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Using Lean Principles to Manage the Data Value Chain
Mario Faria discusses the importance of managing data as a critical asset to enhance business performance through lean principles and effective data governance. He outlines essential roles in data management, including the Chief Data Officer, and emphasizes the need for a strategic approach to transform raw data into valuable insights. Key challenges include fragmented data, silos, and achieving data quality, which can be mitigated by establishing a customer-oriented mentality and implementing continuous improvement practices.
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Using Lean Principles to Manage the Data Value Chain
- 1. Using Lean Principlesto 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. Mario Faria 2 About MarioFaria • 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. Managing your most importantasset to drive business performance
- 4. In May 1915, The Boston Red Sox Babe Ruth pitching debut and his first home run, but …
- 5. The Rex Sox lost to the NY Yanks
- 6. Your data strategy is a journey
- 9. Mario Faria 9 The 3Architectures a Company needs to succeed Business Architecture Technology Architecture Data Architecture
- 10. 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
- 11. 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
- 12. Data teams build the bridge between business and IT
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- 15. Mario Faria 15 A dataproduct allows an objective to be achieved using data & analytics
- 16. Mario Faria 16 More andmore, leaders are being hired to think strategically about all the steps, from getting raw data and making it useful to the business users
- 17. 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
- 18. Mario Faria 18 A fewlessons 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
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- 20. Mario Faria 20 The DataValue Chain
- 21. Mario Faria 21 A fewproblems 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
- 22. Mario Faria 22 Data isan abstract concept
- 23. Using Supply Chain Conceptsand Techniques to manage your data assets
- 24. Mario Faria 24 Data &Analytics as a Production System
- 25. Mario Faria 25 The DemingModel : Production Viewed as a System
- 26. Mario Faria 26 What isData Quality ? • Quality is a customer perception • A few dimensions: freshness, coverage, completeness, accuracy • It is a never ending job
- 27. Mario Faria 27 A FewQuality Programs TDQM TIQM
- 28. Mario Faria 28 Source: DanMyers, The Value of Using the Dimensions of Data Quality, Information Management
- 29. Implementing Lean Best Practices thatcame from the Toyota Manufacturing Process
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- 31. 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
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- 34. Mario Faria 34 The 8-Basicsof Kaizen Based Lean Manufacturing, by Bill Gaw http://bbasicsllc.com/
- 35. Mario Faria 35 • Specifythe 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
- 36. 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
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- 38. Mario Faria 38 The PredictiveAnalytics Factory Concept
- 39. Mario Faria 39 Data ValueChain Monitoring Centers
- 40. Right People Right Data Right Technology
- 41. 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
- 42. Mario Faria 42 Problems withData 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
- 43. Mario Faria 43 Quality isabout customer perception
- 44. Mario Faria 44 What youcan do : Establish a customer oriented mentality within your team
- 45. How did some organizaGons change to a data driven culture ?
- 46. Make Everyone in theorganization feel responsible for Data Quality
- 47. How prepared isyour business to have a lean data quality program in place ?
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- 50. Mario Faria 50 Start whereit hurts the most
- 51. Mario Faria 51 Learn frommistakes
- 52. Mario Faria 52 Be flexibleand adapt to changes fast
- 53. Mario Faria 53 Source :Leading Strategic Initiatives (www.leadingstrategicinitiatives.com)
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- 55. Mario Faria 55 Data, Information,Analytics, Business Intelligence and Performance Management
- 56. “The Data Asset:How Smart Companies Govern Their Data For Business Success” - by Tony Fisher
- 57. Mario Faria 57 • Agood 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
- 58. Mario Faria 58 How leaderscan 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
- 59. Mario Faria 59 Golden Rulesto 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
- 60. Mario Faria 60 Future ofData Quality
- 61. Mario Faria 61 When wasthe last time ?
- 62. Mario Faria 62 “Continuous improvementis 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
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