Enterprise Data Management
Deloitte has helped many of the world’s leading organizations design, develop, and execute effective Enterprise Data Management to support business transformations, achieve regulatory compliance, and enable key business processes.Technologies frequently used include SAP, IBM, SAS/DataFlux, Informatica, and Microsoft.
Managing enterprise data
The data deluge of the past decade is quickly turning the ability to effectively harvest and harness data across the enterprise into a competitive differentiator. However, as many have and continue to spend heavily on core-system and technology optimization, most still find their efforts fall short of expectations; if data is expected to be recognized as a strategic asset, merely tweaking existing systems and business models no longer suffices. Strategically redefining the way information is gathered, stored, defined, governed, analyzed, and disseminated is the only way to realize the benefits of data as a strategic asset and successfully stay in the game.
EDM ensures data is managed to its full potential to guarantee the right information continues to get to people when and how they need it to do their jobs effectively.
We’ve helped many of the leading organizations in their efforts to design, develop and execute an effective Enterprise Data Management to support business transformations, ensure regulatory compliance and support their key business processes.
Bottom-line benefits
Ensure Sponsorship — Ensure executive stewardship, champion and implement data management strategies and standards, institutionalize data quality management.
Measure and manage data risk — Reduce various risk by ensuring data transparency (cfr. Solvency II, BASEL III) and increase data quality and governance.
Support corporate strategy — Enable analytics for decision-making, ensure data is available to the right people at the right time.
Improve the top line — Increase revenue, customer approval ratings, customer retention and market goodwill through the effective governance and use of data.
Improve the bottom line — Lower the cost of quality and cost of compliance, improve productivity through availability of timely and correct data.
How we can help
Our EDM service offering provides a complete range of capabilities to support companies in the following areas:
Enterprise Information Strategy — The definition of an enterprise-wide strategy and roadmap for both structured and unstructured data that is in line with the company's Corporate Strategy to most optimally support a company's key business processes.
Data Governance & Processes — The organization, policies, processes and tools required to maintain the standardized definition of a data element.
Data Quality — The capability to provide reliable data that satisfies the business functions and technical requirements of the enterprise.
Master Data Management — The management of the fundamental data building blocks that are shared across multiple business transactions.
EDM Architecture — The definition of systems, tools and models ensuring integration with corporate infrastructure.
Data Strategy
The continuous emergence of data and information-related trends, both in the public and in the private sector, drives the need to recognize and manage data as a strategic asset and leads to an increased demand for data management. The asset-centric perspective is a proactive approach that fully acknowledges this situation and recognizes the need for a clearly defined data strategy that is closely integrated with the overall organizational strategy.
Data Quality Framework
Organizations of various sizes and industries are increasingly recognizing the importance of high quality data and the critical role of data quality in information governance and stewardship. Enterprise information management initiatives drive this trend. By assessing and monitoring data quality, it is possible to avert problems and maximize the value of the data on hand.
Deloitte has developed a data quality framework specifically designed to assess the data risks and data health. The framework facilitates analysis and provides insights into the root causes of poor data quality. It also offers appropriate remediation recommendations to enhance data standardization activities. Data quality monitoring is performed on an ongoing basis to ensure sustainable data quality.
The Data Quality framework is a continuing process and recognizes the strategic and tactical goals.