Sustainability Planning and Monitoring

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ORGANIZING AND INTERPRETING THE DATAequity and use, in figures and graphical forms,as and when needed. It is also possible to showprogress over time as the number of individualcommunity projects increases. Updating onlyrequires new information on current conditions,not historical analysis.Using aggregated scores from sub-indicators onsustained or effectively used services (e.g. asstacked bar charts, as shown in Figure 8),managers can rank individual communities intotop and bottom performers. Ranking givesmanagers and staff insight into the characteristicsof both groups. It helps them to bring communitiestogether for horizontal learning and to decidewhere to focus limited resources.Comparing community performance on individualand aggregated scores also helps identifyinteresting findings for case studies, especiallywhen combined with qualitative information.In situations where MPA is used for more researchfocusedpurposes, such as investigatingrelationships between factors or for comparingclusters of communities on specific aspects,statistical tests appropriate for ordinalmeasurements can be applied, providedconditions for statistual testing are satisfied. Thismeans ensuring that appropriate sample selectionprocedures have been followed, the correctstatistical test is selected, and sufficiently smallmargins of error are chosen to conclude that thedifferences or associations found are significant(that is, not due to chance). 17 For hypothesestesting, a 95 percent level of confidence isconsidered sufficient for most social research andmonitoring purposes, although MPA data haveoften produced results significant at a higher (99percent) level of confidence, i.e., with only 1percent probability that the tested relationshipfound is not true.Statistical testing for associations helps managersto see whether certain clusters of factors, as wellas individual factors, tend to occur together. MPAdata have been used in this manner to answerquestions such as:●●Are better-sustained services also better usedby all? If not, are non-users a mix of differenttypes of households or are certain groups,such as poor households, systematicallyexcluded?Are higher user payments for operation andmaintenance associated with greater choiceavailable to users (for service levels or for modesof financing, or choice by more groups in thecommunity), more equitable tariff systems,provision of training on financialmanagement, and/or better accountability tousers?To test for significant correlations, non-parametrictests are used because most scales used in theMPA are ordinal in nature. The strength of theassociation is measured through the correlationcoefficient. As the name indicates, a correlationmerely says that the two related aspects “co-relate,”or “occur together.” It does not say whetherincrease in scores for one aspect leads to asimultaneous increase in scores for the relatedaspect. Clear causal relationships are hard toestablish using ordinal data, since suchrelationships may only be tested using parametrictests such as multiple regression analysis or factoranalysis - which are applicable at higher levels ofmeasurement and require much larger samplesizes than is usual with MPA applications.17 For a fuller explanation readers can refer to standard textbooks for behavioral and social research such asResearch Methods and Anthropology: Qualitative and Quantitative Approaches by H. Russel Bernard. 1995.Altamira Press.60
ORGANIZING AND INTERPRETING THE DATASupplementing non-parametric tests of associationwith qualitative explorations of communityperceptions of causality can provide projectmanagers with sufficient insights for action. Tocite an example from the global study, bettergender balance in the village water and sanitationcommittees was found to be significantly associatedwith higher overall sustainability scores. Qualitativedata from focus groups explained that whencommunity service management organizations aregender-balanced, more management training cango to women, enabling them to exert greaterinfluence on service management, thus makingthe water service more responsive to their demandsand therefore more satisfying to the principal users(who are usually women in the community).Satisfied users value the service and therefore tendto pay user fees regularly, thus improving theadequacy of financing, which makes the servicemore sustainable .It can also be investigated if such relationshipscontinue to hold when controlling for otherpossible influencing factors, e.g., the level ofdevelopment in the communities concerned orthe complexity and age of the installed systems.Through building a model, it is possible to seewhich factors are most crucial in obtaining thedesired results. However, such analyses can onlybe done when the sample and data meet certainrequirements (see any methodological orguidebook on statistical analysis in the socialsciences).Insight through statistical analysis is attractive forprogram managers, policymakers andresearchers. It requires the presence of asociologist, economist or statistician experiencedin the use of non-parametric statistics at theprogram level. Her or his main functions are tosupervise data entry, analyze frequencies andcross-tabulations, decide on the statistical test(s),test the strengths of the associations amongindividual influencing factors, and between thosefactors and the achieved results in terms of howservices are sustained and used.61
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SustainabilityPlanning andMonitorin
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SustainabilityPlanning andMonitorin
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PrefaceThe mission of the Water and
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AcknowledgementsThe Participatory L
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viii
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4.9 Visualization and self-scoring
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Figure 18 KDP 2 activity cycle with
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THE CHALLENGE OF SUSTAINED WATER SU
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Page 25 and 26: THE CHALLENGE OF SUSTAINED WATER SU
Page 27 and 28: A NEW TOOL FOR PLANNERS AND MANAGER
Page 35 and 36: THE MPA FRAMEWORK AND PROCESSkey va
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Page 39 and 40: THE MPA FRAMEWORK AND PROCESS●●
Page 41 and 42: THE MPA FRAMEWORK AND PROCESSThe MP
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Page 45 and 46: THE MPA IN ACTIONaction points in i
Page 47 and 48: THE MPA IN ACTION●●●●●●
Page 49 and 50: THE MPA IN ACTIONBox 15 Key element
Page 51 and 52: THE MPA IN ACTIONsuccessful or unsu
Page 53 and 54: THE MPA IN ACTIONexternal facilitat
Page 55 and 56: THE MPA IN ACTIONBox 17 Indicative
Page 57 and 58: THE MPA IN ACTIONvisits and conduct
Page 59 and 60: THE MPA IN ACTIONScoring principles
Page 61 and 62: THE MPA IN ACTION4.10 Quality contr
Page 63 and 64: THE MPA IN ACTIONExperiences with t
Page 65 and 66: THE MPA IN ACTION5Organizing and In
Page 67 and 68: Box 22 Gender and poverty analysis
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Page 79 and 80: PARTICIPATORY TOOLS USED IN THE MPA
Page 109 and 110: Section 2MPAApplication Case Studie
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FROM THEORY TO PRACTICEAdding Accou
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ADDING ACCOUNTABILITY FOR GENDER EQ
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Table 2WSLIC 2: ADDING POVERTY ACCO
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Table 3 (continued) ADDING PERFORMA
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LOOKING BACK TO SEE FORWARDMembers
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LOOKING BACK TO SEE FORWARDFigure 2
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LOOKING BACK TO SEE FORWARDFigure 2
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LOOKING BACK TO SEE FORWARD●●
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LOOKING BACK TO SEE FORWARDMPA core
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EFFECT OF THE MPA ON GENDER RELATIO
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EFFECT OF THE MPA ON GENDER RELATIO
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ACHIEVING SUSTAINED SANITATION FOR
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HOW WELL DID THOSE DEVELOPMENT PROJ
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HOW WELL DID THOSE DEVELOPMENT PROJ
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Appendix AInstitutions that current
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Appendix BProcess designed forPLA P
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StepNo.7.ProcessAsk “Were users e
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ReferencesBernard, Russel H. (1995)
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Wijk, Christine van. (1998). ‘Gen
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Water and Sanitation ProgramWater S
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