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Lead Your Data Revolution - How to Build a Foundation of Trust and Data Governance

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<p>Becoming a data-driven organization is something many companies aspire to, but few are able to obtain. Let’s face it: Data is confusing. It is complicated, dirty, and spread out all over a business. While companies are making big investments in Data Management projects, only a few are seeing the payoff. </p>
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<p>New research from Experian shows that despite many ongoing data initiatives, 69 percent of organizations struggle to be data-driven. The struggles are real. Companies face a large data debt, look at data projects through a siloed lens, and still have a large volume of inaccurate data. In fact, 65 percent report inaccurate data is undermining key initiatives. <br></p>
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<p>However, the tide is turning. Businesses are starting to adopt data enablement, or a practice of empowering a larger group of individuals within the business to understand and harness the power of data and analytics. Companies that empower wider data usage are better able to comply with regulations, improve decision-making, and, of course, deliver a superior customer experience. Are these the results you’re striving for? </p>
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<p>Join us to uncover new research from more than 500 Data Management practitioners as we take a deep dive into:</p>
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<ul><li>The top challenges in becoming a data-driven organization </li><li>Trends and the rise of data enablement </li><li>The profile of a mature organization </li><li>Tips for how you can adopt data enablement practices</li></ul>
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Lead Your Data Revolution - How to Build a Foundation of Trust and Data Governance

