The EIM Puzzle – February 2014

EIM-PuzzleDetermining the current state of an organization’s process in a domain is called “assessment” and this is how any maturity model, including the CMM, is used most frequently – to assess the organization’s level of maturity for the discipline.

Assessment using an EIM / enterprise data management maturity model and an industry framework can demonstrate the following effects:

    • For organizations that currently do not engage in EIM, systematically developing and implementing EIM based on the results of an assessment using the complete EIM Maturity Model  and an industry framework reduces risk in projects and delivers higher quality information to users.  Using the EIM Maturity Model and an industry framework as the basis for developing an EIM program can be an effective method for establishing an understanding of the depth and breadth of enterprise information management, and the areas the organization should focus on, and to what extent.
    • After having reached Level 2 of the EIM maturity scale, using the periodic assessment from the EIM Maturity Model can become the basis for proactive management of data / information in the organization.
    • As the organization progresses along the EIM maturity continuum, the EIM Maturity Model and the results gathered from assessments and continued improvement can be used to define, communicate and enforce business-driven information management policy.

Although many organizations struggle with expressing the need for strategic management of information, an assessment based on the EIM Maturity Model and an industry framework for data/information management can be used as a way to address their immediate needs for tactical improvement in data quality and cost reduction from poor data management.  These benefits come as a result of improved data in systems that are used for operational activities.

Data protection, a part of IT governance concerned with the security and privacy of the data stored in information systems is another area of information management that should not be overlooked in developing an enterprise approach to data management since many applications rely on the convergence of high quality master data and related transactional data to satisfy privacy and other regulatory issues.  Often, these collections of data come from different sources and must be reconciled against different formats and so require the application of data governance and master data management practices found in an EIM practice.

Stressing the tactical benefits of enterprise data management does not weaken the strategic view needed for full information management.  However, businesses may want to see the benefits of a tactical approach to EIM before they can justify the implementation of a strategic view of data and its management.  Using the EIM maturity model as the benchmark for assessing their current data management status can give organizations information on what areas should constitute their initial focus for improving the management of their data assets.

A simple assessment can yield significant information about the current state of an organization’s practices in each area of enterprise information management, its strengths / areas of challenge / opportunities for improvement and start a rewarding journey on the road to improved EIM maturity.

It is important to assess all aspects of the enterprise information management / enterprise data management framework, including all the components or domains of enterprise information management in the evaluation to ensure that a complete view of the current state of EIM is developed.  Omitting any of the domains will give a skewed view of the data management landscape for the organization and may offer an overly optimistic perception of the practices and processes that are used in the organization for managing data as an asset.

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Anne Marie Smith, Ph.D.

Anne Marie Smith, Ph.D.

Anne Marie Smith, Ph.D., is an acclaimed data management professional, consultant, author and speaker in the fields of enterprise information management, data stewardship and governance, data warehousing, data modeling, project management, business requirements management, IS strategic planning and metadata management. She holds a doctorate in Management Information Systems, and is a certified data management professional (CDMP), a certified business intelligence professional (CBIP), and holds several insurance certifications.

Anne Marie has served on the board of directors of DAMA International and on the board of the Insurance Data Management Association.  She is a member of the MIS faculty of Northcentral University and has taught at several universities. As a thought leader, Anne Marie writes frequently for data / information management publications on a variety of data-oriented topics.  She can be reached through her website at and through her LinkedIn profile at

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