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Sustaining Data Governance and Adding Value for the Long Term

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Designed to address more mature programs, this tutorial covers the issues and approaches to sustaining Data Governance and value creation over time, amongst a changing business and personnel environment.

Part of the reason many companies launch a Data Governance program again and again is that over time, it is challenging to maintain the enthusiasm and excitement that accompanies a newly initiated program.

Learn about:
• Typical obstacles to sustainable Data Governance
• Re-energizing your program after a key player (or two) leave and other personnel challenges
• Staying relevant to the company as the business evolves over time
• Understanding the role of metrics and why they are critical
• Leveraging Communication and Stakeholder Management practices to maintain commitment
• Embedding Data Governance into the operations of the company

Published in: Data & Analytics

Sustaining Data Governance and Adding Value for the Long Term

  1. 1. The First Step in Information Management www.firstsanfranciscopartners.com Sustainable  Data  Governance:   Adding  Value  for  the  Long  Term   Kelle  O’Neal   kelle@firstsanfranciscopartners.com   415-­‐425-­‐9661   @1stsanfrancisco  
  2. 2. Why  We’re  Here   pg 2Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential   Purpose:     Understand  criQcal  success  factors  for  sustainability  of  a  Data   Governance  Discipline   Outcome:     §  Understanding  Data  Governance  FoundaQon   §  Understanding  how  to  make  governance  a  core  competency   §  PracQcal  knowledge  that  can  be  immediately  implemented  
  3. 3. Agenda   §  Level  SeTng  -­‐  FSFP’s  perspecQve  on  Data  Governance   §  Obstacles  &  Challenges  to  Sustainability   §  CreaQng  Sustainable  Data  Governance   −  OrganizaQon   −  Alignment   −  Metrics  &  Measurements   −  CommunicaQon   −  Embedding  Governance   §  Ensuring  success   pg 3Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  4. 4. www.firstsanfranciscopartners.com Level  SeTng  
  5. 5. Data  Governance  DefiniQon   §  Data  Governance  is  the  organizing   framework  for  establishing  the   strategy,  objecQves  and  policy  for   effecQvely  managing  corporate  data.     §  It  consists  of  the  processes,  policies,   organizaQon  and  technologies  required   to  manage  and  ensure  the  availability,   usability,  integrity,  consistency,   auditability  and  security  of  your  data.   CommunicaQon   and  Metrics   Data       Strategy   Data  Policies   and  Processes   Data     Standards     and     Modeling   A  Data     Governance     Program  consists  of   the  inter-­‐workings     of  strategy,   standards,  policies   and  communicaQon   pg 5 © 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  6. 6. pg 6 Data  Governance  Framework   © 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential •  Vision & Mission •  Objectives & Goals •  Alignment with Corporate Objectives •  Alignment with Business Strategy •  Guiding Principles •  Statistics and Analysis •  Tracking of progress •  Monitoring of issues •  Continuous Improvement •  Score-carding •  Policies & Rules •  Processes •  Controls •  Data Standards & Definitions •  Metadata, Taxonomy, Cataloging, and Classification •  Operating Model •  Arbiters & Escalation points •  Data Governance Organization Members •  Roles and Responsibilities •  Data Ownership & Accountability •  Collaboration & Information Life Cycle Tools •  Data Mastering & Sharing •  Data Architecture & Security •  Data Quality & Stewardship Workflow •  Metadata Repository •  Communication Plan •  Mass Communication •  Individual Updates •  Mechanisms •  Training Strategy •  Business Impact & Readiness •  IT Operations & Readiness •  Training & Awareness •  Stakeholder Management & Communication •  Defining Ownership & Accountability Change Management
  7. 7.    Develop  and  execute  architectures,  policies  and  procedures  to  manage  the  full  data  lifecycle   Enterprise  Data  Management   Enterprise  Data  Management   Ensure  data  is  available,  accurate,  complete  and  secure   Data  Quality   Management   Data  Architecture   Data   RetenQon/Archiving   Master  Data   Management   Big  Data     Management   Metadata  Management   Reference  Data   Management   Privacy/Security   DATA GOVERNANCE pg 7© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  8. 8. pg 8 The  Big  Picture:  EIM  Framework   © 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Provides  a  holisQc  view  of  data  in  order  to  manage  data  as  a  corporate  asset   Enterprise  InformaQon  Management   InformaQon  Strategy   Architecture  and  Technology  Enablement   Content  Delivery   Business  Intelligence    and   Performance  Management     Data  Management   InformaQon  Asset     Management   GOVERNANCE ORGANIZATIONAL ALIGNMENT Content  Management  
  9. 9. www.firstsanfranciscopartners.com Obstacles  &  Challenges  
  10. 10. The  landscape  is  changing  …   pg 10Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential pg 10Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  11. 11. Obstacles   §  CompeQng  prioriQes  and  lack  of  resources   §  Data  Ownership  and  other  territorial  issues   §  Lack  of  cross-­‐business  unit  coordinaQon   §  Lack  of  data  governance  understanding   §  Resistance  to  change  or  transformaQon   §  Lack  of  execuQve  sponsorship  and  buy-­‐in   §  Resistance  to  accountability   §  Lack  of  business  jusQficaQon   §  Inexperience  with  cross-­‐funcQonal  iniQaQves   §  Change  of  personnel   pg 11Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  12. 12. Obstacles   pg 12Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  13. 13. Why  is  Data  Governance  Important?   Internal  pressures:   §  Desire  to  understand  customer  at  any  Qme   from  any  channel   §  Data  Quality  issues  are  persistent   §  Balance  of  old  mainframe  systems  with  new   technologies   §  Movement  to  the  cloud  and  losing  control  of   data   §  Data  Volumes  are  increasing   §  Mobile  apps  enabling  data  to  be  created  and   accessed  anywhere   §  Project  oriented  approach  to  addressing  issues/ opportuniQes   External  pressures:   §  Greater  amounts  of  new  regulaQons   §  Increasing  Customer  Demands  –  my   informaQon  anywhere  at  any  Qme   §  Technology  and  market  changes   outpacing  ability  to  respond   pg 13Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Ensures  the  right  people  are  involved  in   determining  standards,  usage  and   integra4on  of  data  across  projects,  subject   areas  and  lines  of  business  
  14. 14. www.firstsanfranciscopartners.com Establishing  the  OrganizaQon  
  15. 15. Don’t  base  your  program  on  specific  individuals   pg 15Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  16. 16. Process   •  How  are  decisions   made?   •  Who  makes  them?   •  How  are  Commihee’s   used?   Culture   •  Centralized   •  Decentralized   •  Hybrid   OperaQng   Model   •  Data  Governance   Owner   •  SME’s   •  Leadership   People   pg 16Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  17. 17. OperaQng  Model     §  Outlines  how  Data  Governance  will  operate   §  Forms  basis  for  the  Data  Governance  organizaQonal  structure  –  but  isn’t  an  org  chart   §  Ensures  proper  oversight,  escalaQon  and  decision  making   §  Ensures  the  right  people  are  involved  in  determining  standards,  usage  and  integraQon   of  data  across  projects,  subject  areas  and  lines  of  business   §  Creates  the  infrastructure  for  accountability  and  ownership   pg 17Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Wikipedia:  An  OperaQng  Model  describes  the  necessary  level  of  business  process   integraQon  and  data  standardizaQon  in  the  business  and  among  trading  partners   and  guides  the  underlying  Business  and  Technical  Architecture  to  effecQvely  and   efficiently  realize  its  Business  Model.  The  process  of  OperaQng  Model  design  is  also   part  of  business  strategy.  
