Integrating a data quality perspective into business process management

  title={Integrating a data quality perspective into business process management},
  author={Martin Ofner and Boris Otto and Hubert {\"O}sterle},
  journal={Business Proc. Manag. Journal},
Purpose – The purpose of this paper is to conceptualize data quality (DQ) in the context of business process management and to propose a DQ oriented approach for business process modeling. The approach is based on key concepts and metrics from the data quality management domain and supports decision-making in process re-design projects on the basis of process models. Design/methodology/approach – The paper applies a design oriented research approach, in the course of which a modeling method is… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 84 references

Business process management (BPM) standards: a survey

Business Proc. Manag. Journal • 2009
View 4 Excerpts
Highly Influenced

Modeling information manufacturing systems to determine information product quality

D. P. Ballou, R. Y. Wang, H. L. Pazer, G. Kumar-Tayi
Management Science, • 1998
View 4 Excerpts
Highly Influenced

Multiple Criteria Decision Making: From Early History to the 21st Century, World Scientific, Singapore

M. Köksalan, J. Wallenius, S. Zionts
View 4 Excerpts
Highly Influenced

Invisible data quality issues in a CRM implementation

A. Reid, M. Catterall
Journal of Database Marketing & Customer Strategy Management, • 2005
View 4 Excerpts
Highly Influenced

Barriers to successful data quality management

T. C. Redman
Studies in Communication Sciences, • 2004
View 2 Excerpts
Highly Influenced