The Effects of Benchmarking on the Eastern Cape Municipalities’ Performances

Abstract

Local government practices reveal that there is skewed use of human resource measures as mechanisms for evaluating, measuring and improving governmental performances. Yet in a number of instances, organizational diagnosis have revealed that shortfalls in governmental performances are not related to human resource related factors, but the kinds of operational systems, processes and work methods in place. It is against such a backdrop that this paper examines the nexus between benchmarking as a system and process improvement mechanism, and its resulting positive effects on improving performances of the municipalities in the Eastern Cape Province. The target population for the study comprised of all the municipalities in the Eastern Cape Province. It is indicated in the Local Government Human Resource Document (2009:19) that there are approximately 11700 municipal employees in the Eastern Cape Province. In order to determine the appropriate and valid sample for the study, Yamane (1967:886)’s formula was applied, with the result that 100 sample respondents were concluded as the representative and valid sample for the study. The desired 100 respondents were drawn into the study using simple random sampling. The principal primary data collection instrument was a questionnaire designed basing on the Likert Scale Style. The Cronbach and Spearman Brown analysis were performed in order to determine the validity and reliability of the questionnaire. The techniques which were used in determining whether the hypothesized benchmarking theory fits the sample data included; the Goodness of Fitness Index (GFI), Parsimony Normed Fit Index (PNFI), Tucker Lewis Index (TLI), Comparative Fit Index (CFI) and RMSEA (Root Mean Square Error of Approximation). Hu and Bentler’s (1995:22) interpretation was used in determining whether the results of GFI, PNFI, TLI and CFI were within acceptable limits of 0 and 1. On the other hand, Wheaton’s (1987:2) and Carmnines and McLver’s (1981:1) arguments were used in assessing whether RMSEA (Root Mean Square Error of Approximation), fell in the acceptable limit of 0.05 and 0.08. Nonetheless, the results of GFI, PNFI, TLI, CFI and RMSEA confirmed that the hypothesized benchmarking model fits well with the observed sample data.

Keywords; Benchmarking; Performance; Municipalities; Eastern Cape Province