Browse > Article
http://dx.doi.org/10.7232/IEIF.2011.24.2.128

A Resource Allocation Model for Data QC Activities Using Cost of Quality  

Lee, Sang-Cheol (Korea Institute for Defense Analyses)
Shin, Wan-Seon (Systems Management Engineering, Sungkyunkwan University)
Publication Information
IE interfaces / v.24, no.2, 2011 , pp. 128-138 More about this Journal
Abstract
This research proposes a resource allocation model of Data QC (Quality Control) activities using COQ (Cost of Quality). The model has been developed based on a series of research efforts such as COQ classifications, weight determination of Data QC activities, and an aggregation approach between COQ and Data QC activities. In the first stage of this research, COQ was divided into the four typical classifications (prevention costs, appraisal costs, internal failure costs and external failure costs) through the opinions from five professionals in Data QC. In the second stage, the weights of Data QC activities were elicited from the field professionals. An aggregation model between COQ and Data QC activities has been then proposed to help the practitioners make a resource allocation strategy. DEA (Data Envelopment Analysis) was utilized for locating efficient decision points. The proposed resource allocation model has been validated using the case of Korea national defense information system. This research is unique in that it applies the concept of COQ to the data management for the first time and that it demonstrates a possible contribution to a real world case for budget allocation of national defense information.
Keywords
resource allocation; data quality control; cost of quality;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Larry, P. English (1999), Improving Data Warehouse and Business Information Quality : Methods for reducing costs and increasing profits, Wiley computer publishing.
2 Lee, K-J. (2002), A Case Study on Q-Cost System Utilization Method, Management Study 11.
3 Oppermann, M., Sauer W., and Wohlrabe, H. (2003), Optimization of quality costs, Robotics and Computer-Integrated Manufacturing, 19(1-2), 135-140.   DOI   ScienceOn
4 Park, D-H., Ryu H-Y., and Kim, J-S. (2007), Test Process Improvement by Using Cost of Quality in National Defense Software Development, Korea Computer Congress.
5 Park, J-S. and Kim, C-S. (2003), Data Quality Management Maturity Model, Database Grand Conference.
6 Park, M-H. (2002), A Decision Support System for Stepwise Improvement of Quality Competitiveness, SungKyunKwan University.
7 Park, M-H. (2008), Analysis of Efficiency and Productivity, Korea Studies Information co.
8 Crawsey, R. A. (1976), A Business Performance Measure of Quality Management, Annual Quality Congress Transactions, American Society for Quality Control.
9 Harrington, H. J. (1987), Poor Quality Costs, American Society For Quality Control, 5.
10 Herb Krasner (1998), Using the Cost of Quality Approach for Software, Crosstalk (The journal of Defense Software Engineering).
11 Groocock, J. M. (1986), Chain of Quality; Market Dominance Through Product Superiority, John Wiley and Sons.
12 Juran, J. M. and Gryna, F. M. (1993), Quality Planning and Analysis, 3rd ed., New York : McGraw-Hill, 19.
13 Juran, J. M. (1974), Quality Control Handbook, 3rd edition, New York : McGraw- Hill, 7.
14 Jack, E. Olson(2006), Data Quality.
15 Jeong, Y-B., Kim, Y-S., and Kim, J-H. (2004), Development of Web Based Q-Cost System, Journal of Korea Industrial and Systems Engineering.
16 Kang, J-H. (1995), A Study on Classification and Calculation Method of Cost of Quality, Journal of Korea Industrial and Systems Engineering, 18(35), 17-24.
17 Feigenbaum, A. V. (1961), Total Quality Control, 2nd ed., McGraw-Hill, Chapter 5.
18 Korea Database Agency (2006), Data Quality Management Maturity Model (1.0).
19 Korea Database Agency (2006), The Guideline for Data Quality Management (2.1).
20 Schneiderman, A. M. (1986), Optimum Quality Costs and Zero Defects : Are They Contradictory Concepts?, Quality Progress.
21 Alan, F. Karr, Ashish P. Sanil., and David L. Banks (2006), Data Quality : A Statiscal Perspective, Science Direct.
22 Bank, B. (1989), Principles of Quality Control, Singapores, 499.
23 Stephen, T. Knox. (1993), Modeling the Cost of Software Quality, Digital Equipment Corporation.
24 Chang, S-J., Park, Y-H. and Park, E-H. (1996), Quality Costs in Multi-stage Manufacturing Systems, Computers and Industrial Engineering, 31(1-2), 115-118.   DOI   ScienceOn