DS11  Manage Data
Control over the IT process of ...
managing data
    with the business goal
    to ensure that data remains complete, accurate and valid during its input, update and storage
     
      is enabled by
      • an effective combination of application and general controls over the IT operations

        and takes consideration

        • Critical Success Factors that leverage
        • specific IT Resources and is measured by
        • Key Performance Indicators


         


Record of Assessment
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  Control Objective:

Managing data. 

CRITICAL SUCCESS FACTORS
Selected
Status
Description
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Data entry requirements are clearly stated, enforced and supported by automated techniques at all levels, including database and file interfaces
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The responsibilities for data ownership and integrity requirements are clearly stated and accepted throughout the organisation
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Data accuracy and standards are clearly communicated and incorporated into the training and personnel development processes
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Data entry standards and correction are enforced at the point of entry
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Data input, processing and output integrity standards are formalised and enforced
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Data is held in suspense until corrected
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Effective detection methods are used to enforce data accuracy and integrity standards
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Effective translation of data across platforms is implemented without loss of integrity or reliability to meet changing business demands
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There is a decreased reliance on manual data input and re-keying processes
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Efficient and flexible solutions promote effective use of data
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Data is archived and protected and is readily available when needed for recovery
KEY GOAL INDICATORS
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A measured reduction in the data preparation process and tasks
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A measured improvement in the quality, timeline and availability of data
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A measured increase in customer satisfaction and reliance upon the data
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A measured decrease in corrective activities and exposure to data corruption
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Reduced number of data defects, such as redundancy, duplication and inconsistency
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No legal or regulatory data compliance conflicts
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KEY PERFORMANCE INDICATORS
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Percent of data input errors
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Percent of updates reprocessed
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Percent of automated data integrity checks incorporated into the applications
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Percent of errors prevented at the point of entry
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Number of automated data integrity checks run independently of the applications
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Time interval between error occurrence, detection and correction
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Reduced data output problems
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Reduced time for recovery of archived data
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Conclusions:
* Non-existent 

Data is not recognised as a corporate resource and asset. There is no assigned data ownership or individual accountability for data integrity and reliability. Data quality and security is poor or non-existent.
* Optimised 
Data management is a mature, integrated and cross-functional process that has a clearly defined and well-understood goal of delivering quality information to the user, with clearly defined integrity, availability and reliability criteria. The organisation actively manages data, information and knowledge as corporate resources and assets, with the objective of maximising business value. The corporate culture stresses the importance of high quality data that needs to be protected and treated as a key component of intellectual capital. The ownership of data is a strategic responsibility with all requirements, rules, regulations and considerations clearly documented, maintained and communicated.
* Managed and Measurable 
Data is defined as a corporate resource and asset, as management demands more decision support and profitability reporting. The responsibility for data quality is clearly defined, assigned and communicated within the organisation. Standardised methods are documented, maintained and used to control data quality, rules are enforced and data is consistent across platforms and business units. Data quality is measured and customer satisfaction with information is monitored. Management reporting takes on a strategic value in assessing customers, trends and product evaluations. Integrity of data becomes a significant factor, with data security recognised as a control requirement. A formal, organisation-wide data administration function has been established, with the resources and authority to enforce data standardisation.
* Defined Process 
The need for data integrity within and across the organisation is understood and accepted. Data input, processing and output standards have been formalised and are enforced. The process of error identification and correction is automated. Data ownership is assigned, and integrity and security are controlled by the responsible party. Automated techniques are utilised to prevent and detect errors and inconsistencies. Data definitions, rules and requirements are clearly documented and maintained by a database administration function. Data becomes consistent across platforms and throughout the organisation. The information services function takes on a custodian role, while data integrity control shifts to the data owner. Management relies on reports and analyses for decisions and future planning.
* Repeatable but Intuitive 
The awareness of the need for data accuracy and maintaining integrity is prevalent throughout the organisation. Data ownership begins to occur, but at a department or group level. The rules and requirements are documented by key individuals and are not consistent across the organisation and platforms. Data is in the custody of the information services function and the rules and definitions are driven by the IT requirements. Data security and integrity are primarily the information services function's responsibilities, with minor departmental involvement. 
* Initial / Adhoc 
The organisation recognises a need for accurate data. Some methods are developed at the individual level to prevent and detect data input, processing and output errors. The process of error identification and correction is dependent upon manual activities of individuals, and rules and requirements are not passed on as staff movement and turnover occur. Management assumes that data is accurate because a computer is involved in the process. Data integrity and security are not management requirements and, if security exists, it is administered by the information services function.
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