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A Method For Designing Improvements in Organizations, Products, and Services. Dragan Tevdovski Mathematics, Statistics and Informatics University Sts. Cyril and Methodius Skopje, Macedonia E-mail: dragan@eccf.ukim.edu.mk. Stuart Umpleby Research Program in Social and Organizational Learning
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A Method For Designing Improvements in Organizations, Products, and Services Dragan Tevdovski Mathematics, Statistics and Informatics University Sts. Cyril and Methodius Skopje, Macedonia E-mail: dragan@eccf.ukim.edu.mk Stuart Umpleby Research Program in Social and Organizational Learning The George Washington University Washington, DC USA E-mail: umpleby@gwu.edu Second Conference of the Washington Academy of Sciences Washington DC, March 2006
Introduction • A method for determining priorities for improvement in an organization • Priority means high importance and low performance • Quality Improvement Priority Matrix
The approach to design • This approach to design is “piecemeal” rather than “utopian” • It is “bottom up” rather than “top down” • It uses the judgments of employees or customers • Features to improve are ranked by urgency • Several projects can be worked on simultaneously
References • The method was first described by the specialists from GTE Directories Corporation in 1995 • Armstrong Building Products Operation used the method in1996 • Naoumova and Umpleby (2002) - evaluation of visiting scholar programs
Melnychenko and Umpleby (2001) and Karapetyan and Umpleby (2002) used QIPM in a university department • Prytula (2004) introduced the importance / performance ratio • Dubina (2005) used cluster analysis and proposed standard deviation as a measure of agreement or disagreement
Goals of the Paper • Understand more fully the priorities of the Department of Management Science at The George Washington University (GWU), USA, and the Department of Management at Kazan State University (KSU), Kazan, Russia • Use and develop new methods to compare QIPMs for two organizations
The Data • A questionnaire was given to management faculty members at both GWU and KSU in 2002 • The questionnaire contained 51 features of their departments • Importance and performance scales, each ranging from 0 to 10
Standardization of the importance and the performance scores
Ranking the Priorities • Standardized importance-performance ratio (SIP)
Clustering the Priorities GWU Clusters Centers
Clustering the Priorities GWU Clusters Centers
Review of what we did (1) • We used 2002 data from GWU and KSU • We divided importance and performance means by st. dev. in order to achieve a common level of agreement among GWU and KSU faculty members • Combining GWU and KSU data, we calculated the nearest whole integer mean for importance and performance
Review of what we did (2) • These means were used to create a common QIPM coordinate system • For each department the features in the SE quadrant were clustered by proximity • The clusters were ordered by average SIP, a measure of urgency
Conclusions (1) • Standardizing importance and performance scores to achieve a common level of agreement magnifies the differences between the two departments • At KSU the average importance of the features is lower than at GWU. This may mean that KSU is still struggling with basics such as salaries and office space. GWU has the luxury of concern with travel and research funds and the library collection
Conclusions (2) • Faculty members at KSU evaluate the performance of their department lower than do GWU faculty members • At KSU high priority features are mostly personal concerns such as salaries • At GWU high priority features are organizational issues such as planning