  18. 18. Types  of  OperaQng  Models   §  Centralized   −  Similar  to  a  top  down  project  model     §  Decentralized   −  Flat  structure,  more  virtual/grassroots  in  nature   §  Hybrid  /  Federated   pg 18Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  19. 19. Pros:   •  Formal  Data  Governance  execuQve  posiQon   •  Data  Governance  Steering  Commihee  reports   directly  to  execuQve   •  Data  Czar/Lead  –  one  person  at  the  top;   easier  decision  making   •  One  place  to  stop  and  shop   •  Easier  to  manage  by  data  type   Cons:   •  Large  OrganizaQonal  Impact   •  New  roles  will  most  likely  require  Human   Resources  approval   •  Formal  separaQon  of  business  and  technical   architectural  roles   Bus  /  LOBs   pg 19 OperaQng  Model  -­‐  Centralized   Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential DG   Execu4ve     Sponsor   DG     Steering   Commi<ee   Center  of  Excellence  (COE)   Data  Governance   Lead   Technical  Support   Data Architecture Group Technical Data Analysis Group Business  Support   Business   Analysis     Group   Data   Management     Group  
  20. 20. LOB/BU     Data  Governance  Steering  Commi<ee   LOB/BU  Data  Governance  Working  Group   pg 20 OperaQng  Model  -­‐  Decentralized   Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Data Stewards Application Architects Business Analysts Data Analysts Pros:   •  RelaQvely  flat  organizaQon   •   Informal  Data  Governance  bodies   •   RelaQvely  quick  to  establish  and  implement   Cons:   •  Consensus  discussions  tend  to  take  longer   than  centralized  edicts   •   Many  parQcipants  compromise  governance   bodies   •   May  be  difficult  to  sustain  over  Qme   •   Provides  least  value     •   Difficult  coordinaQon   •   Business  as  usual   •   Issues  around  co-­‐owners  of  data  and   accountability  
  21. 21. pg 21 OperaQng  Model  -­‐  Hybrid   Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Pros:   •  Centralized  structure  for  establishing  appropriate  direcQon   and  tone  at  the  top   •  Formal  Data  Governance  Lead  role  serving  as  a  single  point   of  contact  and  accountability   •  Data  Governance  Lead  posiQon  is  a  full  Qme,  dedicated  role   –  DG  gets  the  ahenQon  it  deserves   •  Working  groups  with  broad  membership  for  facilitaQng   collaboraQon  and  consensus  building   •  PotenQally  an  easier  model  to  implement  iniQally  and  sustain   over  Qme   •  Pushes  down  decision  making   •  Ability  to  focus  on  specific  data  enQQes   •  Issues  resoluQon  without  pulling  in  the     whole  team Cons:   •  Data  Governance  Lead  posiQon  is  a  full  Qme,  dedicated  role   •  Working  groups  dynamics  may  require  prioriQzaQon  of   conflicQng  business  requirements   •  Too  many  layers Data  Governance  Steering  Commihee   Data  Governance  Office   Data  Governance  Working  Group   Business  Stakeholders   IT  Enablement   Data Governance Organization
  22. 22. OperaQng  Model  -­‐  Federated   pg 22Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Pros:   •  Centralized  Enterprise  strategy  with  decentralized  execuQon   and  implementaQon   •  Enterprise  Data  Governance  Lead  role  serving  as  a  single   point  of  contact  and  accountability   •  “Federated”  Data  Governance  pracQces  per  Line  of  Business   (LOB)  to  empower  divisions  with  differing  requirements   •  PotenQally  an  easier  model  to  implement  iniQally  and  sustain   over  Qme   •  Pushes  down  decision  making   •  Ability  to  focus  on  specific  data  enQQes,  divisional  challenges   or  regional  prioriQes   •  Issues  resoluQon  without  pulling  in  the     whole  team Cons:   •  Too  many  layers   •  Autonomy  at  the  LOB  level  can  be  challenging  to  coordinate   •  Difficult  to  find  balance  between  LOB  prioriQes  and   Enterprise  prioriQes Enterprise  Data  Governance  Steering   Commihee   Enterprise  Data  Governance  Office   Data  Governance  Groups   Data  Governance  OrganizaQon   Business   Stakeholders   IT  Enablement   Divisional  DG   Office   Business   Stakeholders   IT  Enablement   Divisional  DG   Office   Business   Stakeholders   IT  Enablement   Business   Stakeholders   IT  Enablement   Divisional  DG   Office  
  23. 23. OperaQng  Model  Roles  and  ResponsibiliQes   §  Data  Governance  Steering  Commihee   −  Provides  overall  strategic  vision   −  Approves  funding,  budget  and  resource  allocaQon  for  strategic  data  projects   −  Establishes  annual  discreQonary  spend  allocaQon  for  data  projects   −  Adjudicates  intractable  issues  that  are  escalated   −  Ensures  strategic  alignment  with  corporate  objecQves  and  other  business  unit  iniQaQves   §  Data  Governance  Office   −  Chairs  the  Data  Governance  Steering  Commihee  and  Data  Governance  Working  Group   −  Acts  as  the  glue  between  the  Data  Governance  Steering  Group  and  the  Working  Commihee   −  Defines  the  standards,  metrics  and  processes  for  data  quality  checks,  invesQgaQons,  and  resoluQon     −  Advises  business  and  technical  resources  on  data  standards  and  ensures  technical  designs  adhere  to  data  architectural  best   pracQces  to  ensure  data  quality   −  Adjudicates  where  necessary,  creates  training  plans,  communicaQon  plans  etc   §  Data  Governance  Working  Group   −  Governing  body  comprised  of  data  owners  across  Business  and  IT  funcQons  that  own  data  definiQons  and  provide  guidance  &   enforcement  to  drive  change  in  use  and  maintenance  of  data  by  the  business   −  Validates  data  quality  rules  and  prioriQze  data  quality  issue  resoluQon  across  the  funcQonal  areas   −  Trains,  educates,  and  creates  awareness  for  members  in  their  respecQve  funcQonal  areas   −  Implements  data  business  processes  and  are  accountable  to  decisions  that  are  made   pg 23Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  24. 24. Typical  DG  Office  Deliverables   §  Some  Typical  Deliverables:   §  Documented  DG  Strategy,  Vision,  Mission,  ObjecQves   §  Documented  DG  Guiding  Principles   §  Documented  roles  &  responsibiliQes  of  the  various  members   §  Up  to  date  OperaQng  Model   §  RACI  matrices   §  Templates  for  Policies  and  Processes   §  Templates  for  capturing  metrics  and  measurement  requirements   §  Templates  for  steering  commihee  meeQngs   §  Training  Plans   §  CommunicaQon  Plans   §  Template  for  regular  DG  communicaQon   §  Templates  for  logging  issues  needing  escalaQon  and  eventual  resoluQon   §  Templates  for  new  DG  service  requests   §  Checklists  for  new  projects  to  ensure  adherence  to  DG  standards   pg 24Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  25. 25. Typical  Roles   §  Business  Steward   §  Data  Owner   §  Data  Steward   §  Data  Quality  Analyst   §  Business  Analyst   §  Data  Architect   §  Technical  Leads  (MDM,  Metadata,  Reference  Data,  App)   pg 25Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  26. 26. Sample  Data  Governance  OperaQng  Model   pg 26Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Direc4on   TBD     Execu4ve  Sponsor   Business  and  IT   Business  Steward  Leads     Service   Order  Management   Finance  FP&A   Sales   Market  Strategy   Analy4cs   Data  Governance  Steering    Commi<ee     Finance   (CFO)   InternaQonal     (President)   Global   Services    (COO)   IT   (CIO)   MarkeQng     (CMO)   Data  Governance  Office   Data  Governance  Leads   Business  and  IT   Data  Governance  Coordinator   Management   Provides  budget  and   resource  approvals.     Forum  for  issue     escalaQon   Craps  the  enterprise  data   strategy,  including  polices,   processes  and  standards     to  ensure  that  data  is   managed  as  an  asset   Execu4ve  Level   Management    Level       Stewards  data  within   their    BU  to  ensure  that   the  enterprise  policies   are  applied   Tac4cal    Level   Strategic  Level   Provides  overall  strategic     direcQon,  budget  and   resource  approvals     forum  for  issue    escalaQon   Execu4on   Data  Management  IT  Support  Group   Data  Quality  Lead   Metadata  Lead   Data  Architect     BI  Delivery     Opera4ons  External     Repor4ng   DGWG   Enterprise   Architect   BA   Data  Analyst   IT  Security   Privacy   Legal   Data  Stewards     Risk     Centralized  Data  Steward  Pool   Accoun4ng  
  27. 27. Data  Governance  Leadership  Team   Sample  MulQ-­‐Domain  OperaQng  Model   pg 27Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Program  Oversight  &  DirecQon   ExecuQve  Sponsor   Program  Management   DG  Working  Group   Data  Governance  Program  Management  Team   DG  Program  Manager   DG  Coordinator   Program  ExecuQon   IT  Manager   Data Domain Owners Business  Data  Leads   Data  AcquisiQon   Data  Stewardship   IT  Enablement   Supply  Chain   InternaQonal   Sales   HR   Finance   IT   MarkeQng   Customer   Product   Employee   Vendor  Supplier   DG  Data  Quality  Manager  
