LGCDP M&E Framework
LGCDP M&E Framework
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 />
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