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The Five Pillars of Data Governance 2.0 Success

What’s the state of data governance readiness within your organization?

Do you have an executive sponsor?
Is a standard definition understood across the enterprise?
How does your IT team view it?
How does your organization approach analytics, business intelligence and decision-making?
Have you implemented any technology to provide the necessary capabilities?

These are just a few of the questions you should be asking to determine whether your organization is a data governance leader, laggard or novice. With the General Data Protection Regulation (GDPR) about to take effect, there’s no time to waste in determining whether your’re really ready.

erwin and DATAVERSITY want to help you shore up your data governance initiative so you can use your data to produce the desired results, including but not limited to meeting information security and compliance requirements.

You’ll learn what it takes to build and sustain an enterprise data governance experience – not just an isolated program – for greater visibility, control and value to achieve regulatory compliance and so much more.

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The Five Pillars of Data Governance 2.0 Success

  1. 1. The Five Pillars of Data Governance 2.0 Readiness A D A T A V E R S I T Y W E B I N A R March 8, 2018
  2. 2. Today’s Speakers © 2018 erwin. All rights reserved. 2 Mariann McDonagh CMO, erwin Inc. Jamie Knowles Product Director, erwin Inc. https://www.linkedin.com/in/mariannmcdonagh/ https://www.linkedin.com/in/jamieknowlesltd/@mcdonaghmariann
  3. 3. Our Agenda © 2018 erwin, Inc. All rights reserved. 3 Highlights of erwin State of DG Report/research Assessing your readiness: what matters most Getting there from wherever you are
  4. 4. erwin’s Take on the State of DG Traditional DG has failed. Successful DG requires a different approach that empowers the enterprise. Readiness is key to success. DG should be measured and measurable in the context of the business. DG accomplishes regulatory compliance and so much more. © 2018 erwin. All rights reserved. 4
  5. 5. Enterprise Data Governance Experience (EDGE) 5 Regulatory Peace Of Mind Visibility Across Domains Integrated Ecosystem Any Data Anywhere Collaboration & Organizational Empowerment
  6. 6. Fuel Organizational Success Across the Board 6 Improved Decision-Making Increased Customer Satisfaction Compliance, Privacy & Security Operational Efficiency Revenue Growth
  7. 7. erwin State of Data Governance Report © 2018 erwin, Inc. All rights reserved. 7 • Surveyed North American companies in 16+ sectors, including financial services, government, healthcare, IT and telecommunications • Respondents included CIOs, CTOs, data center managers, IT staff and consultants In partnership with
  8. 8. Our customers have told us data governance is at the heart of their initiatives. We wanted to confirm that customer feedback and gather more information from the larger market. We wanted to understand who owns data governance, what is driving their interest, why they are making their decisions, and how they are using their data assets. 8 Why Commission a Survey? © 2018 erwin, Inc. All rights reserved.
  9. 9. 9 Key Findings DEFINITIONS ABOUND But it’s clear organizations are coming at data governance from many different angles. © 2018 erwin, Inc. All rights reserved.
  10. 10. 10 Key Findings A CONTRADICTION IN TERMS 98% of respondents view data governance as either important or very important from a business perspective. However, a disquieting 46% don’t have a formal governance strategy. © 2018 erwin, Inc. All rights reserved.
  11. 11. 11 Key Findings DO WE EVEN HAVE A BUDGET FOR THAT? More than one in five (21%) are just getting started, meaning they’re in the data discovery and inventory phase, and 63% either don’t have a budget for data governance or don’t know if they do. © 2018 erwin, Inc. All rights reserved.
  12. 12. 12 Key Findings WHERE IS THE ENTERPRISE IN ALL OF THIS? At 40% of the organizations surveyed, the IT department continues to foot the bill for data governance expenses. © 2018 erwin, Inc. All rights reserved.
  13. 13. 13 Key Findings OBJECTS IN MIRROR ARE CLOSER THAN THEY APPEAR Only 6% of enterprises are prepared for GDPR, with less than four months until the regulation goes into effect. © 2018 erwin, Inc. All rights reserved.
  14. 14. 14 Key Findings WHO’S IN CHARGE? © 2018 erwin, Inc. All rights reserved. 57% say both IT and the business are responsible for data governance, yet 68% say the CIO is driving the process.
  15. 15. 15 Key Findings DG ISN’T JUST FOR COMPLIANCE ANYMORE 60% say regulatory compliance is the biggest driver, but it’s not the only one. 49% see it as a way to improve customer satisfaction, and 45% see it supporting better decision-making. Reputation management (30%), analytics (27%) and Big Data (22%) are also key drivers. © 2018 erwin, Inc. All rights reserved.
  16. 16. 16 Key Findings ROADBLOCKS 58% of respondents report the biggest obstacle is the cost of data governance, followed by understanding the right approach (42%), executive support (42%); organizational support (39%), effective tools (36%) and articulating business justification (27%). © 2018 erwin, Inc. All rights reserved.
  17. 17. Quick Poll … How ready are you? 17 Category 1 Category 2 Category 3 Category 4 Category 5 © 2018 erwin, Inc. All rights reserved. 1. Laggard. Have not even begun a DG project in our business 2. Novice. We have a strategy and are just beginning to assemble a team 3. Leader. We have a comprehensive DG strategy that is enterprise wide, its resourced and funded
  18. 18. Advice on Readiness K E Y T H I N G S T O C O N S I D E R
