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LGCDP M&E Framework

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2. <strong>LGCDP</strong> Monitoring and Evaluation Plan<br />

MONITORING<br />

We propose to build <strong>LGCDP</strong>’s performance monitoring system around four pillars:<br />

• MC/PM Assessments (annually)<br />

• MLD administrative data (ongoing)<br />

• <strong>LGCDP</strong> Sample Surveys (every two years)<br />

• Indicator tracking (trimesterely)<br />

MC/PM Assessments of DDCs, municipalities and VDCs are a convenient,<br />

meaningful and already existing data collection mechanism (for DDCs). To monitor<br />

<strong>LGCDP</strong>, MC/PM assessments can provide a) information on overall progress through<br />

highly aggregated, qualitative indicator using a scorecard approach, and b)<br />

disaggregated information on detailed progress in fields of particular interest to<br />

<strong>LGCDP</strong> (for example inclusive decision-making or financial irregularities). MC/PM<br />

assessments for DDCs, municipalities and VDCs need to be done during the 3 rd<br />

trimester before the Nepal fiscal year begins on July 15 th .<br />

Recommendation:<br />

⇒ make extensive but selective use of aggregated and disaggregated<br />

MC/PM Assessment data for monitoring progress of <strong>LGCDP</strong><br />

Administrative data from MLD is currently only collected with regard to financial<br />

and physical progress. Over time, however, MLD should be increasingly able to<br />

collect, aggregate and analyze key administrative data from VDCs through DDCs. To<br />

be able to do that, MLD – especially its M&E Section - will need substantive support<br />

through <strong>LGCDP</strong>.<br />

Recommendation:<br />

⇒ start improving the capacity of MLD with a focus on collecting, entering,<br />

aggregating and analyzing readily available administrative data (e.g.<br />

number of participants at DDC planning meeting, degree of participation of<br />

DAGs)<br />

⇒ immediately increase the capacity of the M&E section of the MLD by hiring<br />

a DMIS/data analysis staff to aggregate already existing data<br />

22

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