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Big Data: Markets' Friend or Foe?

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John P. Girard, Ph.D.'s talk at Sales & Marketing Middle East. Everyone is talking about big data. Lots of people of selling big data. Many leaders are wondering about big data. An honest, sans hype, overview of where we are in the big data space.

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Big Data: Markets' Friend or Foe?

  1. 1. www.johngirard.net john@johngirard.net1 John  P.  Girard,  Ph.D. https://www.youtube.com/watch?v=QL1dQuK5Wsg
  2. 2. www.johngirard.net john@johngirard.net2 Technology,  Leadership,  and  Culture Defending  Knowledge  Management
  3. 3. www.johngirard.net john@johngirard.net3 Big  Data  =  KM  by  another  name? Big  Data  is  Everywhere
  4. 4. www.johngirard.net john@johngirard.net4 Is  Big  Data  New? www.google.com/trends/ Teradata,  1991 (Osco  Drug) www.tinyurl.com/GirardBD Prairie  Business  Magazine,   7(1)  -­‐‑ 2008     Is  data  mining   synonymous  with   Big  Data? No.    Big  Data  is  the  data   set  (or  asset).   Data  mining  is  the   process (or  handler).
  5. 5. www.johngirard.net john@johngirard.net5 The  History  of  Big  Data Information  Overload Information  overload   occurs  when  the  amount  of   input  to  a  system  exceeds   its  processing  capacity. (Speier et  al,  1999) Information  Overload Information  overload  is  that   state  in  which  available,   and  potentially  useful,   information  is  a  hindrance   rather  than  a  help. (Bawden,  2001) Personal  Information  Overload A  perception on  the  part  of  the  individual   (or  observers  of  that  person)  that  the  flow   of  information  associated  with  work  tasks   is  greater  than  can  be  managed   effectively.  (Wilson,  2001) Organizational  Information  Overload A  situation  in  which  the  extent  of   perceived information  overload  is   sufficiently  widespread  within  an   organization  as  to  reduce  the  overall   effectiveness  of  management   operations.(Wilson,  2001) Overload  is  not  new! The  Roman  Philosopher   Seneca   worried  about  information   overload  nearly  2,000  years   before  it  was  cool.  “What  is  the   point  of  having  countless  books   and  libraries  whose  titles  the   owner  could  scarcely  read   through  in  a  whole  lifetime?”  he   wondered. Michael  Grunwald @MikeGrunwald Aug.  28,   2014
  6. 6. www.johngirard.net john@johngirard.net6 The  History  of  Big  Data 2/3  of  managers  complained  of   Information  overload    (KPMG,   2000) 38%  of  the  surveyed  managers   waste  a  substantial  amount  of   time  locating  information   (Wilson,  2001) Managers  “dwell  on  information   that  is  entertaining  but  not   informative,  or  easily  available   but  not  of  high  quality”  (Linden,   2001) 43%  of  the  managers  delayed   decisions  because  of  too  much   information.  (Wilson,  2001) The  total  accumulated  codified  database  of  the  world,  which  includes  all   books  and  all  electronic  files,  doubles  every  seven  years  and  some   predict  this  will  double  twice  a  day  by  2010  (Bontis,  2000). What  we  knew a  decade  ago: KM  1.0  (According  to  John) Knowledge Information Data Data  to   Information Context Categorize Calculate Correct Condense Information   to   Knowledge Compare Consequences Connects Conversation
  7. 7. www.johngirard.net john@johngirard.net7 KM  2.0 Ikujiro  Nonaka Sociali zation Externa lization Interna lization Comb ination TACIT EXPLICIT EXPLICIT TACIT What  do  decision-­‐makers  want? http://www.youtube.com/watch?v=lH39xjXaLW8
  8. 8. www.johngirard.net john@johngirard.net8 Seek  Wisdom Seek  wisdom,   not  knowledge.   Knowledge  is  of  the  past,   wisdom  is  of  the  future. ~  Lumbee Proverb The  Lumbee Tribe  of  North  Carolina  is  a  state  recognized  tribe  of  approximately   55,000  enrolled  members,  most  of  them  living  in  Robeson  and  the  adjacent   counties  in  southeastern  North  Carolina.   The  Cognitive  Hierarchy 10  Years Knowledge Information Data Ackoff’s  Apex Wisdom Understanding Knowledge Seek  Wisdom not  Knowledge  (KM  2.5?)
