Professor EOC Ijeoma and Antony Matemba Sambumbu Utilization of Community Evaluation for Improving Municipal Performance; Eastern Cape Perspective By Professor EOC Ijeoma and Antony Matemba Sambumbu A Paper Presented at a 4th Biennial SAMEA Conference held at Sandton, Johannesburg, South Africa

Contextualization of the Problem Motivation; Skewed use of human resources’ related measures such as; performance appraisals, performance measurement, management by objectives. Yet, a diagnosis implies that the challenges are related to systems, processes and work methods that are used in the Eastern Cape Local Government. On that basis, this paper examines the nexus between the use of benchmarking as a performance improvement mechanism and the resulting effects on the performances of the municipalities in the Eastern Cape Province. 2 2

Previous Studies; Fact-Findings Despite Six-Sigma and Process Re-engineering, benchmarking is one of the process control and improvement measures. Benchmarking refers to the process of measuring and comparing the performance of an organization against the best performing organization in order to identify areas of strengths and weaknesses, and subsequently the best practice that must be adopted for improving the general organizational performance. Depending on the challenges, benchmarking can be done internally or externally, and can centre on either a single or multiple functional areas. 3 3

In the Context of Bourne’s (2005:101) postulation, the successful application of benchmarking is significantly influenced by the strict adherence to the six steps that encompass; Step 1; Understand and Measure Critical Success Factors Step 2; Select an Area of Performance for Benchmarking Step 3; Select a Benchmark Partner Step 4; Collect Data in Partner Organization Step 5; Compare Data Step 6; Mark Strength to be Built

In conjunction with the application of measures such as; Top management support Constant review and evaluation Change management strategies Allocation of sufficient resources, a consensus exists among management theorists that benchmarking can significantly contribute to improvement in; Costs’ reductions Efficiency and Effectiveness Ability to ever changing diverse public needs Achievement of the desired level of superior performance

Hypotheses Formulation On the basis of the above identified problem and theoretical foundation, it is hypothesized in this paper that; The use of a combination of different types of benchmarking can significantly influence the improvement in the performance of the municipalities in the Eastern Cape Province The application of the Bourne’s (2005:101) Six Main Steps in the Benchmarking can influence the improvement in the performance of the Municipalities in the Eastern Cape Province The use of certain accompanying measures would significantly influence The benchmarking process and subsequently the improvement in the performance of the municipalities in the Eastern Cape Province

Methodology (Confirmatory Factor Analysis) In order to test the above indicated three hypotheses, this study uses the confirmatory factor analysis technique which was accomplished according the four main steps that include; Step 1; Model Specification and Hypotheses’ Formulations Step2; Target Population and Sample Size Determination (100 sample respondents were used) Step3; Data Collection (Using a Five Point Likert Questionnaire- Designed basing on the above stated three hypotheses) Step4; Data Analysis and Interpretation of Indices (In order to determine model Fitness)

Findings and Discussions Data Analysis was accomplished using the AMOS Programme of the SPSS The following indices were used in the interpretation of the Findings and determining model fitness; (1) Chi-Square Value (with df, P-Value, and CMIN/df) (2) Root Mean Residual (RMR) (3) Comparative Fit Index (CFI) (4) Tucker Lewis Index (TLI) (5) Normed Fit Index (NFI) (6) Root Mean Square Error of Approximation (RMSEA) (7) Standardized Regression Weights (8) Square Multiple Correlation Coefficient The findings were as interpreted and discussed according to the above indicated three hypotheses

Hypothesis 1; The use of a combination of different types of benchmarking can significantly influence the improvement in the performance of the municipalities in the Eastern Cape Province; Standardized Regression Weights and Squared Multiple Correlation Coefficient

Types and Effects on the Performance of the Eastern Cape Table 1.1; The Use of a Combination of Benchmarking Types and Effects on the Performance of the Eastern Cape Municipalities; Chi-Square and Modification Indices Chi-Square= 25; Degree of Freedom (DF) =20; Probability (P)=.215; CMIN/DF= 1.23 Modification Indices (Alternative Fit Statistics) Obtained Value Interpretation GFI ( Acceptable if falls between 0 and 1) .71 Acceptable NFI (Normed Fit Index, acceptable if falls between 0 and 1) .28 TLI (Tucker Lewis Index, acceptable if it falls between 0 and 1) .41 CFI (Comparative Fit Index, acceptable if falls between 0 and 1) .67 RMSEA (Root Mean Square Error of Approximation, acceptable if falls between 0.05 and 0.08) .05(Pclose = .467)

Hypothesis 2; The application of the Bourne’s (2005:101) Six Main Steps in the Benchmarking can influence the improvement in the performance of the Municipalities in the Eastern Cape Province; Standardized Regression Weights and Squared Multiple Correlation Coefficient

Table 1.2; The application of the Bourne’s (2005:101) Six Main Steps in the Benchmarking can influence the improvement in the performance of the Municipalities in the Eastern Cape Province; Chi-Square and Modification Indices Chi-Square= 54; Degree of Freedom (DF) =35; Probability (P)=.021; CMIN/DF= 1.5 Modification Indices (Alternative Fit Statistics) Obtained Value Interpretation GFI ( Acceptable if falls between 0 and 1) .89 Acceptable NFI (Normed Fit Index, acceptable if falls between 0 and 1) .30 TLI (Tucker Lewis Index, acceptable if it falls between 0 and 1) .34 CFI (Comparative Fit Index, acceptable if falls between 0 and 1) .15 RMSEA (Root Mean Square Error of Approximation, acceptable if falls between 0.05 and 0.08) .07(Pclose = .149)

Hypothesis 3; The use of certain accompanying measures would significantly influence the benchmarking process and subsequently the improvement in the performance of the municipalities in the Eastern Cape Province; Standardized Regression Weights and Squared Multiple Correlation Coefficient

Table 1.3; The use of certain accompanying measures would significantly influence the benchmarking process and subsequently the improvement in the performance of the municipalities in the Eastern; Chi-Square and Modification Indices Chi-Square= 53; Degree of Freedom (DF) =27; Probability (P)=.002; CMIN/DF= 1.9 Modification Indices (Alternative Fit Statistics) Obtained Value Interpretation GFI ( Acceptable if falls between 0 and 1) .76 Acceptable NFI (Normed Fit Index, acceptable if falls between 0 and 1) .12 TLI (Tucker Lewis Index, acceptable if it falls between 0 and 1) .1 CFI (Comparative Fit Index, acceptable if falls between 0 and 1) .00 RMSEA (Root Mean Square Error of Approximation, acceptable if falls between 0.05 and 0.08) .1(Pclose = .024) Unacceptable

CONCLUSIONS AND RECOMMENDATIONS In line with the above discussed results of confirmatory factor analysis, it is recommended that the Eastern Cape Local Government must adopt benchmarking as a Performance improvement measure.