Experian-2019全球数据管理调查报告（英文）-2019.3-20页_1mb

2019 Global Data Management Research Summary

Core Content

This 2019 global data management research conducted by Experian, with insights from Insight Avenue, highlights the challenges and opportunities businesses face in leveraging data effectively in the digital age. The study surveyed over 1,000 data practitioners and business leaders across the United States, the United Kingdom, Brazil, and Australia, spanning multiple industries such as IT, telecommunications, manufacturing, retail, and healthcare. The research focuses on three main areas: Customer Experience, Trust in Data, and Changing Data Ownership.

Main Views

1. Customer Experience is a Strategic Priority

• Customer experience is now seen as a top strategic business driver, with 53% of respondents identifying it as their main focus.
• Achieving a Single Customer View (SCV) is critical for improving customer experience, but it remains a challenge due to:
  • Poor data quality (30% of respondents cite this as a key issue).
  • Rapidly changing customer interaction methods (30%).
  • Legacy systems and lack of modern technology (30%).
• 98% of companies use data to improve customer experience, but only 42% have a SCV in place, with the majority relying on a central CRM.
• The concept of SCV is debated, with some viewing it as a centralized repository and others as a contextual or individualized view.

2. Trust in Data is a Major Hurdle

• 95% of organizations report that poor data quality negatively impacts business performance.
• 29% of current customer/prospect data is suspected to be inaccurate, incomplete, or inconsistent.
• 70% of businesses say they lack direct control over data, which hinders their ability to meet strategic objectives.
• Data management maturity has not improved significantly in the past three years, with many still relying on outdated practices.
• Building trust requires:
  • A better understanding of the current data landscape.
  • Developing a clear data strategy with C-suite support.
  • Identifying quick wins to demonstrate improvement and build momentum.
  • Implementing data remediation and monitoring practices.

3. Data Ownership is Evolving

• 89% of companies face challenges in managing data, often due to:
  • Lengthy delays in gaining insight (42%).
  • Lack of trust in data (40%).
  • Lack of customer insight (39%).
  • Lack of ability to use data (39%).
• 84% of data is still managed primarily or only through IT, which is not ideal as IT teams often lack the business context needed for effective data management.
• There is a growing desire to decentralize data ownership, giving more control to business users and promoting data democratization.
• 75% believe data quality responsibility should lie with the business, with occasional support from IT.
• The shift toward a decentralized model is seen as essential for aligning data practices with business goals and improving agility.

Key Information

• Data quality is a critical issue, with poor data undermining business performance, customer experience, and regulatory compliance.
• SCV is a key goal for improving customer experience, but its implementation is hindered by technical and organizational challenges.
• Technology must be modern, modular, and adaptable to support evolving data needs and user requirements.
• Talent in data roles such as data analysts, data engineers, and data scientists is vital for bridging the gap between technical and business requirements.
• Data ownership is shifting from centralized IT control to a more decentralized approach, emphasizing the need for business-led data governance and management.

Conclusion

The research underscores that while data is increasingly recognized as a strategic asset, its full potential is often unrealized due to issues like poor quality, lack of control, and outdated management practices. To succeed in the digital economy, organizations must invest in people, processes, and technology that support flexible, trustworthy data management and contextual customer views. The shift toward decentralization and the democratization of data is a necessary step to align data practices with business objectives and foster innovation.