  19. 19. Pillars of DG Readiness 19 • Initiative Sponsorship • Organizational Support • Team Resources • Enterprise Data Management Methodology • Delivery Capability © 2018 erwin, Inc. All rights reserved.
  20. 20. Initiative Sponsorship 20 GET REAL WITH EXPECTATIONS Realistic expectations are needed, or the data governance team won’t be able to deliver against expectations. The initiative is likely to fail and be abandoned. SPONSORS ARE KEY Without executive sponsorship, your initiative will have difficulty obtaining the funding, resources, support and alignment necessary for successful implementation. ENGAGEMENT MATTERS If your sponsors are passive or only figureheads, you should consider ways to increase their involvement or solicit additional sponsors. © 2018 erwin, Inc. All rights reserved.
  21. 21. Organizational Support 21 LEARN FROM OTHERS Definitions should be based on industry standards and accepted best practices to ensure the initiative is based on sound fundamentals. LONG-TERM FUNDING IS ESSENTIAL Data governance requires continued funding, which should come from the enterprise, not be project-based. IT’S A CULTURE SHIFT Data governance must be integrated into the company’s current culture. IT HAS TO BE MEASURED TO COUNT Scope and success factors should be defined to establish parameters and metrics for evaluation. © 2018 erwin, Inc. All rights reserved.
  22. 22. 22 RELATIONSHIP Understanding the relationship between data management and data governance is key. data management are supported by these programs. EXPERIENCE Most organizations lack enterprise-level DG experience, which is required to advance organizational goals. TEAM © 2018 erwin, Inc. All rights reserved. Most successful organizations have established a formal data management group that resides at the enterprise level because it recognizes the need for managing data as an enterprise asset. Team Resources IT’S VIEW IT must be an active participant in any DG initiative, since IT is the main technical enabler of successful data governance.
  23. 23. Enterprise Data Management Methodology 23 GET META Metadata management provides every organization with contextual information concerning data assets. BI COMPONENTS TO SUCCESS MDM MDM benefits from DG because of governing common and reference data across the organization with cross-departmental standards and definitions, allowing data sharing and reuse, reducing data redundancy and storage, avoiding data errors due to incorrect choices or duplications, and supporting data quality and analytics. © 2018 erwin, Inc. All rights reserved. DG is a foundational component of enterprise data management. It and metadata management, enterprise data architecture, data quality management, etc., are essential to success. BI/analytics benefit from DG due to the ability to govern data from its sources to destinations in warehouses/marts, defining standards for data across those stages, and promoting common algorithms and calculations where appropriate.
  24. 24. Delivery Capability 24 DATA MODELING Enterprise data modeling, a component of enterprise data architecture, is an enabling force in the performance of data management and successful DG. EFFECTIVE TOOLS DG requires a specific tool suite. Selecting the proper DG solution should be done as part of the development of technical requirements for the DG initiative. DATA QUALITY Solution selections, including those for data quality management, should be based on the organization’s business goals, its current state of data quality and the rest of enterprise data management, and best practices as promoted by the data quality management team. FORMAL DG UNIT Having the capability to manage all DG operations and coordinate data stewardship activities can have a positive effect by giving the DG initiative administrative support for program management. © 2018 erwin, Inc. All rights reserved.
  25. 25. Final Poll: Any change to your earlier answer on readiness? 25 Category 1 Category 2 Category 3 Category 4 Category 5 © 2018 erwin, Inc. All rights reserved. 1. No change to my assessment of our readiness. 2. Food for thought. We need to consider some of these issues
  26. 26. What Should Organizations Look for in DG Technology? © 2017 erwin. All rights reserved. 26 Understand Data Dictionary Data Quality Data Usage Discover Reference Data Business Glossary Socialize Data Sets Data Issues Impact & Lineage Govern Policies and Rules DGOM Collaboration Workflow Collaboration Shared Services Integration
  27. 27. The erwin EDGE Platform 27
  28. 28. Data Governance: The Driving Principle 28 UNDERSTANDDISCOVER SOCIALIZE Data Sets Data Issues Impact & Lineage GOVERN Policies and Rules DGOM Collaboration Data Dictionary Data Quality Data Usage Reference Data Business Glossary D ATA V I S I B I L I T Y, C O N T R O L & C O L L A B O R AT I O N U N L O C K B U S I N E S S VA L U E What do we have? What does it mean? Where did it come from? Is it secure? What rules or restrictions apply? How accurate is it? Who is accountable? Who is using it? How is it used? How can I access it? Where is it? DATA IN CONTEXT
  29. 29. Take the Next Step: Visit erwin.com © 2018 erwin. All rights reserved. Download our ebook Request the report
  30. 30. Coming Soon: erwin DG RediChek™ © 2018 erwin, Inc. All rights reserved. 30
  31. 31. No Buts About It … 31 DG must align with your unique organizational goals. What’s driving your DG program, and where do you start? erwin understands data and how to govern it. Real-world DG requires a cultural shift. Our platform creates an EDGE for measurable outcomes. Let erwin be your guide in all this. e r w i n . t h e d a t a g o v e r n a n c e c o m p a n y .
  32. 32. Q&A

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