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Business Scope for Improved Data Governance

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Information Management Roadmap OverviewTesting and Deployment PlanSoftware Development ReadinessDetailed Business RequirementsBusiness Scope for Improved Data GovernanceEnterprise Information ArchitectureRoot Cause Analysis of Data Governance IssuesData Governance MetricsDatabase DesignTaxonomy DesignMetadata DevelopmentMessage ModellingData ProfilingData Re-EngineeringBusiness Intelligence Initial Design and PrototypeSolution Architecture Definition/RevisionPrototype the Solution Architecture
The overall set of activities for Phase 3About this image

Contents

Activity: Business Scope for Improved Data Governance

Objective

The Business Scope for Improved Data Governance involves documenting select business processes that are being addressed as part of the Data Governance initiative to ensure that the usage of Key Data Elements (KDEs) is fully revealed. Business Process Definition includes documenting the users of the data and the systems that touch the data. The documented definition must include both operational and analytical uses of KDEs. By providing a definition of the processes that use the data elements, the impact of missing or erroneous data values can be determined.

Data valuation then assigns value to KDEs that are used to prioritise the scope of the Data Governance program. Data valuation is assigned by linking data elements to the business processes that they enable. Through an in-depth understanding of how a data element enables business process steps, both operational and analytical, and the value of those processes, KDEs can be assigned prioritised values.

To perform this task, Business Analysts are teamed with Business Owners and are allocated with sufficient time to complete valuation analysis. Business Analysts have sufficient business domain experience to analyze Business Process Definitions and assess impact of KDEs. Business Owners provide hard numbers or estimated judgment of impact to their business for missing or erroneous data.

For many implementations there is a hesitation to incorporate Data Governance improvements into the programme, i.e. for a Data Warehouse implementation there may be a resistance to address data quality issues or recommend changes to source systems. This is often the only feasible approach due to funding. Not taking a comprehensive approach to improve Data Governance, however, means that there are risk areas that will not be addressed and these should then be highlighted. At a minimum, the scope of the KDEs to improve Data Governance should be identified.

Major Deliverables

  • Business process definitions, supplemented with information about KDEs
  • Mapping of KDEs to business users
  • Recommended future-state business processes, with process and system improvement opportunities
  • Prioritized KDEs
  • Complement existing business process definition documentation where necessary, with information about how KDEs are Retrieved, Created, Updated, and Deleted
  • Ensure that operational and analytical uses of data are documented
  • Documented process and system improvement opportunities

Tasks

Define Business Process Scope for Increment

Objective:

Based on the business requirements, the scope should be refined to include those areas that will undergo a Data Governance improvement. The Data Governance scope is determined by first mapping the business requirements and processes to the data scope. In the next task, KDEs then are identified to focus this work within the data scope.

Input:

  • Detailed Business Requirements for Increment


Output:

Determine KDEs and Prioritize by Business Impact

Objective:

This task determines the KDEs by meeting with information users and assessing the business impact of missing or erroneous data. These KDEs should then be prioritised based on the interview results and the business value impact due to associated issues. This prioritisation can help drive future requirements for profiling, re-engineering and integration.

KDEs are selected by prioritising them based on value to the business. In addition, other criteria can be considered in prioritising KDEs such as:

  • Scope of KDE in terms of number of business process areas impacted
  • Likelihood of error (e.g., the field is known to have significant quality issues)
  • Pending requirements

Experience has proven that an effective data quality improvement program should not attempt to address every data element but instead should focus on high impact elements. Once the initial set of KDEs meet target quality levels, additional data elements can then be added.

Input:


Output:

Capture Recommend Business Process Changes

Objective:

At this point, there may be some obvious business process changes that can easily be implemented and will provide significant value. Recommendations at this point would involve minor changes to the as-is state as opposed to significant information process re-engineering. Recommendations at this point should not involve technology changes.


Input:


Output:

Core Supporting Assets

Yellow Flags

  • Major issues identified with KDEs but there is not scope within the programme to address root cause issues
  • There is scope within the programme to address issues with KDEs but problems are significant and implementation will result in significant delays to project

Key Resource Requirements

Potential Changes to this Activity

May expand this definition somewhat when incorporating unstructured content to mean more than just key data elements.

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