Article Abstract

	Title:	Performance measurement system simplicity
	Author:	Eric O. Olsen, Peter T. Ward
	Address:	Orfalea College of Business – Industrial Technology, California Polytechnic State University, San Luis Obispo, CA 93407, USA. ' Fisher College of Business – Management Science, The Ohio State University, Columbus, OH 43210, USA
	Journal:	International Journal of Manufacturing Technology and Management 2006 - Vol. 8, No.4  pp. 330 - 354
	Abstract:	Leading researchers, consultants and practitioners advocate that internal operations performance measurement (PM) systems need to be 'simple' in order to be most effective. The notion of PM system simplicity has often been expressed as the characteristic of having few versus many measures. This paper proposes a new simplicity scale based on the importance rankings of performance measures found in a large-scale survey of manufacturing firms. The PM system simplicity scale is developed and applied in the context of traditional manufacturing strategy constructs such as cost, quality, delivery and flexibility and with respect to environmental dynamism. Analysis of empirical data on 100 manufacturing firms shows that superior market performance is associated with firms that have both complex and simple PM systems, but that moderately simple systems perform less well.
	Keywords:	complexity; manufacturing management; performance measurement systems; simplicity; manufacturing performance; importance rankings; manufacturing strategy; environmental dynamism; business performance.
	DOI:	10.1504/IJMTM.2006.009243
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Article's references with DOI links:

• Calinescu, The Journal of the Operational Research Society. 1998 - Vol. 49, No. 7 p. 723
  
• Coskun, Information and Software Technology. 2001 - Vol. 43, No. 9 p. 527
  
• Dess, Administrative Science Quarterly. 1984 - Vol. 29, No. 1 p. 52
  
• Flynn, Journal of Operations Management. 1990 - Vol. 9, No. 2 p. 250
  
• Frizelle, International Journal of Operations & Production Management. 1995 - Vol. 15, No. 5 p. 26
  
• Keats, The Academy of Management Journal. 1988 - Vol. 31, No. 3 p. 570
  
• Keuzenkamp, The Economic Journal. 1995 - Vol. 105, No. 428 p. 1
  
• Leong, Omega. 1990 - Vol. 18, No. 2 p. 109
  
• Miller, The Academy of Management Review. 1993 - Vol. 18, No. 1 p. 116
  
• Miller, Strategic Management Journal. 1983 - Vol. 4, No. 3 p. 221
  
• Moores, Journal of Systems and Software. 1998 - Vol. 44, No. 1 p. 45
  
• Van Dierdonck, Journal of Operations Management. 1980 - Vol. 1, No. 1 p. 37
  
• Vickery, Decision Sciences. 1993 - Vol. 24, No. 2 p. 435
  
• Ward, Journal of Operations Management. 2000 - Vol. 18, No. 2 p. 123
  
• Wheel Wright, Strategic Management Journal. 1984 - Vol. 5, No. 1 p. 77
  
• Youndt, The Academy of Management Journal. 1996 - Vol. 39, No. 4 p. 836