Data punctuality

Characteristic Name:	Data punctuality
Dimension:	Availability and Accessability
Description:	Data should be available at the time of its intended use
Granularity:	Information object
Implementation Type:	Process-based approach
Characteristic Type:	Usage

Verification Metric:

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

The number of complaints received due to lack of data punctuality

GuidelinesExamplesDefinitons

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

Guidelines:	Scenario:
Standardise the timelines for the availability of information for a particular task	(1) Investment product pricing data is often provided by third-party vendors. As the success of the business depends on accessibility to that pricing data, service levels specifying how quickly the data must be provided are defined and compliance with those timeliness constraints.
Create efficient processes for information delivery by removing the bottlenecks in information flow	(1) Billing details of a patient is gathered two hours before discharging the patient

Validation Metric:

How mature is the process of ensuring data punctuality

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

Example:	Source:
1) For example, the best and easiest method to obtain demographic information may be to obtain it from an existing system. Another method may be to assign data collection by the expertise of each team member. For example, the admission staff collects demographic data, the nursing staff collects symptoms, and the HIM staff assigns codes. Team members should be assigned accordingly. 2) For example, patient census is needed daily to provide sufficient day-to-day operations staffing, such as nursing and food service. How- ever, annual or monthly patient census data are needed for the facilityís strategic planning.	B. Cassidy, et al., “Practice Brief: Data Quality Management Model” in Journal of AHIMA, 1998, 69(6).

Example:

Source:

1) For example, the best and easiest method to obtain demographic information may be to obtain it from an existing system. Another method may be to assign data collection by the expertise of each team member. For example, the admission staff collects demographic data, the nursing staff collects symptoms, and the HIM staff assigns codes. Team members should be assigned accordingly.

2) For example, patient census is needed daily to provide sufficient day-to-day operations staffing, such as nursing and food service. How- ever, annual or monthly patient census data are needed for the facilityís strategic planning.

B. Cassidy, et al., “Practice Brief: Data Quality Management Model” in Journal of AHIMA, 1998, 69(6).

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

Definition:	Source:
1) The characteristic of getting or having the Information when needed by a process or Knowledge Worker. 2) The Characteristic of the Information being accessible when it is needed.	ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing.
Is the information processed and delivered rapidly without delays?	EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer.
Timeliness refers to the time expectation for accessibility and availability of information. Timeliness can be measured as the time between when information is expected and when it is readily available for use. For example, in the financial industry, investment product pricing data is often provided by third-party vendors. As the success of the business depends on accessibility to that pricing data, service levels specifying how quickly the data must be provided can be defined and compliance with those timeliness constraints can be measured.	LOSHIN, D. 2006. Monitoring Data quality Performance using Data Quality Metrics. Informatica Corporation.
Timeliness reflects the length of time between availability and the event or phenomenon described. Punctuality refers to the time lag between the release date of data and the target date when it should have been delivered.	LYON, M. 2008. Assessing Data Quality , Monetary and Financial Statistics. Bank of England. http://www.bankofengland.co.uk/ statistics/Documents/ms/articles/art1mar08.pdf.

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.