  1. 1. Lead your data revolution: How to build a foundation of trust and data governance Presented by: Kevin McCarthy, Director of Product Marketing Erin Haselkorn, Head of Market Research
  2. 2. 2 © Experian Public • Our methodology • Key findings • Top challenges in becoming a data-driven organization • Trends and the rise of data enablement • Profile of a mature organization • Questions What we’ll cover
  3. 3. 3 © Experian Public We spoke to 517 U.S. managers with knowledge and/or visibility of data management practices at businesses with 250+ employees. Our methodology Department Seniority 3% 1% 1% 3% 4% 8% 10% 14% 16% 20% 20% Other Innovation Risk management Research and development Customer services Information Technology (IT) Sales Finance Operations Data / insight / analytics Marketing CEO / C-level 23% Director-level 29% Manager-level 48%
  4. 4. 4 © Experian Public 61% say it takes too long to get actionable insights from data. 66% say those improving data quality often do not fully understand the needs of the business. Data enablement is a key focus over the next 12 months for 57% of respondents. Key findings 4 © Experian Public 64% say they do not have enough talented data professionals. 69% see most data management initiatives occur in individual departments. 69% say despite many ongoing data initiatives, their organization still struggles to become data-driven.
  5. 5. 5 © Experian Public Major takeaways 1. Despite major investments in big data projects, most are struggling to become data-driven. 2. Most organizations are missing a key cornerstone to data management success: a foundation built on data quality and trust. 3. To improve data usage, organizations must supply the right data talent and technology, while promoting a data culture.
  6. 6. 6 © Experian Public Lots of data investment, but few measurable results
  7. 7. 7 © Experian Public Data is in the driver seat 69% say despite many ongoing data initiatives, their organization struggles to be data-driven. 58% say data management projects primarily sit with IT, while 42% say they primarily sit with business users. 80% are actively pursuing multiple big data projects. The focus: data quality, big data analytics, and data governance.
  8. 8. 8 © Experian Public 35% 39% 45% 48% 56% 62% 33% 31% 33% 31% 29% 25% 20% 19% 14% 15% 11% 8% 13% 11% 7% 7% 4% 4% Artificial intelligence Machine learning Data literacy Data governance Big data analytics Data quality Currently undertaking Plan to undertake in next 12 months On the radar, but with no fixed timeline Not planned / considered Data management initiatives
  9. 9. 9 © Experian Public Approach to data quality 93% of businesses report progress with data quality in the last 12 months. 61% say they have traditionally underinvested in data quality. Yes, definitely 56% Yes, possibly 37% Not particularly 5% Not at all 1% Don’t know 1%
  10. 10. 10 © Experian Public Big data analytics 12% 20% 20% 25% 26% 27% 28% 31% 32% No challenges in leveraging our data for analytics We don’t trust the information Our data quality is too poor Our data is incomplete We lack necessary skills or human resources We don’t have the right technology It takes too long to prepare the data There is too much data to analyze We don’t have access to all the information we need Challenges in leveraging data for analytics 79% are focused on analytics and how to gain more insight from data. 88% have challenges leveraging data for analytics. 92% plan to leverage AI or ML.
  11. 11. 11 © Experian Public Approach to data governance We are taking a holistic approach that involves a governing body to make decisions, changes in processes, technology and new data governance related roles. 29% We are planning to implement a program within the next 12 months. 27% Processes vary based on individual departments. 26% We have a data governance board but have not decided how to move forward with technology or processes. 16% We don’t have an approach to data governance. 2%
  12. 12. 12 © Experian Public Data governance in practice 29% 41% 45% 48% 48% 51% 52% We want to eliminate data quality issues and develop trust We want to monetize our data We want to be more agile We need to be data-driven We want to improve the quality of our decision-making Compliance with regulations We want to understand how data is used 16% 1% 20% 21% 26% 30% 32% 32% We don’t have any challenges with data governance Other We don’t know where to get started We can’t come to a consensus We lack executive buy-in We don’t have enough knowledgeable resources We don’t have the right technology It is too hard to convince people to follow the new data rules Reasons for implementing a data governance program Challenges in tackling data governance
  13. 13. 13 © Experian Public The data roadblocks, starting with data debt
  14. 14. 14 © Experian Public Stuck in a data rut Only 29% say they take a holistic approach to data governance. 65% say inaccurate data undermines key initiatives. 69% say despite ongoing data initiatives, their organization struggles to be data-driven.
  15. 15. 15 © Experian Public15 © Experian A variety of data management approaches Each organization is unique in its approach to data. Data management falls to different business units, there are varying degrees of maturity, and every initiative should not and cannot be set up the same way. But, we did find common themes: Department vs enterprise approach Foundational element of data quality One-off project vs discipline Data debt
  16. 16. 16 © Experian Public Departments most advanced in leveraging data 1% 2% 20% 25% 31% 33% 34% 36% 39% 44% None of the above / we are not advanced in any areas Other Call center enablement Compliance reporting Marketing campaigns Sales Senior Management decision-making Marketing segmentation Finance Logistics and operations
  17. 17. 17 © Experian Public Level of data quality maturity A - LIMITED 19% B - EMERGING 32% C - DEVELOPING 38% D - MATURE 11%
  18. 18. 18 © Experian Public A (series of) one-off projects 50% A continuous set of processes 50% Is data management seen as series of projects or continuous set of processes? Project vs discipline
  19. 19. 19 © Experian Public The accumulated cost that is associated with the suboptimal governance of data assets in an enterprise. Data debt
  20. 20. 20 © Experian Public The rise of data enablement: Thinking about data in a new way
  21. 21. 21 © Experian Public21 © Experian What is data enablement? The practice where individuals in the business have the support and tools they need to responsibly leverage trusted data to achieve real business outcomes.
  22. 22. 22 © Experian Public Data enablement in practice Companies need to focus on hiring the right talent, getting the right technology, and creating cultural change. 89% say they have challenges in enabling the use of data. 57% of organization cite data enablement as a key focus over the next 12 months.
  23. 23. 46% 48% 49% 49% 54% 55% 56% 56% 58% 46% 39% 39% 41% 38% 39% 38% 39% 33% 8% 12% 12% 10% 9% 6% 6% 6% 8% Grow revenue Enable happier employees Message / communication personalization Gain cost efficiencies Reduce risk Better understanding of the customer Improve customer experience Enable better decision-making Comply with regulations Have achieved Will be able to achieve in next 12 months Neither Outcomes achieved from improved data usage
  24. 24. Enabling the use of data 1% 21% 36% 37% 41% 42% 47% 48% We are not enabling the use of data Hiring a CDO Creating centers of data excellence Creating a true single customer view across the business Consolidating certain sources of information Putting data professionals in data-driven departments Better utilizing data governance to ensure the proper usage of data Providing standardized data across departments % saying these actions have resulted in better outcomes for the business 97% 97% 95% 97% 97% 98% 98%
  25. 25. Challenges to enabling data 11% 21% 22% 23% 25% 26% 28% 29% 33% 33% We don’t have challenges in enabling the use of data Inadequate senior management support Poor data strategy Lack of ownership of data enablement Inadequacies or a lack of technology We lack trusted, quality data Lack of data literacy Insufficient budget Lack of communication between departments Lack of skilled human resources
  26. 26. Starting with the right people 4% 20% 30% 31% 35% 38% 39% 43% We don’t have specialized data roles Data steward Data scientist Data quality analyst Data governance manager Chief data officer Data engineer Data analyst Data roles employed to better leverage data assets 64% say they do not have enough data professionals. The top challenge to enable data in the organization is a lack of skilled human resources.
  27. 27. Investing in tools for everyone 43% 47% 51% 53% 54% 56% 59% 64% 71% 45% 41% 40% 38% 38% 32% 35% 28% 22% 12% 12% 9% 9% 8% 12% 6% 8% 6% Data catalog Master data management Business intelligence or analytics platforms Data governance tools Data integration Product information management Data quality tools Excel Data preparation tools Currently using Plan to use No plans to use 87% report concerns with the tools and technology around data enablement.
  28. 28. Cultural changes Top data enablement challenges include lack of communication, budget, and data literacy. 28 © Experian More mature organizations are more likely to be working on data literacy Lack of general understanding of data across the business Lack of scale and efficiency Focus on individual initiatives, but lack of communication between departments
  29. 29. 29 © Experian Public Profile of a mature business
  30. 30. 30 © Experian Public More likely to undertake all types of data management projects More of a focus on data enablement More likely to have specialist data roles in place—especially a CDO Data management more likely to be seen as a continuous process Less likely to see data quality undermine key initiatives 1 2 4 5 3 Profile of a mature organization Data quality maturity can give us a good indication of companies that are doing something right around data management. Companies of all sizes and industries can achieve this level of maturity.
  31. 31. 31 © Experian Public Major takeaways 1. Despite major investments in big data projects, most are struggling to become data-driven. 2. Most organizations are missing a key cornerstone to data management success: a foundation built on data quality and trust. 3. To improve data usage, organizations must supply the right data talent and technology, while promoting a data culture.
  32. 32. 32 © Experian Public Questions?
  33. 33. 33 © Experian Public Thank you! For more data management insight, view the resources on edq.com

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