Sustaining Data Governance and Adding Value for the Long Term

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. 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. 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. www.firstsanfranciscopartners.com Level SeTng

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. 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. 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. 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. www.firstsanfranciscopartners.com Obstacles & Challenges

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. 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

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. www.firstsanfranciscopartners.com Establishing the OrganizaQon

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. www.firstsanfranciscopartners.com Alignment

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. 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. 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

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. 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. 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. 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. 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.

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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. 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. 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. 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. www.firstsanfranciscopartners.com CreaQng Metrics

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. 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. 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. 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. 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)

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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. 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. 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. •  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. 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. 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. 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. 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. www.firstsanfranciscopartners.com Embedding Data Governance

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

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

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. www.firstsanfranciscopartners.com Program / Project Alignment

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. 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. 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. 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. 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. 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. 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. 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. 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. 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. www.firstsanfranciscopartners.com Ensuring Success

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. 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. 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

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. 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. 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. www.firstsanfranciscopartners.com Leadership Roles & Decision Making Bodies pg 91

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. 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. 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. www.firstsanfranciscopartners.com Data Governance Roles

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. 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. 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. 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. 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. 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. www.firstsanfranciscopartners.com The Data Governance Oﬃce

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