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The Enterprise Information Management (EIM) capability ensures that quality data is available to support the business activities of the organization.

• Improve the quality of information available at all levels of the organization to support improved decision-making and business insights.
• Improve the efficiency of business processes by making data and information available that is fit for purpose.
• Provide flexible, dynamic, and centralized data platforms that enable stakeholders to access, interpret, and manipulate data as appropriate to their roles.
• Enable the analysis of data and information to improve the identification and exploitation of new business opportunities by the provision of an appropriate linked data platform.
• Safely and effectively manage data and information throughout their life cycles.

The Enterprise Information Management (EIM) capability provides appropriate operational data for business transactions, and consistently enables timely and informed decision-making.

Data is the lifeblood of any business. It is obtained from many disparate, often discrete, sources: emails, business transactions, operational processes, websites, and so on. In this era of big data, the volume, speed, and variety of data and information continue to increase. In addition, the regulatory and legal requirements relating to data retention and privacy are becoming more complex. For data to be of benefit, it has to address the needs of the organization's employees and customers. It has to be accurate, understandable, and accessible. A life cycle approach to managing data and information¹ can be effective, as this can help inform an understanding of what data is currently stored where and its value to the organization²³.

By establishing an effective Enterprise Information Management (EIM) capability, an organization can manage potential information risks, support ongoing business operations, and enable the strategic development of the organization⁴. It can lead to employee and customer productivity improvements, as better knowledge leads to improved decision- making⁵, fewer mistakes, deeper insights, and identification of new opportunities.

The Enterprise Information Management (EIM) capability is the ability to establish effective systems for gathering, analysing, disseminating, exploiting, and disposing of data and information. The data can be held in any medium — all forms of digital storage, film, paper, or any other recording mechanism used by the organization. The Enterprise Information Management (EIM) capability covers the strategic, operational, and security aspects of information management:

• Establishing an information management strategy.
• Establishing data and information governance mechanisms.
• Establishing information management standards, policies, and controls.
• Performing information valuations.
• Defining and maintaining master- and metadata — for example, metadata for information security classifications and continuity management.
• Making infrastructure and storage decisions.
• Managing data and information life cycles, including data and information tracking.
• Establishing information quality with inputs from stakeholders.
• Measuring how frequently information is accessed and assessing its value to the business.
• Analysing information, including exploratory and confirmative data analysis.
• Developing the skills and competences of information management and analytics practitioners.

Representative POMs are described for EIM at each level of maturity.

2Basic

• Practice

  Ensure management is involved in the development of information management policies, standards, and controls.

  Outcome

  Confidence in a business-focused Enterprise Information Management (EIM) capability grows.

  Metric

  Percentage of relevant stakeholders participating in the approval of information management policies, standards, and controls.

• Practice

  Clearly define information management roles, and provide training for data stewardship, quality, and security.

  Outcome

  Employee competences are improved, and employees take ownership of, and responsibility for, data and information services.

  Metrics

  • Stakeholder satisfaction with data and information availability.
  • Number of roles identified.
  • Number of training programmes offered.

• Practice

  Develop and implement a life cycle approach for the management of the most critical and voluminous data and information.

  Outcome

  Data begins to be properly curated and deleted as appropriate — that is, the organization knows when it is safe to delete data (all uses are complete) and what data is due for deletion (for example, a personal data retention policy states the data must be deleted).

  Metrics

  • Percentage of data sets managed following a life cycle approach.
  • Data sets assigned to a life cycle phase as a percentage of all data sets.

• Practice

  Encourage business unit leaders and champions to promote business intelligence and analytics.

  Outcomes

  • Local business intelligence and analytics activities deliver local gains and enhance expertise.
  • The application of statistics to support decision-making is growing.

  Metrics

  • Percentage of employees with formal enterprise information management, business intelligence, or analytics training and qualifications.
  • Number of reports using analytics.
  • Number of decisions routinely supported by business intelligence and analytics.

3Intermediate

• Practice

  Promote regular alignment of information management, business intelligence, and analytics activities with business objectives.

  Outcome

  Information management services meet the needs of most stakeholders.

  Metric

  Number of major business intelligence goals and analytics-specific goals set by the business and met by using IT-enabled analytical services.

• Practice

  Promote metadata and master data management to improve information quality.

