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Using Lean Principles to Manage the Data Value Chain

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Creating and managing a data office is not an easy task. The reasons for so many problems in streamlining a data strategy come from lack of data ownership, lack of a data roadmap and the data processes not clearly defined.

Using the Lean Principles that come from the Toyota Production System is one method that has been proved to be quite successful.

This session delivered for the Data Quality Pro Summit explores how it can be done.

Published in: Data & Analytics

Using Lean Principles to Manage the Data Value Chain

  1. 1. Using Lean Principles to Manage the Data Value Chain Mario Faria Twitter: @mariofaria Head and Chief Data Officer CDO, Inc. http://www.cdo-inc.com/ Track: Data Quality, Data Governance Industry:
  2. 2. Mario Faria 2 About Mario Faria •  Mario was one of the first Chief Data Officers in the world •  Acting as a CDO for the last 5 years in North America, South America, Europe and Asia •  Passion : Bring order to the chaos •  Leader of teams working in Analytics, Data Monetization, Data Quality, Data Governance, Operations and Business Architecture •  Motto: “If you do not treat people, technology and data as economic assets, they will become liabilities” Mario Faria Twitter: @mariofaria Head and Chief Data Officer CDO, Inc. http://www.cdo-inc.com/
  3. 3. Managing your most important asset to drive business performance
  4. 4. In  May  1915,  The  Boston  Red  Sox  Babe  Ruth   pitching  debut  and  his  first  home  run,  but  …  
  5. 5. The  Rex  Sox  lost  to  the  NY  Yanks    
  6. 6. Your  data  strategy  is  a  journey  
  7. 7. Mario Faria 9 The 3 Architectures a Company needs to succeed Business Architecture Technology Architecture Data Architecture
  8. 8. Mario Faria 10 Data & Analytics Responsibilities •  Data Strategy •  Data Governance •  Data Quality •  Data Analytics •  Data Insights •  Data Architecture •  Data Acquisitions •  Data Operations •  Data Policies •  Data Security •  Data Protection
  9. 9. A  data  &  analyGcs  team  is   responsible  for  transforming   data  assets  into  compeGGve   insights,  that  will  drive   business  decisions  and  acGons,   using  people,  processes  and   technologies  
  10. 10. Data  teams  build  the   bridge  between  business   and  IT  
  11. 11. Mario Faria 13
  12. 12. Mario Faria 14
  13. 13. Mario Faria 15 A data product allows an objective to be achieved using data & analytics
  14. 14. Mario Faria 16 More and more, leaders are being hired to think strategically about all the steps, from getting raw data and making it useful to the business users
  15. 15. Mario Faria 17 Chief  Data  Officer   (focused  on  data   management)   Chief  Digital  Officer   (focused  on  digital   transforma8on)   Chief  Analy8cs  Officer   (focused  on  decision   management  ini8a8ves)   The  ul8mate  leader  who   creates  and  executes  digital,   data  and  analy8cs  strategies   to  drive  business  value     Copyright:  Mario  Faria  2014   The  Chief  Data  /  AnalyGcs  /  Digital  Officer  roles  
  16. 16. Mario Faria 18 A few lessons I have learned to become a data and analytics expert •  Many problems with streamlining a data strategy •  Major concerns with data management •  How you can overcome the issues •  What I have learned from several data journeys
  17. 17. The Data Life Cycle
  18. 18. Mario Faria 20 The Data Value Chain
  19. 19. Mario Faria 21 A few problems in most organizations •  Data is fragmented and scattered •  Silos of information hanging around •  Like the truth, data has many versions •  The Data Lifecycle is a complex process •  Data projects being managed by IT •  A formal process to data management is a requirement in order to do Analytics
  20. 20. Mario Faria 22 Data is an abstract concept
  21. 21. Using Supply Chain Concepts and Techniques to manage your data assets
  22. 22. Mario Faria 24 Data & Analytics as a Production System
  23. 23. Mario Faria 25 The Deming Model : Production Viewed as a System
  24. 24. Mario Faria 26 What is Data Quality ? •  Quality is a customer perception •  A few dimensions: freshness, coverage, completeness, accuracy •  It is a never ending job
  25. 25. Mario Faria 27 A Few Quality Programs TDQM TIQM
  26. 26. Mario Faria 28 Source: Dan Myers, The Value of Using the Dimensions of Data Quality, Information Management
