Actionable Information Governance

[Steve Bennett]

A Practical Approach To Corporate Information Governance It sounds obvious that deciding what it is that you want to govern is essential - but information is a complex beast with many facets. I find it useful to think about the capabilities that I need to have. These are the basic parameters that determine my scope - and the nature of the challenges in delivering them. In my world of corporate business intelligence I believe that there are 26 capabilities related to information management. I like to group them into 8 categories: Now you don't have to include all 26 capabilities into your scope. For many reasons it is possible to exclude one or more. You would generally do this because: The organisation is not mature enough to develop the capability. An example may be where business intelligence is new to the organisation and the strategic decision is made to concentrate on governing only structured data important to management reporting. In this case (for example) the Content Management capability may be out of scope. Budget constraints. You outsource parts of your corporate BI. An example may be where all application development is outsourced to another company. In this case the Data Integration capability may be out of scope. To explain what each of these capabilities are, here is a brief definition in the following sections. IM Capabilities Strategy Group 1. Strategy Development Create and execute the information management strategy in the organisation. The strategy includes the processes, procedures, policies, principles, technologies, and architecture that manage data from definition to destruction, which includes transformation, governance, quality, security, and availability throughout its life cycle. Definitions of service-level agreement (SLA) requirements are in scope. 2. Information Architecture An architecture improves our use of information across the full information life-cycle. In the long term, an architecture reference model will focus on the flow of data through various data management layers. These include infrastructure, data sources, data rationalisation and data movement, as well as data usage. The architecture supports the organisation of data across various databases and applications, based on business requirements. It enables data standardisation and integration across the enterprise, not just for one or two databases or data sources. A formal data management reference architecture will deliver higher service levels and support newer applications and platforms more easily. It includes comprehensive data definitions, data structures, and data integrity rules across the enterprise. It ensures that businesses use data in a consistent manner throughout. Trust Group 3. Data Quality Management Test data quality using a consistent national data quality framework and ensure remediation is done when required. Data quality management ensures that enterprise data used by business stakeholders supports critical business processes and decisions with no reservations as to its relevance, freshness, accuracy, integrity, and other previously agreed-on aspects of quality. 4. Data Governance Create a successful organisation that leverages analytics for competitive advantage by providing business insight, enabling better decision making, and driving strategy. 5. Master Data Management Create and manage information about business...



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