A Framework for Information Quality Assessment Using Six Sigma Approach

Impacts of poor quality of information are felt at every level in an organisation. To mitigate these impacts, information quality must be assessed and managed. However, obtaining accurate measurements and cost-effective assessments of information quality have proven to be an extremely difficult task due to the complexities of information systems and the various information quality dimensions depending upon the business properties. Most of the available information quality assessment frameworks are based on measuring customer data only and thus, they do not provide comprehensive and systematic assessment of information quality. However, not only that these approaches are unable to provide a complete measurement of all the information quality dimensions, but are also unable to highlight the dirtiness of data due to the correlation of various information quality dimensions. This paper introduces a new approach to information quality measurement and employs Six Sigma approach to information quality assessment. This approach focuses on continuous improvement of information quality by a systematic assessment of multiple information quality dimensions. It specifically tackles the correlation and the relative importance of information quality dimensions and proposes precise and systematic information quality assessment criteria.

[1]  InduShobha N. Chengalur-Smith,et al.  The Impact of Data Quality Information on Decision Making: An Exploratory Analysis , 1999, IEEE Trans. Knowl. Data Eng..

[2]  Navin Shamji Dedhia,et al.  Six sigma basics , 2005 .

[3]  Thomas Redman,et al.  Data quality for the information age , 1996 .

[4]  Max Moullin,et al.  Performance measurement definitions: linking performance measurement and organisational excellence. , 2007, International journal of health care quality assurance.

[5]  Richard Y. Wang,et al.  Journey to Data Quality , 2006 .

[6]  Richard Y. Wang,et al.  A product perspective on total data quality management , 1998, CACM.

[7]  Martin J. Eppler Managing Information Quality , 2003 .

[8]  Mouzhi Ge,et al.  Data and Information Quality Assessment in Information Manufacturing Systems , 2008, BIS.

[9]  Stuart E. Madnick,et al.  Overview and Framework for Data and Information Quality Research , 2009, JDIQ.

[10]  Ephraim R. McLean,et al.  Measuring information systems success: models, dimensions, measures, and interrelationships , 2008, Eur. J. Inf. Syst..

[11]  Giri Kumar Tayi,et al.  Enhancing data quality in data warehouse environments , 1999, CACM.

[12]  Richard Y. Wang,et al.  Quality information and knowledge , 1998 .

[13]  Les Gasser,et al.  A framework for information quality assessment , 2007, J. Assoc. Inf. Sci. Technol..

[14]  Heng Li,et al.  Analytic hierarchy process , 2001 .

[15]  Felix Naumann,et al.  Assessment Methods for Information Quality Criteria , 2000, IQ.

[16]  Michael Gertz,et al.  Report on the Dagstuhl Seminar , 2004, SGMD.

[17]  Diane M. Strong,et al.  Product and Service Performance Model for Information Quality: An Update , 1998, IQ.

[18]  Mouzhi Ge,et al.  Information Quality Assessment and Effects on Inventory Decision-Making , 2009 .

[19]  Carlo Batini,et al.  Methodologies for data quality assessment and improvement , 2009, CSUR.

[20]  Binshan Lin,et al.  Information Technology and Six Sigma Implementation , 2007, J. Comput. Inf. Syst..

[21]  Richard Y. Wang,et al.  Anchoring data quality dimensions in ontological foundations , 1996, CACM.

[22]  Giri Kumar Tayi,et al.  Examining data quality , 1998, CACM.

[23]  Diane M. Strong,et al.  Beyond Accuracy: What Data Quality Means to Data Consumers , 1996, J. Manag. Inf. Syst..

[24]  Markus Helfert,et al.  Information Quality Management: Review of an Evolving Research Area , 2007 .

[25]  Larry P. English Improving Data Warehouse and Business Information Quality: Methods for Reducing Costs and Increasing Profits , 1999 .