Data maintenance

Characteristic Name:	Data maintenance
Dimension:	Availability and Accessability
Description:	Data should be accessible to perform necessary updates and maintenance operations in it’s entirely
Granularity:	Record
Implementation Type:	Process-based approach
Characteristic Type:	Usage

Verification Metric:

The number of tasks failed or under performed due to lack of data maintenance

The number of complaints received due to lack of continuity in data access

GuidelinesExamplesDefinitons

The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation

Guidelines:	Scenario:
Technological changes in the infrastructure/system should be handled in such a way that they should not make data inaccessible	(1) Sales order is created once a customer signs a contract. Then it is updated in three instances 1)Delivery date and shipment date is updated once the production plan is created. 2) Actual quantity is updated once the manufacturing is complete 3) Total cost is updated once the freight changes are incurred. A sales order is achieved after one years from delivery.
A maintenance policy for mission critical data should be developed and implemented to handle on going systematic updates (Create, read, update, delete, archive and cleanse)	(1) Customer data : Created when a customer enters into a contract, updated once the customer details change or contact change, archived once the contact end
When multiple versions of the same data is available through different datasets\databases create a master record and make it available across the systems	(1) Master data management
Leverage application and storage technology in such a way that the maintenance policies can be applied on data	(1)Addresses which were not updated during the last 24 months are prompted for validations
Create a responsibility structure/Authorisation structure and a communication structure to manage the process of information generation maintenance and utilisation	(1) It is the responsibility of the work study team to provide SMV (standard minute values) for a garment. (2) Approved SMVs should be sent to the planning department for planning purposes.

Validation Metric:

How mature is the data maintenance process

These are examples of how the characteristic might occur in a database.

Example:	Source:
minutes of a meeting will be produced in draft form and reviewed by the members of the committee before being approved. Once this process of creation is ﬁnished the record must be ﬁxed and must not be susceptible to change. If a record is changed or manipulated in some way, it no longer provides evidence of the transaction it originally documented. For example, if someone alters the minutes of a meeting after they have been approved, the minutes can no longer be considered an accurate record of the meeting. This is another issue that becomes more important in an electronic context.	K. Smith, “Public Sector Records Management: A Practical Guide”, Ashgate, 2007.

Example:

Source:

minutes of a meeting will be produced in draft form and reviewed by the members of the committee before being approved. Once this process of creation is ﬁnished the record must be ﬁxed and must not be susceptible to change. If a record is changed or manipulated in some way, it no longer provides evidence of the transaction it originally documented. For example, if someone alters the minutes of a meeting after they have been approved, the minutes can no longer be considered an accurate record of the meeting. This is another issue that becomes more important in an electronic context.

K. Smith, “Public Sector Records Management: A Practical Guide”, Ashgate, 2007.

The Definitions are examples of the characteristic that appear in the sources provided.

Definition:	Source:
A measure of the degree to which data can be accessed and used and the degree to which data can be updated, maintained, and managed.	D. McGilvray, “Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information”, Morgan Kaufmann Publishers, 2008.
Can all of the information be organized and updated on an on-going basis?	EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer.

Usefulness and relevance

Characteristic Name:	Usefulness and relevance
Dimension:	Usability and Interpretability
Description:	The data is useful and relevant for the task at hand
Granularity:	Information object
Implementation Type:	Process-based approach
Characteristic Type:	Usage

Verification Metric:

The number of tasks failed or under performed due to the lack of usefulness and relevance of data

The number of complaints received due to the lack of usefulness and relevance of data

GuidelinesExamplesDefinitons

The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation

Guidelines:	Scenario:
Define the content of the information object based on the user requirements (as required by the task at hand) and also considering all other compliance requirements so that the information is relevant and legitimate	(1) Customer invoice should contain information for the customer to understand his liability and for the delivery person to understand the point of delivery and the tax department to verify the applicable tax amount.
Regularly monitor the changes to the internal operational environment ( business process changes etc) and find out what are the new information requirements emerge due to the changes, and provide for them by amending the information structures	(1) Time stamp became an important attribute for GRNs (goods receipts notes) when Lean manufacturing started as all raw materials are expected to receive by six hours before production (GRN-record, and the time stamp -attribute)
Regularly monitor the changes in the external environment find out the new information requirements emerge due to such changes and provide for such data needs	(1) Competitors' rates have become important to price the existing products during the recession period since the traditional costing method does not give a competitive price.
Regularly check with knowledge workers to find out how their operations/decisions can be performed better with new data available to them and provide for such data in the information system	(1) An hourly working progress report is useful in identifying the bottlenecks in production lines and balance the lines
Monitor and measure the user satisfaction about the information provided	(1) User satisfaction survey

Validation Metric:

How mature is the process to maintain usefulness and relevance of data

These are examples of how the characteristic might occur in a database.

The Definitions are examples of the characteristic that appear in the sources provided.

Definition:	Source:
1) The Characteristic in which the Information is the right kind of Information that adds value to the task at hand, such as to perform a process or make a decision. 2) Knowledge Workers have all the Facts they need to perform their processes or make their decisions.	ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing.
1) Can the information process be adapted by the information consumer? 2)Can the information be directly applied? Is it useful? 3) Does the information provision correspond to the user’s needs and habits?	EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer.
Relevance of data refers to the extent to which the data meets the needs of users. Information needs may change and is important that reviews take place to ensure data collected is still relevant for decision makers.	HIQA 2011. International Review of Data Quality Health Information and Quality Authority (HIQA), Ireland. http://www.hiqa.ie/press-release/2011-04-28-international-review-data-quality.
Relevance is the degree to which statistics meet current and potential users’ needs. It refers to whether all statistics that are needed are produced and the extent to which concepts used (definitions, classifications etc.)	LYON, M. 2008. Assessing Data Quality , Monetary and Financial Statistics. Bank of England. http://www.bankofengland.co.uk/ statistics/Documents/ms/articles/art1mar08.pdf.
The data includes all of the types of information important for its use.	PRICE, R. J. & SHANKS, G. Empirical refinement of a semiotic information quality framework. System Sciences, 2005. HICSS'05. Proceedings of the 38th Annual Hawaii International Conference on, 2005. IEEE, 216a-216a.
1) Intrinsic: The extent to which the information is new or informative in the context of a particular activity or community. 2) Relational Contextual:The amount of information contained in an information object. At the content level, it is measured as a ratio of the size of the informative content (measured in word terms that are stemmed and stopped) to the overall size of an information object. At the schema number of elements in the object level it is measured as a ratio of the number of unique elements over the total. 3) The extent to which information is applicable in a given activity. 4) The extent to which the model or schema and content of an information object are expressed by conventional, typified terms and forms according to some general-purpose reference source.	STVILIA, B., GASSER, L., TWIDALE, M. B. & SMITH, L. C. 2007. A framework for information quality assessment. Journal of the American Society for Information Science and Technology, 58, 1720-1733.
1) Data are applicable and useful for the task at hand. 2) The quantity or volume of available data is appropriate. 3) Data are of sufficient depth, breath and scope for the task at hand.	WANG, R. Y. & STRONG, D. M. 1996. Beyond accuracy: What data quality means to data consumers. Journal of management information systems, 5-33.