  28. 28. Direc4on   TBD     Enterprise  Data  Sub-­‐Commi<ee   Business  Data  Stewards   Data  Governance  Steering  Commi<ee   Business  Unit   Officers   Data  Owners   IT  Partner(s)   Data  Governance  Office  (DGO)   Management   Program  Oversight.  Allocates  budget  &   resource.  Empower  Business  Data   Stewards.  Forum  for  issue  escalaQon.   Craps  the  Enterprise  Data  Strategy,   processes  and  standards  to  ensure  that   data  is  managed  as  an  asset.   Execu4ve  Level   Management    Level       Stewards  data  within  their  BU  to  ensure   that  the  enterprise  policies,  standards  &   processes  are  applied.   Tac4cal    Level   Strategic  Level   Provides  overall  strategic    direcQon,  budget   &  resource  approvals.  Forum  for  issue     escalaQon.  Approval  of  data  domains  under   governance  control.   Execu4on   Technical    Data  Stewards   Local  Data  Governance  Working  Groups   Chair:     Enterprise  Data  Officer   Chair:     Data  Governance  Office  Lead       IT  Partner(s)   Sr.  Execu4ves   Business  Units   Sample  Enterprise  OperaQng  Model   Business  &  Technical  Data  SMEs  
  29. 29. Scalability  at  the  Data  Domain   Security,  Balance,  PosiQon  &  TransacQons   Accountable  ExecuQve   Company/Account   Accountable  ExecuQve   Enterprise  Data     Sub-­‐Commihee  Member   Security,  Balance,  PosiQon  &  TransacQons    Business  Data  Owner   Company   Business     Data  Owner   Security     Business     Data  Steward   Balance,  PosiQon   &  TransacQon   Business     Data  Steward   Company     Business     Data  Steward   Account  Business   Data  Steward   Security  DG   Working  Group   BP&T  DG   Working  Group   Company  DG   Working  Group   Account  DG   Working  Group   Layers  scale:   §  OrganizaQon   §  Maturity   §  Complexity  of  Domain   Leadership  can  be   responsible  for  mulQple   domains   Data  Stewardship  =   focused     Account    Business     Data  Owner   Members  of  DG   Steering  Commi<ee   Members  of   Business  Data   Steward  Prac4ce   Group   Members  of  Enterprise    Data  Sub-­‐Commi<ee   Copyright  (c)  2015  -­‐                            First  San  Francisco  Partners  www.firstsanfranciscopartners.com                      Proprietary  and  ConfidenQal  
  30. 30. pg 30 Use  Case  –  Account  Local  Data  Governance  Alignment   © 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Accountable  ExecuQve   Business  Data  Steward   Local  Data  Governance   Working  Group    Business  Steward  Lead   Account  Domain  Enterprise  Opera4ng  Model  
  31. 31. Keys  to  a  Successful  DG  OrganizaQon   pg 31Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential §  Governance  team  must  contain  members  from  mulQple  lines  of  business   §  Ensures  cross  funcQonal  buy-­‐in  and  ownership   §  Key  lines  of  business  must  be  represented   §  Team  members  must  represent  both  business  and  IT   §  IT  needs  to  be  able  to  implement  per  the  governance  policies  and  the  business  needs  to  be  aware  of  IT   limitaQons…   §  Team  needs  to  meet  on  a  regular  basis   §  Business  is  constantly  changing   §  Discuss  new  and  emerging  programs   §  Current  IT  acQviQes  and  their  effect  on  the  data   §  Review  policies  and  study  measurement  output   §  Agreed  upon  fundamentals  that  serve  as  the  Guiding  Principles     §  If  this  doesn’t  exist,  the  first  mandate  is  to  create  this   §  Standards  are  mechanisms  for  Qe-­‐breaking   §  Clear  lines  of  communicaQon     §  Regular  interacQon  with  execuQve  management   §  Ensure  communicaQon  methods  to  enforce  policies  at  the  steward  and  stakeholder  level   §  Invite  stewards,  project  managers,  stakeholders  etc  to  provide  status  updates  on  criQcal  iniQaQves  that   affect  the  data   §  Ensure  the  Opera4ng  Model  fits  the  culture  of  the  company  
  32. 32. www.firstsanfranciscopartners.com Alignment  
  33. 33. pg 33Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  34. 34. Random  House  DicQonary:  a  state  of  agreement  or  cooperaQon   among  persons,  groups,  naQons,  etc.,  with  a  common  cause  or   viewpoint.     Wikipedia:  Alignment  is  the  adjustment  of  an  object  in  relaQon   with  other  objects,  or  a  staQc  orientaQon  of  some  object  or  set   of  objects  in  relaQon  to  others.     Understanding  a  process  from  the  perspec4ve  of  others   Working  individually  towards  a  common  goal   DefiniQon  of  Alignment   pg 34Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  35. 35. Impact  on  Governance  Programs   Sources  of  mis-­‐alignment   §  Lack  of  understanding   −  Of  how  an  individual’s  role  fits  into   Corporate  ObjecQves     −  Of  other  jobs,  roles,  experiences,   objecQves   §  ConflicQng/  compeQng  objecQves   §  PoliQcs   §  CommunicaQon  styles   §  Personality  conflicts   Importance  of  Alignment   §  Creates  a  conQnual  “buy-­‐in”   process  with  all  Stakeholders   §  Helps  organizaQons  “think  globally   and  act  locally”   §  OpQmizes  resources  to  manage   costs   §  Work  towards  a  common  goal   §  Minimizes  risk   pg 35Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  36. 36. Alignment  Process   •  Why  is  this   important?   •  Why  should  we   care?   Value   •  Who  cares?   •  Why  should   they  care?   Stakeholders   •  How  does  the   value  benefit   the   stakeholders?   Linkage   pg 36Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  37. 37. IdenQfy  and  Align  Values   pg 37Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Value  of  DG  to  Business   Value  of  DG  to  IT  
  38. 38. IdenQfy  Stakeholders   §  Who  are  the  Stakeholders?   §  IT   §  OperaQons   §  Compliance   §  Line  of  Business   §  What  are  their  drivers?   §  What  are  their  key  goals?   §  What  are  their  concerns?   §  What  are  they  trying  to  avoid?   §  What  are  their  prioriQes?   §  Which  goals  are  criQcal?   §  What  happens  if  those  goals  aren’t  achieved?   pg 38Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  39. 39. pg 39Proprietary & Confidential Stakeholder  Map   pg 39Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Value  of  DG  to   Business   Value  of  DG  to   IT  
  40. 40. Linkage  is  the  tacQcal  process  of  mapping  your  delivery  to  the   issues  important  to  the  stakeholder.     •  Per  Stakeholder,  idenQfy  what  is  important  to  them  and  why.     §  What  happens  if  they  don’t  achieve  their  goal?   •  List  elements  of  DG  soluQon   •  Choose  Top  3   •  Choose  up  to  3  elements  of  the  DG  soluQon  and  arQculate  how   those  deliverables  can  help  that  person  achieve  their  goals   §  ConQnually  ask  yourself,  So  What?   Linkage  delivers  Alignment   Create  Linkage   pg 40Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  41. 41. PotenQal  Deliverables   §  Consistency  of  customer/product/employee  data   §  Improve  data  quality   §  Improve  data  consumpQon  and  appropriate  usage   §  Create  and  understand  data  lineage   §  Create  a  data  platorm  to  support  a  single  face  to  the  Customer   §  Facilitate  the  concept  of  “Single  Sourcing”  of  data  to  the  Data  Warehouse   and  Business  ApplicaQons   §  Create  and  implement  common  enterprise  systems/tools  and  processes  for   selected  data   pg 41Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  42. 42. DG  Program   Sales/MarkeQng   Improve  Understanding   of  Customers   Improve  SegmentaQon   Understand  Risk   IT   Improved  ProducQvity   ProacQvely  support   business   Lower  TCO   Improved  Data   Quality   Single  Repository  of   Customer  Data   Create  Data  Lineage   ArQculate  Linkage   pg 42Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential The  Single  Repository  of  Customer  data  will   improve  my  understanding  of  customers  by   providing  me  a  trusted  source  of  Qmely,   accurate  and  perQnent  data  from  which  to   execute  analyQcs,  segmentaQon  and  risk   assessment.   CreaQng  and  understanding  Data  Lineage  will   improve  IT  producQvity  by  reducing  the  Qme   spent  searching  for  data,  ensure  the  appropriate   data  is  used  and  validaQng  the  data.  Data   Lineage  that  is  created  and  understood  by  both   IT  and  business  will  facilitate  a  common   language  and  enable  IT  to  beher  support  the   business  growth  and  expansion.  
