Download Day 2 Parallel Session 2

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.
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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.
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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
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
.28
Acceptable
and 1)
TLI (Tucker Lewis Index, acceptable if it falls
.41
Acceptable
between 0 and 1)
CFI (Comparative Fit Index, acceptable if falls
.67
Acceptable
between 0 and 1)
RMSEA (Root Mean Square Error of Approximation,
.05(Pclose =
Acceptable
acceptable if falls between 0.05 and 0.08)
.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)
NFI (Normed Fit Index, acceptable if falls between 0
and 1)
TLI (Tucker Lewis Index, acceptable if it falls
between 0 and 1)
CFI (Comparative Fit Index, acceptable if falls
between 0 and 1)
RMSEA
(Root
Mean
Square
Error
of
Approximation, acceptable if falls between 0.05 and
0.08)
.89
.30
Acceptable
Acceptable
.34
Acceptable
.15
Acceptable
.07(Pclose =
.149)
Acceptable
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)
Interpretation
Obtained
Value
GFI ( Acceptable if falls between 0 and 1)
.76
Acceptable
NFI (Normed Fit Index, acceptable if falls between 0 and 1)
.12
Acceptable
.1
Acceptable
TLI (Tucker Lewis Index, acceptable if it falls between 0
and 1)
.00
Acceptable
CFI (Comparative Fit Index, acceptable if falls between 0
and 1)
RMSEA (Root Mean Square Error of Approximation, .1(Pclose = Unacceptable
acceptable if falls between 0.05 and 0.08)
.024)
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.