  27. 27. Implementing Lean Best Practices that came from the Toyota Manufacturing Process
  28. 28. Mario Faria 30 Toyota Production System
  29. 29. Mario Faria 31 Lean Goals •  Improve quality •  Eliminate waste •  Reduce lead time •  Reduce total costs It is about how behaviors, processes and actions can be changed for improving the overall system
  30. 30. Mario Faria 32
  31. 31. Mario Faria 33
  32. 32. Mario Faria 34 The 8-Basics of Kaizen Based Lean Manufacturing, by Bill Gaw http://bbasicsllc.com/
  33. 33. Mario Faria 35 •  Specify the value desired by the customer •  Map the data value stream •  Reengineer your data processes to eliminate waste •  Introduce “pull” •  Strive for continuous improvement Source : Meghann Wooster, Beyond Fire Drills: Applying Lean Principles to Information Governance, http://www.cmswire.com/cms/information-management/beyond-fire-drills-applying- lean-principles-to-information-governance-023705.php Applying Lean Principles to Information Governance
  34. 34. Mario Faria 36 •  Data & Analysis are becoming products •  Quality is key to success •  Data explosion in volume, variety and velocity •  The number and value of external data sets are rising fast •  Focus your team efforts is crucial •  Leverage technology to implement a distributed data value chain initiative Why Building a Distributed Data Value Chain is Critical
  35. 35. Mario Faria 37
  36. 36. Mario Faria 38 The Predictive Analytics Factory Concept
  37. 37. Mario Faria 39 Data Value Chain Monitoring Centers
  38. 38. Right  People   Right  Data   Right  Technology      
  39. 39. Without  proper  Data  Quality   principles,  it  is  impossible  to   achieve  the  goals  of  increasing   revenue,  reducing  costs  or  gaining   operaGonal  efficiency  in  the   business  areas  
  40. 40. Mario Faria 42 Problems with Data Quality •  Business people don’t understand it and don’t have time or patience •  IT people still have a technology mindset •  Data & Analytics people make it more complex than it is
  41. 41. Mario Faria 43 Quality is about customer perception
  42. 42. Mario Faria 44 What you can do : Establish a customer oriented mentality within your team
  43. 43. How  did   some     organizaGons   change  to  a   data  driven   culture  ?  
  44. 44. Make Everyone in the organization feel responsible for Data Quality
  45. 45. How prepared is your business to have a lean data quality program in place ?
  46. 46. Time People Technology
  47. 47. Some bonus tips and recommendations
  48. 48. Mario Faria 50 Start where it hurts the most
  49. 49. Mario Faria 51 Learn from mistakes
  50. 50. Mario Faria 52 Be flexible and adapt to changes fast
  51. 51. Mario Faria 53 Source : Leading Strategic Initiatives (www.leadingstrategicinitiatives.com)
  52. 52. Conclusions  
  53. 53. Mario Faria 55 Data, Information, Analytics, Business Intelligence and Performance Management
  54. 54. “The Data Asset: How Smart Companies Govern Their Data For Business Success” - by Tony Fisher
  55. 55. Mario Faria 57 •  A good CDO can implement a data organization with success •  A great CDO has the ability to turn raw data into new revenue streams for the business •  Components such as technology and methodologies are important, but they are just enablers •  The CDO focus is delivering enterprise value to the business (not writing code or SQL scripts) From good to great CDO
  56. 56. Mario Faria 58 How leaders can benefit from using Lean for Data Quality programs •  Increase of productivity •  Increase throughput •  Improve of quality •  Reduce of cycle times •  Less fire-fighting •  Smooth operation •  Reduce costs
  57. 57. Mario Faria 59 Golden Rules to Success in Data Quality •  Find out the Why •  Strategic vision and a plan in place •  Strong Data Quality leader •  Secure investments and budget •  Always deliver results
  58. 58. Mario Faria 60 Future of Data Quality
  59. 59. Mario Faria 61 When was the last time ?
  60. 60. Mario Faria 62 “Continuous improvement is not about the things you do well — that’s work. Continuous improvement is about removing the things that get in the way of your work. The headaches, the things that slow you down, that’s what continuous improvement is all about.” Bruce Hamilton , lean thought leader
  61. 61. Mario Faria http://www.cdo-inc.com www.slideshare.com/fariamario Twitter : @mariofaria mario.faria@cdo-inc.com +1 (425) 628-3517

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