Carnegie Mellon University SEI and EDM Council complete best practices for data management

Source: Carnegie Mellon University

The Carnegie Mellon University Software Engineering Institute (SEI) and the Enterprise Data Management (EDM) Council yesterday announced that the core content of the Data Management Maturity model is complete.

The SEI and the EDM Council have been working in conjunction with data management professionals since 2009 to document the capabilities and business processes required for effective data management across the entire data life cycle. This process has resulted in the completion of a Data Management Maturity (DMM) model that defines requirements for developing a data management strategy, implementing governance, managing data operations, improving data quality and integrating data effectively into business processes.

With the completion of the core content of the DMM model, the SEI and the EDM Council will move forward with the creation of a program for training and certifying appraisers of data management capabilities. The initial funding for development of the criteria required for this certification was provided by Booz Allen Hamilton. "We know from experience that the need for improved data management is widespread and growing, especially with financial organizations. In our engagements, we find that organizations benefit substantially when better data management practices are implemented," said Leslie DiFonzo, a Senior Vice President with Booz Allen Hamilton. "The potential benefits from a Data Management Maturity model motivated us to collaborate with the SEI and the EDM Council to develop the model and to provide the initial funding."

The concept of data management as an essential component of business operations has gained prominence in the wake of the 2008 credit crisis and supports the transparency and systemic risk objectives contained within the Dodd-Frank Wall Street Reform Act and similar international directives such as the European Market Infrastructure Regulation, Solvency II directives and the Basel Accords. All of these legislative initiatives require companies to comply with standards and are dependent on the availability of accurate and comparable data from many diverse sources.

Achieving trust and confidence in data is a challenge in today's business environment due to independent business silos, inflexible IT environments, a lack of standards for data content and obstacles associated with gaining stakeholder alignment across the organization. "The old adage of 'you can't manage what you can't measure' is also true for data," said Michael Atkin, Managing Director of the EDM Council. "The DMM model not only provides organizations with a definition of the 'what and why' of managing data as meaningful content, it provides a standardized and consistent mechanism for measuring data management capabilities against both business objectives and oversight requirements," Atkin explained.

One of the beneficial outcomes of the financial crisis is a strong and growing recognition by both financial institutions and regulators of the importance of being able to monitor risk through access to accurate, comprehensive and aligned data—and share it across functions without the need for manual reconciliation or imprecise cross-referencing. While the need for effective data management is clear, a comprehensive and standardized mechanism for guiding firms does not yet exist. The DMM model is designed to fill this gap. It provides a framework and assessment methodology for evaluating the effectiveness of data management practices and a clear evolutionary path to establish a data management culture.

The DMM model has been developed via collaboration among expert data management practitioners, operational experts, IT professionals and representatives of lines-of-business. The model is based on the proven principles of the Capability Maturity Model Integration (CMMI) methodology, a standard for software development process improvement for more than 20 years. Combining the process strengths of the CMMI and the data management best practices independently defined and verified by industry practitioners, the DMM model promises a unique and definitive solution to a growing international problem.

"The SEI is proud to be collaborating with the EDM Council on this important project. We look forward to applying our past experience with CMMI and process improvement in the new area of data management to solve pervasive problems facing all organizations that collect and use data," said Paul Nielsen, Director and CEO of the SEI. "We believe this collaboration will result in a new collection of best practices that can dramatically improve effectiveness, efficiency and quality of data."

Early efforts by organizations contributing to the DMM model reveal its promise. "Citi is an early and active contributor to the DMM model," said Heather Wilson, Chief Data Officer at Citi. "We were also one of the first organizations to operationalize the model in the form of an assessment. We originally envisioned the DMM model as a means to provide a measure of our data management capabilities in a structured manner. We've used the DMM model to identify the areas and priorities for improvement with the hope that it would become an industry standard. As the DMM model has evolved, it has become a foundational element of all our data programs, helping to bring alignment and an objective view on progress. The DMM model represents an important dimension to our data management policies and strategy."

The combination of expertise supplied by the SEI, the EDM Council and independent industry practitioners makes the DMM model a first-of-its-kind approach for organizations to assess themselves and upgrade their management of data as a strategic resource. 

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