Business Redesign with Decision Management


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Redesign your business for the big-data driven, social and mobile consumer. This presentation uses a case study approach. It introduces a company trying to build capabilities to handle a growing consumer business. The company has challenges in trying to synchronize initiatives across Marketing, Sales, Product Management, Operations, Accounting and Technology. The presentation describes how Decision Management approaches, tools and technology helped the Company develop a common model to sync up the initiatives with Company goals on its way towards implementation.

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Business Redesign with Decision Management

  1. 1. BUSINESS  DESIGN  For  Big-­‐Data  Driven,  Social  &  Mobile  Consumer   A  Decision  Management  Approach   Gagan  Saxena  (@Gagan_S)   October  16,  2012  
  2. 2. Agenda  1.  Business  coping  with  Challenges  of  Big-­‐Data  and  the   Social,  Mobile  Consumer  2.  Not  a  Technology  Issue  3.  Business  Design  –  Structure,  Processes  and  Roles  4.  “Decision  First”  Approach  5.  Three  Steps  to  Success   2  
  3. 3. Business  Squeezed  in  the  Middle  Consumer  Evoluon   Technology  Choices   3  
  4. 4. Big  Data  Challenge  •  Velocity   –  More  rapid  arrival  •  Volume   –  Of  much  more  data  •  Variety   –  In  many  more  formats   –  …  including  unstructured   and  semi-­‐structured   4  
  5. 5. ACE  Enterprises:  The  Story  So  Far….  •  Established  Business  in  Retail  Distribuon  •  Facing  challenges  from  nimbler  Competors  •  Struggling  to  keep  more  demanding  Customers  •  Need  to  do  something.  Quickly.  •  Department  Heads  go  out  to  develop  Responses.   5  
  6. 6. ACE  Enterprises  Responds  to  Challenges  1.  Marke(ng  ramps  up  Social  Media  team  and  ‘buys’  two   new  Markeng  Management  tools  2.  Sales  recommends  a  Loyalty-­‐Based  Discounng  3.  Product  Development  develops  Cross-­‐Sell/  Up-­‐Sell   packages  to  maximize  Margins  4.  Opera(ons  develops  Rules  for  more  efficient  Shipping   and  for  roung  Customer  Care  calls  5.  Accoun(ng  tries  yet  another  Performance  Management   Dashboard  6.  Technology  signs  up  for  more  BI,  BPM,  BRMS  and   Infrastructure  to  go  with  it   6  
  7. 7. ACE  Enterprises  is  Stuck  •  Too  many  Projects  have  been  Started  •  New  ‘ad-­‐hoc’  Roles  &  Procedures  have  been  Created  •  Time  and  Money  is  running  out  •  Daily  ops  are  suffering  since  Projects  have  priority  •  ACE  is  no  bejer  off.  Things  are  worse.   7  
  8. 8. A  Fresh  Look  Redesign    Consumer  Experience   And  Create  a   “SMART”  System.   8  
  9. 9. What  is  a  ‘Smart’  System?   Business  Rules  Management   Analycs   Big  Data   Predicve  Modeling   Complex  Event  Processing   Natural  Language  Processing   Business  Process  Management  How  do  we  bring  these  capabilies  into  the  Organizaon?   9  
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  13. 13. “Informaon  Technology”  coined  in  1958  (US-­‐BEA).   Double  every  18  months  per  Moore’s  Law.   In  2006,  we  moved  into  the  Second  Half  of  the  Chessboard.  “Exponenal  Growth  has  confounded  our  intuion  &  expectaons.”   13  
  14. 14. Soluon?   “The  soluon  is  organizaonal  innovaon:  co-­‐invenng  new  organizaonal  structures,  processes,  and  business  models  that  leverage   ever-­‐advancing  technology  and  human  skills.”   Where’s  the  Manual?   14  
  15. 15. The  Classics  on  Business  Process  Design.  Assume  ‘Classic’  (Legacy)  Technology.   15  
  16. 16. Management  by  Objecves  (1954)     "Objecves  are  needed   in  every  area  where   performance  and  results   directly  and  vitally  affect   the  survival  and   prosperity  of  the   business."   Create  Customers!   16  
