2023-06-26-Devinit-尼泊尔LNOB评估_Simta市的数据景观（英）_20页_206kb

LNOB Assessment Summary: Data Landscaping in Simta Municipality

Introduction

The Leave No One Behind (LNOB) assessment evaluates data and evidence for addressing poverty and inequality, with a structured methodology focusing on data identification, analysis, and ecosystem foundations. Conducted in Simta Municipality, Nepal, it analyzed data inventory, usage, and systemic factors, identifying priority areas for improvement through local partnerships and desk-based reviews.

Part 1: Data Inventory and Assessment

Simta's ecosystem includes nine data systems. Key findings:

• Data Systems: Five administrative (e.g., health, education), two surveys, and two mixed-methods sources cover demographics, social protection, employment, education, health, disaster risk, disability, and WASH, but lack poverty-related voice and political participation data.
• Disaggregation: Successful for geography, gender, and age, but poor for ethnicity (only 2/9 systems) and disability (1/9 systems), limiting intersectional analysis.
• Frequency: Real-time data for events is common; however, surveys (e.g., Municipal Profile) are infrequently conducted, reducing reliability for decision-making.
• Accessibility and Quality: Open-access data is limited to aggregate statistics; metadata is incomplete for some systems, and discrepancies in disaster data affect trust and use.

Part 2: Data Usage

Data informs programs like skill training for persons with disabilities and budgeting, but utilization is underdeveloped due to:

• Low interest in evidence-based decisions.
• Inadequate digitization and accessibility.
• Distrust in data quality, partly due to lack of coordination and poor training.
  Opportunities exist for expanded advocacy and socioeconomic development initiatives.

Part 3: Data Ecosystem Foundations

Strengths and weaknesses are evident:

• Policies: A Data Management Policy ensures management but needs better implementation and mainstreaming.
• ICT Infrastructure: Lack of electrification in some wards (2 and 9) hinders digital use; internet connectivity is weak at both municipal and ward levels.
• Coordination: No formal data-sharing protocols; departments operate in silos.
• Budget: Inadequate funding for data activities, with only minor allocations; increased investment could enhance decision-making.

Part 4: Recommendations

• Data Sources: Digitize ethnicity from paper forms; improve education data frequency; train ward-level staff; complete metadata collection and ensure consistent disaster data sharing.
• Data Use: Enhance user skills with training and identify needs for prioritized publication.
• Governance and Management: Promote policy use, complete full electrification and internet connectivity, establish the Department of Monitoring, Planning and Data, and increase data-related budget allocations.

This summary highlights the need for systemic enhancements to make data accessible, reliable, and actionable for LNOB.