The analysis of service levels begins by presenting an overview of the composite service level indicator for both programme and control villages across the entire sample. Although the data distribution shares a similar U-shape, as shown in Figures 6-1 and 6-2, there is a clear difference in the skewness of the data, with proportionally over twice as many households in the programme villages receiving high service levels as compared to the control villages. Based on the research methodology’s definition of success, as measured by the composite service level indicator, and the use of median as the appropriate central tendency measure for ordinal data, this difference in skewness is reflected in the median service level in programme villages being ‘improved’ (4) compared to ‘sub-standard’ (2) in the control villages. The Mann Whitney Test confirms the difference in medians as statistically significant at the 0.00 level, as shown in Table 6-2. This verifies that at the whole sample level the study compared more successful service delivery in the programme villages than in the control villages.
Table 6-2 - Descriptive statistics for composite service level (programme v control;
whole sample)
Village type Median Mean N Std.
Deviation
Kurtosis Skewness Mann Whitney U-Test Comparing Medians
However, even for programme villages, over 40% of the sample report having water services that score ‘sub-standard’ or ‘no service’ with regards to the composite indicator. This indicates that within these purposively selected high performance programmes there are still a significant minority of the population receiving inadequate services. In the WASHCost research it was reported that the ‘majority’ of
12 (1 = no service, 2 = sub-standard, 3 = basic, 4 = improved and 5 = high)
people with improved-water sources do not receive a ‘basic’ service level (Burr and Fonseca, 2013). Here, the results are at least reversed in that the majority of households (54%) in programme villages do achieve ‘basic’ or above service levels.
However, the research can be considered to confirm a pattern of results found in other studies – that the improved-water source access figures can mask variable service levels in rural water service programmes (Clasen, 2012; Godfrey et al., 2011).
Figure 6-1 - Consolidated Service Level Indicator (programme villages)
No Service Sub-Standard Basic Improved High
147 Figure 6-2 - Consolidated Service Level Indicator (Control villages)
Moving onto an analysis of the disaggregate service level it is helpful to understand which of the service level parameters are having the most influence on the composite indicator. In total, across the whole sample 1,019 (31%) respondents failed on at least one parameter meaning that due to the nominal logic of the composite indicator they were labelled as sub-standard or no service. Of those failures, 573 failed on just one indicator, 319 failed on two indicators whilst the rest failed on three or more indicators. Table 6-3 illustrates there is greatest variability in the parameter for quantity, compared to accessibility, perceived quality, reliability and continuity. The distribution of the data is split for quantity with a median measure of ‘high’ (5) across the sample but the highest standard deviation of any measure.
This is reflected in the number of households failing on that measure with this coming out at 676 (30% of the sample). Accessibility is the next measure that is most likely to be reported as failing to meet the service level (16%) followed by reliability
No Service Sub-Standard Basic Improved High
and continuity at 11%. Only 3% of respondents reported unacceptable quality but as explained in the methods this is only a measure of perceived quality so has to be treated with caution. The disaggregated service level data therefore shows that a focus on increasing the quantity of water supplied will have the biggest impact in terms of moving populations up the service level ladder from ‘no service’ or ‘sub-standard’ to ‘basic’ or above. Evidence indicates that having a water-source in or close to the home increases the quantity of water people consume (Howard and Bartram, 2013) and so, in this sense, the Government of India drive for household connections is well focused in terms of improving service level outcomes (Government of India, 2013a).
Table 6-3- Descriptive statistics on the disaggregated service level indicators
Quantity Accessibility Quality Reliability Continuity (piped only)
N Valid 2244 2207 2286 2167 1809
Missing 74 111 32 151 509
Mean 3.61 4.27 4.68 4.49 3.70
Median 5.00 5.00 5.00 5.00 3.00
Std. Deviation 1.607 1.380 .792 1.101 1.102
Skewness -.575 -1.541 -2.218 -2.203 .130
Kurtosis -1.334 .676 3.356 3.543 -1.542
Number of household failing on this parameter
676 355 69 239 195
Percentage of households failing on this parameter
30% 16% 3% 11% 11%
Shifting the focus to the case-by-case service level data, the analysis shows that 13 of the cases studies have a median measure of ‘basic’, ‘improved’ or ‘high’ on the composite indicator in programme villages. The services delivered in these cases therefore, on average, meet or exceed the standards for all the individual service level parameters. From these, there are six case studies that have a median service level of ‘high’, giving a sub-group of what can be considered very successful service level outcomes. In the middle there are seven that achieve the ‘basic’ or ‘improved’
level, whilst seven of the case studies have medians that come at either ‘sub-standard’ or ‘no service’.
Based on the research methodology, those latter seven case studies cannot be considered ‘successful’ rural water services as per government norms. For this
149 research the three groups, as shown in Table 6-4, can be labelled as the ‘high service level group’, ‘basic or improved service level group’ and ‘sub-standard or no service level group’. This finding can be interpreted in different ways. It shows that community management can play a role in delivering service levels at various ranks of success suggesting it has a role to play in countries progressing from a focus on basic access to increasing service levels. However, it also shows that a third of
‘reportedly successful’ community management programmes fail to deliver even basic service levels calling into question the overall approach the sector takes to delivering such services.
Table 6-4 - Descriptive statistics on service level composite indicator (all cases, programme villages only)
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