  43. 43. Linkage  creates  Alignment   pg 43Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  44. 44. www.firstsanfranciscopartners.com Measurement  &  Metrics  
  45. 45. Why  are  Metrics  Important?   Alignment   Rele-­‐ vance   Value   pg 45Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  46. 46. Aligning  Benefit  to  Value   pg 46Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Benefits  of  Data  Governance   •  Data  lineage  and  auditability   •  Improved  data  transparency  and  quality   •  Repeatable  processes  and  reusable  arQfacts   •  Consistent  definiQons   •  Appropriate  use  of  informaQon   •  CollaboraQon  among  teams,  business  units,  etc..   •  Accountability  for  informaQon  use   •  Quality  of  all  data  types   •  Easier  sharing  of  informaQon   •  Visibility  into  the  enterprise  via  data   •  InformaQon  security   Content  property  of  IMCue  and  FSFP,  Copyright  2013     ReproducQon  prohibited    
  47. 47. Impact  Determines  Success   pg 47Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Issues   • Report  Quality   and  Accuracy   • Low  ProducQvity   • Regulatory   Compliance  /   Audit  Response   Goals   • Improve  data’s   usability   • Improve   efficiency  and   producQvity   • Reduce   compliance  /   audit  cost   Metrics/KPI’s   • Data  Quality   • Data  remediaQon   Qme   • Effort  to  comply   Impact   • Improve  client   relaQonships   • Address  new   markets   • Improve   producQvity   • Improve  analysis   &  decision   making   Content  property  of  IMCue  and  FSFP,  Copyright  2013     ReproducQon  prohibited    
  48. 48. DefiniQon   §  Metric     −  A  metric  is  any  standard  of  measurement   §  Number  of  business  requests  logged   §  Number  of  data  owners  idenQfied   §  Percentage  business  requests  resolved  within  agreed  SLA,  etc.     §  Key  Performance  Indicator  (KPI)   −  A  Key  Performance  Indicator  (KPI)  is  a  quanQfiable  metric  that  the  DG  Program   has  chosen  that  will  give  an  indicaQon  of  DG  program  performance.     −  A  KPI  can  be  used  as  a  driver  for  improvement  and  reflects  the  criQcal  success   factors  for  the  DG  Program   §  A  metric  is  not  necessarily  a  KPI   pg 48Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  49. 49. Metrics/KPIs  examples   pg 49Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential People   §  #  of  DGWG  decisions  backed  up  by  the  steering  commihee   §  #  of  approved  projects  from  the  DGWG   §  #  of  issues  escalated  to  DGP  and  resolved   §  #  of  data  owners  idenQfied   §  #  of  data  managers  idenQfied   §  DG  adop4on  rate  by  company  personnel  (Survey)     Process   §  #  of  data  consolidated  processes   §  #  of  approved  and  implemented  standards,  policies,  and  processes     §  #  of  consistent  data  definiQons     §  Existence  of  and  adherence  to  a  business  request  escalaQon  process  to  manage  disputes  regarding  data   §  Integra4on  into  the  project  lifecycle  process  to  ensure  DG  oversight  of  key  ini4a4ves   Technology   §  #  of  consolidated  data  sources  consolidated   §  #  of  data  targets  using  mastered  data   §  Address  accuracy  for  mailing/shipping   §  Data  integrity  across  systems   §  Records/data  aged  past  target   §  Presence and usage of a unique identifier(s)  
  50. 50. www.firstsanfranciscopartners.com CreaQng  Metrics  
  51. 51. Process  to  Establish  Metrics   pg 51 Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Issues   • What  are  the   issues  in  your   group?   • What  do  you   mean  by  that?   • Why  is  it   important?   • What  are  your   objecQves?   Goals   •  What  is  the  change   you  would  like  to   see?  What  acQon?   •  How  will  that   change  impact   you?   •  What  is  the  impact   if  those  objecQves   aren’t  met?   Metrics/KPI’s   •  What  processes  are   involved  in  that   change?   •  How  is  informaQon   used  in  that   process?   •  What  informaQon  is   used?  What  data?   •  What  data   improvements  are   needed?   Impact   • PosiQve  change   created  by   addressing  issues   • Benefit  of   improving  data  to   impact  objecQve  
  52. 52. GeTng  to  Data  Change  Metrics   Issues/ Objec4ves   Goals   Informa4on   Data   Data  Change   Addi4onal  Ac4on   Report  Quality  and   Accuracy     Improve  Data   Understanding     Accounts   Client  InformaQon     Reduce  duplicaQon   of  client  data   Improve  Data   Transparency   Increase   completeness  of   record       Reduce  Manual   RemediaQon   Track  data  lineage   Ensure   thoroughness  of   data  sources     Products  owned     Increase   Completeness  of   record   Ensure   thoroughness  of   data  sources   Households   RelaQonship   Groups   pg 52 Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  53. 53. Sample  Data  Metrics   Data  Change   Measurement   Target   Frequency   Reduce  DuplicaQon  of   Client  Data   %  DuplicaQon   1%   Daily   Increase  Completeness   of  Client  Record   %  Completeness  of  key  fields   99%   Daily   Track  Data  Lineage   Completeness  of  lineage  in   metadata   99%   Monthly   Ensure  Thoroughness  of   Client  Data  Sources   Review  of  data  acquisiQon  and  ETL   process   Business   consensus   Quarterly   Increase  Completeness   of  Products  Owned     %  Completeness  of  key  fields   99%   Weekly   Ensure  Thoroughness  of   Product  Data  Sources   Review  of  data  acquisiQon  and  ETL   process     Business   consensus   Quarterly   pg 53 Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Data   Understanding   Data   Transparency   Reduce  Manual   RemediaQon  
  54. 54. GeTng  to  Business  Change  /  Impact  Metrics   pg 54 Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Goal   Measurement   Target   Frequency   Improve  Data  Understanding   Completeness  of  Business  Glossary   %  of  Business  Users  Trained   100%   100%   Monthly   Monthly   Improve  Data  Transparency   Completeness  of  Lineage   80%   Monthly   Reduce  Manual  RemediaQon   Time  to  complete  report  process  (baseline  is  6  days)   1  Day   Monthly   Increase  Report  Quality  and   Accuracy   Improved  Business  Stakeholder  SaQsfacQon  Survey     Reduced  Issue  Requests   Business   Approval     10%  drop   Quarterly       Monthly   This  is  your  KPI  
  55. 55. BU  2   SCORECARD   BU  4    SCORECARD   BU  1   SCORECARD   BU  3   SCORECARD   DATA  GOVERNANCE   SCORECARD   (FUTURE  STATE)   STRATEGIC   VIEW   OPERATIONAL   SCORECARDS   CONSOLIDATED  BY    BUSINES  UNIT   SETUP RULES   THRESHOLDS   DATA  QUALITY   DIMENSIONS   FFREQUENCY  WEIGHTING   ALL  SCORECARDS   START  WITH  A   BASELINE   Scorecard  Approach:  Show  some  vision  forward   Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   ATTRIBUTE   SCORECARD   Ahribute  level  Supports   OperaQonal  Use  Case   EnQty  Level  Supports       Company  Data  Governance   (Strategic  Value)  
  56. 56. www.firstsanfranciscopartners.com CommunicaQon  &  Stakeholder  Management  
  57. 57. Why  is  CommunicaQon  Important?   pg 57Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Ø Creates  Awareness   Ø Aligns  expectaQons   Ø Creates  an  opportunity  for   feedback  /  engagement   Ø ProacQvely  addresses  Change   Ø Publishes  Success   Ø Answers  the  quesQons  “Why?”  and  “What’s  in  it  for  me?”   Ø Aligns  acQviQes  
  58. 58. TranslaQng  Data  Value  into  Business  Value   §  CommunicaQon  is  key  to  maintaining  commitment   §  The  right  metrics  help  maintain  alignment   −  Metrics  have  no  value  if  they  aren’t  aligned  to  the  interests  of  a  stakeholder   −  Ensure  there  is  some  way  of  measuring  how  the  improvement  in  data  is  helping   stakeholders  progress  toward  their  goals   −  What  informaQon  do  you  need  to  track  and  measure  to  those  goals?   §  Translate  the  value  statement  into  the  language  of  the  recipient   pg 58Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  59. 59. Purpose:  Increase  Stakeholder  Engagement   pg 59Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Using  this  framework  enables  clear  gaps  in  stakeholder   engagement  to  be  idenQfied  and  subsequent  change   strategies  to  be  put  in  place  to  enable  the  gaps  to  be  closed   T I M EStatus Quo Vision COMMITMENT/ENTHUSIASM High Contact I’ve heard about this program/project Low I know the concepts Awareness I understand how Program/project positively impacts and benefits me and the organization Positive Perception This is how we do business Institutionalization Understanding I understand what this means to me and the organization as a whole Adoption I am willing to work hard to make this a success Internalization I’ve made this my own and will constantly create innovative ways to use it
