuff!  
  57. 57.   Contact  me:     Jim  Stroud   SR  Director,    RPO  Recrui8ng  Strategies  and  Support   Randstad  Sourceright             Linkedin:    
  58. 58. LINKS   All  the  links  cited  herein  can  be  found  here:   hGp://