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Poor data management weakens an organization's ability to conduct business, effectively manage customers, deliver timely product services, and grow profitably.
Fremont, CA: Data is a corporate asset, but it is frequently regarded as a waste product. Many businesses lack the controls required to ensure data integrity and provide insight into business operations. Systemic risks persist if not addressed, stifling business growth.
Mistakes in business today are costly and potentially disastrous. Guessing is not an option. Organizations require better data stewardship in light of increased regulatory scrutiny, market volatility, insatiable internal demand for answers to increasingly complex questions, and shareholder demand for better returns as well as greater traceability to financial results.
Why is managing data a challenge?
Poor data management weakens an organization's ability to conduct business, effectively manage customers, deliver timely product services, and grow profitably. Worse, a lack of appropriate data controls has an impact on regulatory compliance, including Solvency, Basel, Anti-Money Laundering, and KYC. Data management issues can manifest themselves in a variety of ways, including:
• Uncertain data stewardship and accountability for mitigating system risks
• Data that is redundant, inaccurate, and spread across disparate data silos
• Misaligned initiatives due to uncoordinated funding
• Missed performance targets
• Inability to adapt to the accelerating rate of market and regulatory change
• Inappropriate utilization of technology to manage data across the enterprise
According to a recent independent survey, 36 percent of financial institutions surveyed assign responsibility for data to the IT department, while 16 percent admit that no specific responsibility for data ownership has been identified. Furthermore, according to a 2010 Data Governance Institute survey, only 29 percent of respondents calculate the monetary cost of poor data quality, and only 23 percent of successful programs have the following characteristics:
- A data governance mission statement;
- A clear and documented process for resolving disputes;
- Good policies for controlling access to business data;
- Effective logical models for key business data domains; and
- Either high-level business processes are defined or fully documented at multiple levels and available for data governance.
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