  60. 60. •  Engagement  Strategy:   •  Focused  effort  must  be  given   to  high  priority  groups   •  Provide  sufficient  level  of   informaQon  to  less  influenQal   groups  to  ensure  buy-­‐in   •  Move  people  and  or  groups   to  the  right  by  trying  to   increase  their  level  of   interest   •  Forms  the  foundaQon  of  your   engagement  /   communicaQon  strategy   Stakeholder  Engagement  Strategy   pg 60Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Meet   Their  Needs   Key   Player   Lower     Priority   Show    Considera4on   Stakeholder   Influence   Stakeholder  Influence   Stakeholder  Interest  
  61. 61. What  is  a  CommunicaQon  Plan?   §  CommunicaQon  Plan  DefiniQon   −  A  wrihen  document  that  helps  an  organizaQon  achieve  its  goals  using  wrihen  and   spoken  words.     −  Describes  the  What,  Why,  When,  Where,  and  How   §  Importance  of  a  CommunicaQon  Plan   −  Gives  the  working  team  a  day-­‐to-­‐day  work  focus   −  Helps  stakeholders  and  the  working  team  set  prioriQes   −  Provides  stakeholders  with  a  sense  of  order  and  controls   −  Provides  a  demonstraQon  of  value  to  the  stakeholders  and  the  business  in  general   −  Helps  stakeholders  to  support  the  DG  Program   −  Protects  the  DG  Program  against  last-­‐minute  demands  from  stakeholders   pg 61Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  62. 62. CommunicaQon  Plan   §  Brings  it  all  together:   −  Who  do  we  need  to  communicate  to?   −  What  informaQon  will  be  important  to  them?   −  Metrics  that  map  to  their  professional  and  personal  goals   −  How  frequently  should  they  be  updated?   −  What  is  the  method  of  communicaQon?   −  Who  should  be  communicaQng  to  them?   pg 62Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  63. 63. Components  of  a  CommunicaQon  Plan   pg 63Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Communica4on  Plan   Stakeholder:    XXX   QualitaQve  InformaQon   Any  general  qualitaQve  informaQon  that  I  would  like  to  receive  related   to  this  deliverable   QuanQtaQve  InformaQon   Of  the  quanQtaQve  metrics  that  have  been  defined,  which  are  the  ones   I  would  like  to  be  informed  about  AND  how  do  I  want  the  metric   communicated  to  me  to  make  the  message  perQnent     Frequency   How  open  do  I  want  to  be  informed  about  progress     Method   What  is  my  preferred  mechanism  of  receiving  the  informaQon  
  64. 64. Item Frequency Description Purpose Audience Documentation From Date Owner Status Meetings First BSL Meeting One-Time Introduction Get explicit buy-in from the participants and resource ask DGWG BSLs PowerPoint Presentation John 8/25/11 John Complete DGWG Core Team Kickoff Meeting One-Time DGO kickoff and vision from IT Sponsor Kickoff DGWG-Core, IT Sponsor PowerPoint presentation John 9/15/11 John Complete DGO Launch Logistics One-Time Communication announcing the DGO Plan on the best way to communicate the DGO launch and PR effort DGO, SVB Corporate Communication Email John TBD John Complete DGO-DGWG-Core Status Meeting Weekly DGWG accomplishments, progress towards goals and issues Status DGWG-Core members SharePoint Agenda & Content John Ongoing Flo In progress Meeting with DGO IT Lead Weekly Planning and strategy Status/Planning DGO Chair, DGO IT Lead and DGC John Ongoing John DGO & MDM alignment meetings Weekly MDM Implementation update Status MDM team, DGO Chair & DGC Agenda Rebecca Ongoing Rebecca Mentoring program (Data Stewardship Program) Weekly Opportunity to learn from Business Steward Leads. Best practices, polices, processes, standards, definitions Enrichment DGWG Data Stewards Data Stewardship Best practices. DGO Polices, processes, standards, definitions TBD TBD TBD Not Started Meeting with Program Sponsors Bi-Weekly? Provide DGWG accomplishments, progress towards goals and issues Status DGO Chair, Biz and IT Sponsor PowerPoint presentation John TBD John Not Started DGO-DGWG Decision (Core & Advisory) Meeting Monthly DGWG voting meeting Vote and approve DGWG materials DGWG members SharePoint Agenda & Content John Ongoing Flo In progress DGO-DGWG - DM IT Support Group Meeting Monthly DGWG DM IT Support Group team monthly update Bring the advisory team up to speed on status before the decision meeting DGWG Advisory members SharePoint Agenda & Content John TBD Flo Not Started EIC Meeting Monthly DGWG accomplishments, progress towards goals, issues, documents for informational purposes only Status, Informational EIC members PowerPoint presentation John Ongoing John In progress Meeting with SAM - Fund Business stakeholders As needed Relationship building/Expectations/Impact DGO resource engagement Business Stakeholders Informal/deck, Email John TBD Flo Not Started Meeting with Purchasing stakeholders As needed Relationship building/Expectations/Impact DGO resource engagement Business Stakeholders Informal/deck, Email John TBD Flo Not Started Meeting with Product Implementation stakeholdersAs needed Relationship building/Expectations/Impact DGO resource engagement Business Stakeholders Informal/deck, Email John TBD Flo Not Started Meeting with Global Product stakeholders As needed Relationship building/Expectations/Impact DGO resource engagement Business Stakeholders Informal/deck, Email John TBD Flo Not Started DGO Town Halls One/Year DGWG accomplishments and progress towards goals Forum for open discussion Team Building All DGWG members PowerPoint presentation John TBD Flo Not Started Sample  CommunicaQon  Plan   pg 64Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential And  these  are  just  the   meeQngs!  Also:   •   Awareness  &  Training   •   CommunicaQon  Vehicles   •   Knowledge  Sharing   • ….  
  65. 65. www.firstsanfranciscopartners.com Embedding  Data  Governance  
  66. 66. Ensuring  DG  is  Sustainable   •  Incorporate  DG  goals  into  other  goals,   objecQves  and  incenQves  Incorporate   •  Align  DG  with  strategic  objecQves,   programs  and  projects  Align   •  Embed  DG  into  standard  project,  change   control,  new  iniQaQve  and  operaQonal   processes   Embed   •  Focus  on  delivering  business  value  Focus     pg 66Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  67. 67. Incorporate  IncenQves   Carrots   SQcks   Oversight   AllocaQon   pg 67Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  68. 68. Align  with  ObjecQves,  Programs  and  Projects   §  Examples:   §  Alignment  with  Stakeholder  goals  (already  discussed)   §  Alignment  with  Corporate  ObjecQves   §  Alignment  with  strategic  Programs/Projects   pg 68Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  69. 69. Example:  Alignment  with  Corporate  ObjecQves   pg 69Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  70. 70. Example:     Tie  Principles  to  Corporate  Strategic  ObjecQves   Corporate   Objec4ve   Principle   Client   Data  is  a  key  asset  to  our  company.  We  will  enhance  and  manage   this  asset  by  emphasizing  clear  strategies,  decisive  acQon,   innovaQon  and  results.   Capabili4es   Business  stakeholders  will  get  informaQon  delivered  at  the  right   Qme,  locaQon  and  amount  as  efficiently  as  possible.   Execu4on   Data  Governance  will  introduce,  support  and  drive   standardizaQon  of  enterprise  data.   Brand   Best  in  class  customer  data  quality  will  significantly  improve  both   the  internal  as  well  as  external  customer  experience.   People   Data  Governance  should  increase  producQvity  through   centralized,  streamlined  processes  and  eliminate  non-­‐value  added   acQviQes.  Maximizing  automaQon  is  a  key  way  to  improve  human   resource  efficiencies  and  is  preferable  over  manual  processes.   Principles  drive  crea.on  and  execu.on  of  policies,  standards,  processes,  etc….   pg 70Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  71. 71. www.firstsanfranciscopartners.com Program  /  Project  Alignment  
  72. 72. Project   IniQaQon   Project   ExecuQon   Change   Control   OperaQonal   pg 72 Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  73. 73. Sample:  Embed  in  Project  IniQaQon  Process   pg 73Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential IdenQfy   informaQon/   infrastructure   needs   Profile  to  Iden4fy   data  issues   Analyze  to   Iden4fy  root   causes/  gaps   Design  solu4ons   to  root  cause   problems  /  gaps   Implement   process  &  Tech   soluQons   Sustain   Proac.vely  iden.fy  problems  and  solve  root  causes  