  9. 9. www.johngirard.net john@johngirard.net9 Big  Data  – Some  Definitions A  term  coined  to  reflect  very   large and  very  complex data   sets.  (Sultanow &  Chircu,   2015) Big  data  is  a  term  for  any   collection  of  large and  complex data  sets  that  it  becomes   difficult  to  process.  (Gordon,   2015) Data  set  that  is  beyond  the   capacity  of  relational  database   applications.  (Joseph,  2015) Term  for  a  collection  of  large and  complex data  sets  that  it   becomes difficult  to  process   with  traditional  tools.  (Klepac &  Berg,  2015) Large Complex Difficult Strategic  Data-­‐based  Wisdom  in  the  Big  Data  Era Complex:  A  Definition Large Complex Difficult “a  group  of  obviously   related  units  of  which  the   degree  and  nature  of  the   relationship  is  imperfectly   known”
  10. 10. www.johngirard.net john@johngirard.net10 Knowledge  Application  =  KM  3.0 Knowledge Information Data Wisdom Understanding Knowledge “With  3,600  stores in  the  United  States  and   roughly  100  million  customers  walking   through  the  doors  each  week,  Wal-­Mart  has   access  to  information  about  a  broad  slice  of   America  .  .  .  The  data  are  gathered  item  by   item  at  the  checkout  aisle,  then  recorded,   mapped  and  updated  by  store,  by  state,  by   region  .  .  .  By  its  own  account  Wal-­Mart  has   460  terabytes  of  data.” 14  November  2004 Hurricane An  Example
  11. 11. www.johngirard.net john@johngirard.net11 An  Example Big  Data What  do  we  know  about  Big  Data?
  12. 12. www.johngirard.net john@johngirard.net12 Big  Data  is  Global  and  Multidisciplinary www.google.com/trends/ Big  Data  is  NOT  just  technology www.google.com/trends/
  13. 13. www.johngirard.net john@johngirard.net13 Focus  on  the  desired  business  end  state  … The right  technology Branson’s  secret  weapon  is  carrying  an  old-­‐fashioned   notebook  with  him  everywhere  he  goes.
  14. 14. www.johngirard.net john@johngirard.net14 Big  Data http://melmeric.files.wordpress.com/2012/03/big-­‐data-­‐and-­‐the-­‐web.pdf Size  (and  growth)  Matters http://www.domo.com/learn/data-­‐never-­‐sleeps-­‐2 2011 2013
  15. 15. www.johngirard.net john@johngirard.net15 www.theguardian.com/technology/2015/mar/18/twitter-­‐puts-­‐trillions-­‐tweets-­‐for-­‐sale-­‐data-­‐miners It  is  NOT  just  about  size http://www.domo.com/ Size  is  not   measured  in   terabytes  but   rather  business   processes
  16. 16. www.johngirard.net john@johngirard.net16 The  Size  of  Big  Data http://www.youtube.com/watch?v=B27SpLOOhWw CEO:  How  much  data  do  we  need? http://www.computerworlduk.com/news/infrastructure/3433595/boeing-­‐‑787s-­‐‑ create-­‐‑half-­‐‑terabyte-­‐‑of-­‐‑data-­‐‑per-­‐‑flight-­‐‑says-­‐‑virgin-­‐‑atlantic/
  17. 17. www.johngirard.net john@johngirard.net17 Decide  later  … The  History  of  Big  Data 2/3  of  managers  complained  of   Information  overload    (KPMG,   2000) 38%  of  the  surveyed  managers   waste  a  substantial  amount  of   time  locating  information   (Wilson,  2001) Managers  “dwell  on  information   that  is  entertaining  but  not   informative,  or  easily  available   but  not  of  high  quality”  (Linden,   2001) 43%  of  the  managers  delayed   decisions  because  of  too  much   information.  (Wilson,  2001) The  total  accumulated  codified  database  of  the  world,  which  includes  all   books  and  all  electronic  files,  doubles  every  seven  years  and  some   predict  this  will  double  twice  a  day  by  2010  (Bontis,  2000). What  we  knew a  decade  ago:
  18. 18. www.johngirard.net john@johngirard.net18 Michael  Jordan  on  the  “Delusions”  of  Big  Data http://spectrum.ieee.org/robotics/artificial-­‐‑intelligence/machinelearnin g-­‐‑maestro-­‐‑michael -­‐‑jordan-­‐‑on-­‐‑the-­‐‑ delusions-­‐‑of-­‐‑big-­‐‑data-­‐‑and-­‐‑other-­‐‑huge-­‐‑engineering-­‐‑efforts When  you  have  large  amounts  of  data,  your   appetite  for  hypotheses  tends  to  get  even   larger.  And  if  it’s  growing  faster  than  the   statistical   strength  of  the  data,  then  many  of   your  inferences  are  likely  to  be  false.  They  are   likely  to  be  white  noise. http://www.tylervigen.com/
  19. 19. www.johngirard.net john@johngirard.net19 http://www.tylervigen.com/ http://www.tylervigen.com/
  20. 20. www.johngirard.net john@johngirard.net20 The  Marketer’s  task  is  to  help  the  CEO/COO  see  …
  21. 21. www.johngirard.net john@johngirard.net21 The  Future  … What  do  you  think?  Is  Big  Data  good  or  evil?
  22. 22. www.johngirard.net john@johngirard.net22 Slides  available  at:  www.johngirard.net/sais-­‐2015/ The  History  of  Big  Data

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