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Information |


Information component in Brief

The transformation of raw data into information and then into knowledge is a central feature of the maturity model. The empirical evidence also supports this finding, as often the inhibitors, challenges and pitfalls were related to bad data quality, information incoherence, and the improper use of operational information systems.

Howard Dresner1 came up with the concept of Information Democracy, by which he means that every employee in an organization should have the information they need to make decisions. This information should be freely available, without the need to ask someone for it. Dresner also suggests that management should not censor or filter such information. Rather, everyone should have access to raw data, which they can analyse and then process into information and knowledge which can be shared with others in the organisation. The information component in this maturity model focuses on much the same issues as those presented by Dresner in his book.

The information component is further divided into three subcomponents: 1) data and information quality, 2) information production, distribution and availability, and 3) common structures and master data. Each of these subcomponents focuses on the various aspects of information, its properties, and its lifecycle.

Key capabilities and management practices

  • High quality data
  • Common structures and business vocabularies
  • Master Data
  • Trust in data and information
  • Automatization of data collection
  • Integration of data
  • Easy access to data and information

See also other components

Maturity levels for Information component

Level 1 Level 2 Level 3 Level 4 Level 5
Bad quality and scattered data; lack of standards, common structures and master data; people cannot access the data they need Business understands the value of information; no trust in information quality and consistency; much redundant and inconsistent data Data quality becomes better; collecting financial data is highly automatized; data warehouses have timely data; common data model and business vocabulary; better data availability; people have access to data they need in their work Data and information are high quality; understanding that information is critical for business; all relevant performance data is available in data warehouse; data is available for every measure; performance data is used for analysis Information is trusted across the organization; data is fully integrated; information is highly valued asset in the organization


  1. Dresner (2007)

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