  74. 74. Sample:   Embed  Data  Governance  Into  Your  Project  Methodology   pg 74Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Engage  DG,  DQ,  DA,   MDM,  Metadata   Leads   Assess  adherence  to   Guiding  Principles   Alignment   Workshop   Assess  adherence  to   Guiding  Principles   Engage  DG,  DQ,  DA,   MDM,  Metadata  Leads   Engage  DG,  DQ,  DA,   MDM,  Metadata  Leads   AddiQonal  DG,  DQ,  DA,  MDM  and  Metadata  related  deliverables  added  to  ‘typical’   list:    Data  Profiling  Reports,  New/modified  Score-­‐cards,  AddiQonal  Metadata,  New/ modified  Processes,  Data  Model  Reviews,  etc   Engage   DG,  DQ,   DA,  MDM,   Metadata   Leads   Engage   DG  Lead  
  75. 75. Sample:     Embed  Data  Governance  with  Change  IniQators/Control   pg 75Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential A  process  flow  will  help  ensure  consistent  change   requests  related  to  data      
  76. 76. Sample:  OperaQonal  Process  (Client  On-­‐Boarding)   New  Client   Request   DocumentaQo n  &  Due   Diligence   Terms   confirmed   Agreement  /   Contract   Created   Create  Client   Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential • ExisQng  or  Previous  Client   (Master  Data  Check)   • Data  Standards  and   ValidaQon   • Data  Quality  Check   • Regulatory  Checks   • RACI  /  Data  Ownership   • Data  Enrichment   • Data  ClassificaQon   • Data  RemediaQon   • Decision  Making  /  EscalaQon   Processes   • Hierarchy  /  RelaQonship   Check   • Client  SegmentaQon   • Contract  Management   • Document   Management   • Update  Master  Data   • Create  Hierarchies   • Data  Standards  and   ValidaQon   • Data  Quality  Check   • Data  Sharing,  Access  &  Use   Policy   • …  
  77. 77. Sample:  OperaQonal  Process  (Unique  Device  IdenQficaQon   Management)   pg 77Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential IdenQfy  Products   for  Submission   IdenQfy  Data   Sources   Profile  Product   Data   IdenQfy  and   Address  DQ   Issues   Aggregate  Data   Cleanse  /  Enrich   Data   Review  /  Approve   Data  for   Submission   Submit  Data  and   resolve  errors   Publish  data  for   internal  /external     consumpQon  
  78. 78. ArQfacts  needed  for  IdenQfying  Product  Data  &  Sources   pg 78Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential IdenQfy  Products   for  Submission   IdenQfy  Data   Sources   Profile  Product   Data   IdenQfy  and   Address  DQ   Issues   Aggregate  Data   Cleanse  /  Enrich   Data   Review  /  Approve   Data  for   Submission   Submit  Data  and   resolve  errors   Publish  data  for   internal  /external     consumpQon   Data  DicQonary  /  Business  Glossary   Data  Inventory   Data  Flow  Diagrams   Product  Data  Hierarchies   Data  Standards   Data  Ownership  and  RACI  matrices  
  79. 79. ArQfacts  needed  for  Profiling  and  Addressing  DQ   pg 79Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential IdenQfy  Products   for  Submission   IdenQfy  Data   Sources   Profile  Product   Data   IdenQfy  and   Address  DQ   Issues   Aggregate  Data   Cleanse  /  Enrich   Data   Review  /  Approve   Data  for   Submission   Submit  Data  and   resolve  errors   Publish  data  for   internal  /external     consumpQon   • Data  Quality  Standards   • Data  Quality  Rules   • Data  Profiling  SoluQons   • Data  RemediaQon  Processes   • Decision  Making  &  EscalaQon   Processes    
  80. 80. ArQfacts  needed  for  AggregaQng,  Cleansing,  Enriching   pg 80Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential IdenQfy  Products   for  Submission   IdenQfy  Data   Sources   Profile  Product   Data   IdenQfy  and   Address  DQ   Issues   Aggregate  Data   Cleanse  /  Enrich   Data   Review  /  Approve   Data  for   Submission   Submit  Data  and   resolve  errors   Publish  data  for   internal  /external     consumpQon   • Product  Hierarchies  and  RelaQonships   • Match  /  Merge  Rules   • Data  ValidaQon  and  Cleansing  Rules   • Data  AcquisiQon  Policies  (Purchasing  and   IntegraQng)   • ExcepQon  and  Error  Handling  Processes  
  81. 81. ArQfacts  needed  for  Review,  Approve,  &  Submit   pg 81Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential IdenQfy  Products   for  Submission   IdenQfy  Data   Sources   Profile  Product   Data   IdenQfy  and   Address  DQ   Issues   Aggregate  Data   Cleanse  /  Enrich   Data   Review  /  Approve   Data  for   Submission   Submit  Data  and   resolve  errors   Publish  data  for   internal  /external     consumpQon   • Data  Profiling   • Data  Management  Workflows   • RACI  Matrices   • Decision  Making  and  EscalaQon  Processes   • Approval  Process   • ExcepQon  and  Error  Handling  Process   • Measurement  and  Monitoring  of  the  process  
  82. 82. ArQfacts  needed  to  Publish  &  Manage   pg 82Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential IdenQfy  Products   for  Submission   IdenQfy  Data   Sources   Profile  Product   Data   IdenQfy  and   Address  DQ   Issues   Aggregate  Data   Cleanse  /  Enrich   Data   Review  /  Approve   Data  for   Submission   Submit  Data  and   resolve  errors   Publish  data  for   internal  /external     consumpQon   • Data  Sharing  Policies  (Usage,  Access  Rights)   • Data  RetenQon   • Training  and  CommunicaQon  
  83. 83. www.firstsanfranciscopartners.com Ensuring  Success  
  84. 84. Principle   Descrip4on   Be  clear  on  purpose   Build  governance  to  guide  and  oversee  the  strategic  and  enterprise  mission   Enterprise  thinking   Provide  consistency  and  coordinaQon  for  cross  funcQonal  iniQaQves.  Maintain  an  enterprise  perspecQve  on   data   Be  flexible   If  you  make    it  too  difficult,  and  people  will  circumvent  it.    Make  it  customizable  (within  guidelines),  and   people  will  get  a  sense  of  ownership   Simplicity  and  usability  are  the  keys  to   acceptance   Adopt  a  simple  governance  model  people  can  use.    A  complicated  and  inefficient  governance  structure  will   result  in  the  business  circumvenQng  the  process   Be  deliberate  on  par4cipa4on  and  process   Select  sponsors  and  parQcipants.  Do  not  apply  governance  bureaucracy  solely  to  build  consensus  or  to   saQsfy  momentary  poliQcal  interest   Enterprise  wide  alignment  and  goal  congruence   Maintain  alignment  with  both  enterprise  and  local  business  needs.  Guide  prioriQzaQon  and  alignment  of   iniQaQves  to  enterprise  goals   Establish  policies  with  proper  mandate  and   ensure  compliance     Clearly  define  and  publicize  policies,  processes  and  standards.  Ensure  compliance  through  tracking  and   audit   Communicate,  Communicate,  Communicate!     Frequent,  directed  communicaQon  will    provide  a  mechanism  for  gauging  when  to    “course  correct”,   manage  stakeholder  and  effecQveness  of    the  program   Governance  Design  Principles   pg 84Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  85. 85. Ensuring  Success   §  The  following  factors  are  usually  evident  in  a  successful  program:   −  First  create  a  strategy  and  then  follow  it  (agreed  on  starQng  point  &  steps   necessary)   −  Ensure  solid  alignment  between  Business  &  IT   −  Clearly  defined  and  measureable  success  criteria   −  Small  iteraQons  vs.  all  or  nothing   −  ExecuQve  sponsorship  is  criQcal   −  IdenQfy  and  assess  the  importance  of  key  people  and  or  groups   −  Really  know  your  data   −  Leverage  prior  experience/work…don’t  re-­‐invent  the  wheel   −  Embed  governance  into  the  operaQons  of  your  company   −  Communicate,  Communicate,  Communicate!   pg 85Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  86. 86. pg 86Copyright (c) 2015 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential Thank  you!     Kelle  O’Neal   kelle@firstsanfranciscopartners.com   415-­‐425-­‐9661   @1stsanfrancisco  