  17. 17. ”Linking  Strategy  to  Operaons”   17  
  18. 18. Designing  New  Validated   Business  Models  Learning   18  
  19. 19. New  Approach  to  Business  Process  Design.   Decisions,  First.   19  
  20. 20. Business  is  a  Series  of  Decisions  Strategic  Decisions  •  Few  in  number,  large  impact  •  Should  we  acquire  this  company  or  exit  this  market?  Tac(cal  Decisions  •  Management  and  control,  moderate  impact  •  Should  we  re-­‐organize  this  supply  chain,  change  risk  mgt  approach?  Opera(onal  Decisions  •  Day-­‐to-­‐day  decisions  that  affect  one  transacon  or  customer  •  Best  offer  for  this  customer?  How  risky  is  this  loan?  Is  this  claim  fraudulent?   20  
  21. 21. Change  in  Processing  Paradigm   Interrupted  Processing   A   B   C   Process   Human   Process   Human   Process   Decision   Decision   Straight  Through  Processing  Automated   Decisions   A   C   Manage  Rules  &   B   Handle  Excepons   21  
  22. 22. Business  Rules  ...statements  of  the  acons  you  should  take  when  certain  business  condions  are  true.   22  
  23. 23. Business  Rule  Formats   23  
  24. 24. The  Analycs  Spectrum   Business  Intelligence   Data  Mining   Predicve  Analycs   X  X  XX   X  X     X  X  X  X   X   X   X   X   X   X   X   X   X  X   X   X   X  X  X   X  X  X  X  X   X   X  X   X   X   X  X  X   X   X   X   X  X  X  X  X   X   X   X  X  X   X  X   X   X  X   X  X  X   X  X  X   X   X   X   X   X  How  do  I  use  data  to   Who  are  my  best/ How  are  those  learn  about  my   worst  customers?   customers  likely  to  customers?  What  has   How  do  I  turn  my  data   behave  in  the  future?  been  happening  in  my   into  rules  for  bejer   How  do  they  react  to  business?   decisions?   the  myriad  ways  I  can   “touch”  them?  Knowledge  -­‐  Descrip1on   Ac1on  -­‐  Prescrip1on   24  
  25. 25. Analycs  DRIVE  Acon  Operational Systems THE CRUCIAL LINK For being Agile & Adaptive Decision   Analytic Systems Business  relies  on  Experts  to  manage  this  Link   CANNOT  SCALE!   25  
  26. 26. From  Decisions  to  Data   Data   Analyc   Insight  Decisions   NOT  the  other  way  around!   26  
  27. 27. ACE  Enterprises  are  Ready  for  the  3  Steps!   Discover   Build   Improve   27  
  28. 28. 1.  Discover  Decisions  Hint:  Operaonal  Decisions  are  Everywhere   28  
  29. 29. Idenfy  &  Understand  Decisions  ✓ Name  ✓ Descripon    ✓ A  queson    ✓ A  defined  set  of  allowable   answers    ✓ Key  facts  like  volume,  complexity,   latency   29  
  30. 30. Decompose  Decisions  What  is  required  to  make  Decisions?   q  Guidelines,  Policy  Documents   q  Human  Experse   q  Regulaons   q  Exisng  System  Logic   q  Analyc  insight   q  Data  Describing  the  Case   q  External  Reference  Data   q  Results  of  other  decisions   30  
  31. 31. Analyze  Knowledge  &  Decision  Dependencies   31  
  32. 32. 2.  Build  Decision  Services   Once  Decisions  have  been  defined,     Build  the  Technical  Components  that  encapsulate  Decisions   Straight  Through  Processing  Automated   Decisions   A   C     Manage  Rules  & B   Handle  Excepons   32  
  33. 33. 3.  Improve  Decisions  •  Learning  from  the  Results  of  Decision  Execuon   –  Good  Decisions?   –  Bad  Decisions?  •  Running  Experiments   –  Use  experimental  configuraon  on  small  parts  of  the  business   and  compare  (A/B  Tesng)  •  Advanced  Analycs   –  Find  Pajerns  in  Data   –  Extrapolate  Data   33  
  34. 34. ACE  Enterprises  &  Decision  Management   Strategy   New  Roles  &  Workflows   Aligned  with   Decision  Model   Automated     Decisions   Rules   Experts Opmize   Technology   Rules  Raonalized  Technology  Architecture   Automated     Run  Base  &  Predicve Processes   Analycs   34  
  35. 35. QUESTIONS?   35