  Outcome

  Information quality issues can be systematically addressed and improved.

  Metrics

  • Transaction data quality — for example, the number of transactions needing rework.
  • Analytical data quality — quality should be looked at in terms of fitness for purpose.
  • For example, marketing may be happy with a 10 per cent accuracy variance, whereas inventory management may want less than 1 per cent variance.

• Practice

  Ensure employees that are assigned to information management roles are suitably qualified and their performance is managed.

  Outcome

  Reliable and professional information management services develop.

  Metric

  Stakeholder satisfaction with data and information management services, as indicated by survey results.

• Practice

  Apply a life cycle approach for information management to most data and information.

  Outcome

  The organization moves from a reactive to a proactive approach to managing key quality attributes of data and information.

  Metrics

  • Data sets whose life cycles are defined and managed as a percentage of all data sets throughout the organization.
  • Number of systems requirements, policy, and process documents referring to information life cycles.

4Advanced

• Practice

  Develop a rolling multi-year planning cycle for the information management strategy.

  Outcome

  Adopting a longer term strategic focus will help deliver greater value over time.

  Metric

  Number of years covered by the rolling information management strategy.

• Practice

  Use cross-functional teams to collectively manage data and information acquisition, storage, and retrieval costs.

  Outcome

  Investment decisions can be more holistic and business value-focused.

  Metrics

  • Percentage of data sets assigned to life cycles with associated acquisition, storage, and retrieval costs.
  • This can be measured at architectural, database, file, view, transaction, or field level.

• Practice

  Implement data classifications and access controls in metadata.

  Outcome

  The management of information artefacts is facilitated.

  Metrics

  • Percentage of data with associated classification and access control metadata.
  • This can be measured at architectural, database, file, view, transaction, or field level.

• Practice

  Design, implement, and manage life cycles for business, technical, and forensics information.

  Outcome

  Cost-effective, well-managed information life cycles ensure information is available when, where, and how it is needed.

  Metrics

  • Percentage of data assigned to life cycles with associated acquisition, storage, and retrieval costs.
  • Number of storage platform moves related to life cycles — that is, does data need to be located in the fastest (usually most expensive) storage or is there a phased movement of data to secondary and lower tier (archival storage) over its life cycles to manage cost?

• Practice

  Encourage management to set ambitious organization-wide business intelligence and analytics targets.

  Outcomes

  • Business intelligence and analytics efforts are focused on issues identified as important by senior management.
  • This focus helps to develop relevant skills, tool usage, and problem solving techniques.

  Metric

  Number of business intelligence and analytics targets.

5Optimized

• Practice

  Regularly review and update information management policies, standards, and controls.

  Outcome

  Continually validating compliance with legal, regulatory, and industry standards reduces risk and enhances reputation.

  Metric

  Number of compliance issues raised per reporting period.

• Practice

  Review information life cycles to maintain their extensibility and flexibility.

  Outcomes

  • New opportunities can be more readily seized where there are flexible data platforms that enable access, interpretation, and manipulation of data by stakeholders.
  • Extensible life cycles can easily be expanded to include new features or life cycle steps.

  Metric

  Number of business opportunities that can be pursued because of the availability of flexible data platforms.

This capability was introduced in Revision 16 as a new critical capability.

It was deprecated in Revision 18.10, being updated by Enterprise Information Management (18.10).

The following CCs cover topics that are related to EIM in some way:

EAMEnterprise Architecture Management

Data architecture guidelines

EAMEnterprise Architecture Management

Designing infrastructure architecture

ISMInformation Security Management

Guidance on information security classifications for metadata to control administration and access.

ISMInformation Security Management

Managing information security

ITGIT Leadership and Governance

Guidance on oversight requirements

KAMKnowledge Asset Management

A catalogue of knowledge assets.

KAMKnowledge Asset Management

Addressing the cultural and organizational aspects of knowledge and information sharing

RMRisk Management

Guidelines on information risk management

RMRisk Management

Managing organizational risk related to technology

SDSolutions Delivery

Designing and building solutions or applications

SDSolutions Delivery

Solution dependent data views or database stored functionality that modifies the view (field combinations), access rights (CRUD), or access permissions. These changes can affect architectural integrity, security integrity, or validation and consistency of the data view.

TIMTechnical Infrastructure Management

Selecting and managing storage infrastructure