  87. 87. www.firstsanfranciscopartners.com Appendix  1  Roles  &  ResponsibiliQes   pg 87Copyright (c) 2014 - First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  88. 88. Direc4on   TBD     Execu4ve  Sponsor   Business  &  IT   Business  Data  Stewards   Data  Governance  Steering  Commi<ee   Business  Unit   Officers   Data  Owners   IT  Partner(s)   Data  Governance  Office  (DGO)   Management   Program  Oversight.  Allocates  budget  &   resource.  Empower  Business  Data   Stewards.  Forum  for  issue  escalaQon.   Craps  the  Enterprise  Data  Strategy,   processes  and  standards  to  ensure  that   data  is  managed  as  an  asset.   Execu4ve  Level   Management    Level       Stewards  data  within  their  BU  to  ensure   that  the  enterprise  policies,  standards  &   processes  are  applied.   Tac4cal    Level   Strategic  Level   Provides  overall  strategic    direcQon,  budget   &  resource  approvals.  Forum  for  issue     escalaQon.  Approval  of  data  domains  under   governance  control.   Execu4on   Technical    Data  Stewards   Local  Data  Governance  Working  Groups   Reference  OperaQng  Model   Business  &  Technical  Data  SMEs   pg 88© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  89. 89. Core  Data  Governance  Roles   Role   Common  Aliases   Insights   Execu4ve  Sponsor  (Business)   In  an  ideal  state  there  is  execuQve  sponsorship  in  both  Business   &  IT.  If  there  is  a  single  sponsor,  look  to  the  Business.   Data  Owner  (Business)   Business  Data  Owner,  Accountable   ExecuQve,  Business  Steward  Lead   Probabili4es:   -­‐“Owner”  may  not  be  accepted  by  culture   -­‐May  not  be  able  to  idenQfy  “Owners”   Large/Complex  Organiza4ons:  May  need  both  Data  Owner  and   Business  Steward  Lead   Data  Steward  (Business)   Business  Data  Steward,  Data  Custodian,   Chief  Data  Steward   It’s  all  about  the  details.  Never  assume  the  R&R’s  based  on  the   Qtle.     Technical  Data  Steward  (IT)   Technical  Lead,  IT  Support  Partner   Data  Architect  (IT)   Open  part  of  Enterprise  Architecture   Member  of  Architecture  Review  Board  (ARB)   May  not  exist,  however  responsibiliQes  should  be  assigned   Business  Analyst  (Business)   BA’s  with  Data  Governance  experience  are  extremely  valuable   and  provide  criQcal  support  to  the  Data  Stewards.       Data  Governance  Office  Lead   DGO  Lead   pg 89© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  90. 90. SupporQng  Roles   Role   Common  Aliases   Insights   Data  Analyst   Business  Data  Analyst,  Technical  Data   Analyst   Data  Architect   InformaQon  Architect  (IA)   Different  from  an  Enterprise  Architect,  open  part  of  Enterprise   Architecture   Member  of  ARB   If  ARB/EA  funcQons  don’t  exist:  Assign  responsibiliQes.   Data  Quality  Analyst   Librarian   Knowledge  Worker   Common  in  MDM  Programs,  more  so  when  MDM  technology  is  in  place.   Role  is  dedicated  to  Data  Maintenance  acQviQes  associated  with  Data   Governance.   Data  SME   Subject  Maher  Expert,  Knowledge  Worker,   User,  Data  Entry  Clerk   SME’s  can  be  found  in  the  Business  &    IT,  and  at  all  levels  in  an   organizaQon.      In  some  organizaQons  a  “SME”  is  considered  highly   skilled,  respected  role.   pg 90© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  91. 91. www.firstsanfranciscopartners.com Leadership  Roles  &  Decision  Making  Bodies   pg  91  
  92. 92. ExecuQve  Sponsor  (Business  and  IT)   §  Chairs  the  Data  Governance  Steering  Commihee   §  UlQmate  authority  and  responsible  for  overall  program  direcQon   §  Provides  overall  strategic  vision   §  Sets  strategy  and  direcQon  for  Data  Governance  &  Management   §  Works  with  the  Data  Governance  Office  to  formulate  the  data   governance  strategy   §  Sets  direcQon  for  the  Data  Governance  Working  Group  (DGWG)   and  ensures  that  the  implementaQon  is  in-­‐line  with  the  strategy   §  Conveys  the  data  management  and  governance  strategy  to  the   other  Exec  Commihees   §  Clarifies  business  strategies  to  the  DGWG   §  Provides  reinforcement  to  enable  the  success  of  data  governance   through  communicaQon   §  Gathers  funding  and  resource  availability  for  the  governance   program   §  Approves  changes  to  the  data  governance  strategy   Resources:  Virtual   Primary  ResponsibiliQes   Set  Strategy  and  Steer   Skills/CapabiliQes   §  Generally  a  Corporate  ExecuQve/Officer  of  Company   §  Recognized  cross-­‐funcQonal  leadership  and  influencing  skills   §  PoliQcally  astute   pg 92© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential ! Roles  may  be  different  in   large  or  complex   organizaQons  ,  i.e.  the  DGO   Lead  can  run  the  DGSC  
  93. 93. Data  Governance  Steering  Commihee   Resources:  Virtual   Primary  ResponsibiliQes   Membership   §  Chaired  by  the  ExecuQve  Sponsor  (Business)   §  IT  Sponsor   §  Cross  LOB  execuQves   §  Data  Owners   §  Data  Governance  Office  Lead  (usually  non-­‐voQng)   §  IT  Partner     Oversight   pg 93© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential §  Brings  corporate  and  cross  LOB  perspecQve   §  Approves  budget  and  allocates  funding     §  Approves  funding  for  enhancements   §  Appoints  and  approves  data  governance  resources   §  Nominates,  selects  and  empowers  and  mandates  the  DGWG   §  Ensures  strategic  alignment  between  DG  program  and  other   business  unit  iniQaQves   §  Ensures  strategic  alignment  with  corporate  objecQves   §  Adjudicates  intractable  issues  that  are  escalated  by  the  Data   Governance  Working  Group  (DGWG)   §  Approves  funding  for  enhancements   §  Enforces  the  data  governance  polices,  processes  and  standards  for   the  organizaQon   §  Approves  changes  to  the  data  governance  strategy   §  Has  the  final  say  in  all  data  governance  decisions   §  Owns  key  data  assets  across  enterprise   !     May  have  addiQonal   decision  making  bodies  in   large  or  complex   organizaQons    
  94. 94. Data  Governance  Working  Group   Resources:  Virtual   Primary  ResponsibiliQes   §  Data  Governance  Office  Lead   §  Data  Stewards   §  Technical  Data  Stewards   §  Business  &  Technical  Data  SMEs   §  Key  Stakeholders     Management  &  ExecuQon   Membership   pg 94© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential §  Governing  body  across  Business  and  IT  funcQons  that  own  data   definiQons  and  provide  guidance  &  enforcement  to  drive  change   in  use  and  maintenance  of  data   §  Defines  data  polices,  processes  and  standards    (PPS)   §  PrioriQzes  opportuniQes  to  develop  data  polices,  processes  and   standards,  and  iniQates  data  quality  iniQaQves   §  Advises  data  stewards  on  the  development  and  maintenance  of   the  data    PPS   §  Assists  in  the  approval  and  enforcement  of  data  data  PPS   §  Assess  compliance  and    manages  risk   §  Resolves  issues  that  have  been  escalated  to  the  DGWG   §  Approves  data  polices,  processes  and  standards     §  Reviews  and  approves  appeals  and  excepQons;  escalates  rare   excepQons   !     Local  DGWG  for  large  or   complex  organizaQons   Led  by  the  Data  Owner,   Business  Data  Lead  or  Data   Steward  
  95. 95. www.firstsanfranciscopartners.com Data  Governance  Roles  
  96. 96. Data  Owner   §  Member  of  Data  Governance  Steering  Commihee   §  Accountable  for  represenQng  the  Business  Unit  and  corporate   interests  from  an  Enterprise  perspecQve   §  Accountable  for  the  Business  Unit  at  the  Data  Governance  Steering   Commihee   §  IdenQfies  and  prioriQzes  issues  and  suggested  enhancements  from   end  users   §  Helps  to  promote  the  data  governance  program  across  the   Enterprise   §  Serves  as  an  escalaQon  point  for  all  data  governance  issues  for  the   Data  Steward  and  Data  Governance  Working  Group   §  Works  with  other  Data  Owners  to  idenQfy  and  resolve  specific  data   quality  issues   §  Responsible  for  ensuring  compliance  with  data  governance  policies   and  standards  across  the  Enterprise  and  within  the  Business  Unit   §  Seeks  and  manages  funding  for  iniQaQves  to  improve  data  quality   §  Trains,  educates,  and  creates  awareness  for  members  in  their   respecQve  funcQonal  areas   Resources:  Virtual   Primary  ResponsibiliQes   §  Business  RepresentaQve   §  Ability  to  syndicate  and  achieve  organizaQonal  change  in  a   decentralized  environment   §  Demonstrated  program  management  and  enterprise-­‐wide   coordinaQon  experience   §  Expert  communicaQon  skills  (verbal  and  wrihen)  with  the  ability  to   communicate  complex  issues  /  requirements  to  technical  and  non-­‐ technical  audiences  as  well  as  educate  the  business  about  data   management   Manage   CapabiliQes/Skillsets   pg 96© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential !   “Data  Owner”  may  not   be  embraced     Complexity/Scope  may  require   addiQonal  layers/roles  to   execute  at  the  enQty  level  
  97. 97. Business  Steward  Lead   §  Responsible  for  represenQng  the  LOB  and  corporate  interests  from  an   enterprise  perspecQve   §  Represents  the  LOB  at  the  Data  Governance  Working  Group  (DGWG)   §  IdenQfies  and  prioriQzes  issues  and  suggested  enhancements  from  end  users   §  Helps  to  promote  the  data  governance  program  across  the  enterprise   (primarily  within  their  LOB)   §  Defines  polices  and  standards  to  ensure  data  quality  within  the  LOB   §  Sets  goals  on  how  to  manage  business  informaQon  beher   §  Serves  as  an  escalaQon  point  for  all  data  governance  issues  within  the  LOB   §  IdenQfies  and  resolves  LOB-­‐specific  data  quality  issues;  works  with   appropriate   §  Responsibility  for  ensuring  compliance  with  data  governance  policies  and   standards  within  the  LOB   §  Seeks  and  manages  funding  for  iniQaQves  to  improve  data  quality   §  Trains,  educates,  and  creates  awareness  for  members  in  their  respecQve   funcQonal  areas   Resources:  Virtual   Primary  ResponsibiliQes   •  Solid  knowledge  and  understanding  of  the  business,  organizaQon,  and   funcQonal  area   •  Excellent  communicaQon  skills  (wrihen  and  oral)   •  FacilitaQon  and  consensus  building  skills   •  Ability  and  willingness  to  work  as  part  of  a  team   •  Ability  to  funcQon  independently   •  ObjecQvity,  CreaQvity  and  Diplomacy   Execute   CapabiliQes/Skillsets   pg 97© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential !   Business  Steward   lead  takes  the  place   of  the  “Data   Owner”  
  98. 98. Data  Steward  (Business)   §  Develop  policies  and  standards  to  ensure  data  quality;  has  overall   accountability  for  data  quality   §  Ensures  compliance  with  data  governance  policies  and  standards   §  UlQmately  accountable  for  the  execuQon  of    the  data  governance   strategy   §  Ensures  that  all  policies,  standards,  escalaQons,  and  decisions  follow   the  predefined  processes   §  Performs  root  cause  and  impact  analysis   §  Responsible  and  accountable  to  Business  Steward  Lead  for  the  subject   maher  knowledge  within  a  parQcular  LOB   §  Works  on  Data  Governance  Working  Group  (DGWG)  when  assigned  to   specific  requests  and  projects   §  Works  with  the  Business  Steward  leads  to  help  define  metrics  to   measure  and  monitor  data  quality   §  Ensures  consistency  of  data  quality  processes  within  an  LOB   §  Resolves  daily  data  quality  operaQonal  issues  and    performs  root   cause  analysis  to  idenQfy  point  of  failure   §  ParQcipates  in  the  wriQng  of  data  definiQons  and  genealogy     Resources:  Virtual   Primary  ResponsibiliQes   CapabiliQes/Skillsets   §  Experience  developing  standards,  processes  and  policies   §  Exposure  to  mulQple  business  units  in  relevant  industry  in  order  to   understand  linkages  and  dependencies   §  Ability  to  understand  upstream  and  downstream  needs   §  Can  represent  a  broader  view  (beyond  LOB)   §  Knowledge  of  data  /  content  management   §  Experience  with  technical  wriQng   §  Excellent  oral  /  wrihen  communicaQon   Execute   pg 98© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  99. 99. Data  SME  (Business  and  IT)   §  Member  of  Data  Governance  Working  Groups  for  specific  data  domain(s)   §  Recognized  experts  within  the  organizaQon   §  May  not  be  officially  responsible  for  managing  an  Domain  but  may  be   consulted  on  topics  related  to  Domain   §  Considered  a  data  “go-­‐to”  person  within  their  Business  Unit   §  Deep  understanding  of  use  and  impact  of  data  within  and  across  Business   Unit   §  Ability  to  parQcipate  in  development  of  standards,  processes  and  policies   §  Ensures  compliance  with  data  governance  policies  and  standards   §  Ensures  that  all  policies,  standards,  escalaQons,  and  decisions  follow  the   predefined  processes   §  Performs  root  cause  and  impact  analysis   §  Responsible  and  accountable  to  Data  Steward  for  the  subject  maher   knowledge  within  Business  Unit.     §  Resolves  daily  data  quality  operaQonal  issues  and    performs  root  cause   analysis  to  idenQfy  point  of  failure   §  ParQcipates  in  the  wriQng  of  data  definiQons  and  genealogy     §  Works  with  other  SMEs  and  the  data  steward  to  idenQfy  and  address  data   interdependencies  across  businesses  and  funcQons   §  Work  with  other  SMEs  and  the  data  steward  to  resolve  issues   §  Drive  awareness  and  adopQon  of  policies,  standards  and  business  rules   Resources:  Virtual   Primary  ResponsibiliQes   CapabiliQes/Skillsets   §  Business  RepresentaQve   §  Considered  a  data  “go-­‐to”  person  within  their  business  unit   §  Deep  understanding  of  use  and  impact  of  data  within  and  across  business  unit   §  Ability  to  parQcipate  in  development  of  standards,  processes  and  policies   §  Exposure  to  mulQple  business  units  in  relevant  industry  in  order  to  understand   linkages  and  dependencies   §  Knowledge  of  data  /  content  management   §  Excellent  oral  /  wrihen  communicaQon   Execute   pg 99© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  100. 100. Business  Data  Analyst   §  Supports  the  Business  Data  Steward   §  Work  with  Technical  Data  Stewards  and  IT  Data  Governance  resources  to   support  data  modeling,  metadata  and  data  quality  acQviQes.   •  Leverage  well  thought  out  methodology  applying  specific  data  enQty  and   business  process  experQse.   •  Provide  metrics  and  reporQng  support  (both  adhoc  and  repeQQve)  to  data   management  programs  and  Data  Governance   •  Make  recommendaQons  for  correcQng  and  prevenQng  errors  and  defects   that  include  process  changes,  data  cleansing  and  integrity  rule  updates.   •  DocumenQng  the  types  and  structure  of  the  business  data  (conceptual  &   logical  modeling)   •  Analyze  and  mine  business  data  to  idenQfy  paherns  and  correlaQons  among   the  various  data  points   •  Design  and  create  data  reports  and  reporQng  tools  to  help  business   execuQves  in  their  decision  making   Resources:  Dedicatedl   Primary  ResponsibiliQes   CapabiliQes/Skillsets   §  Strong  relaQonship  with  technical  staff   §  Ability  to  map  and  tracing  data  from  system  to  system  in  order  to   solve  a  given  business  or  system  problem   §  Ability  to  perform  staQsQcal  analysis  of  business  data   §  Able  to  translate  business  quesQons  into  data  requirements  to  IT   §  Able  to  analyse  large  sets  of  complex  datasets,  examining  for  both   standard  and  anomalies  of  data   Execute   pg 100© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  101. 101. Support  Roles   Resources:  Dedicated   Execute  -­‐  TacQcal   Role   Primary  ResponsibiliQes   Data  Librarian     §  Uses  well  documented  "playbooks",  execute  manual   data  remediaQon/data  cleansing  acQviQes.     §  Execute  manual  processes  to  close  the  gap  on  key  data   that  cannot  be  fixed  by  automaQon  tools  and   technology.     §  Apply  the  established  data  quality  playbook  of  policies   and  processes  to  the  data  i.e.  IdenQfy  and  remediate   duplicate  records,  improve  completeness  for  criQcal   data  ahributes.     Data  Users   §  Defines  business  requirements   §  Understands  the  data’s  term  of  use   §  Complies  with  data  governance  policies   §  Involved  in  accessing  and  invesQgaQng  integrated   datasets  for  staQsQcal  and  research  purposes   pg 101© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential
  102. 102. www.firstsanfranciscopartners.com The  Data  Governance  Office  
  103. 103. Data  Governance  Office   §  Documented  DG  Strategy,  Vision,  Mission,  ObjecQves   §  Documented  DQ,  MDM/RDM  and  Metadata  Management  Strategies   §  Documented  DG  Guiding  Principles   §  Documented  roles  &  responsibiliQes  of  the  various  members   §  Up  to  date  OperaQng  Model   §  RACI  matrices   §  Templates  for  Policies  and  Processes   §  Templates  for  capturing  metrics  and  measurement  requirements   §  Templates  for  steering  commihee  meeQngs   §  Training  Plans   §  CommunicaQon  Plans   §  Template  for  regular  DG  communicaQon   §  Templates  for  logging  issues  needing  escalaQon  and  eventual  resoluQon   §  Templates  for  new  DG  service  requests   §  Checklists  for  new  projects  to  ensure  adherence  to  DG  standards   Resources:  Dedicated   Primary  ResponsibiliQes   Lead,  Advise  &  Support   Data  Governance  Office   Data  Quality  Management   MDM  Management   Metadata  Management   Coordinator/   Program   Manager   Data   Governance     Lead   pg 103© 2015 First San Francisco Partners www.firstsanfranciscopartners.com Proprietary and Confidential !   Strong  Partnership   between  the  DGO     and  IT  DG   OrganizaQons  

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