Project Details

CRLP Tool 1 – CDC Member Data Analysis

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Project Overview

This analysis was conducted as part of the UNIOPS Afghanistan Community Resilience and Livelihoods Project (CRLP) to support verification and profiling of Community Development Council (CDC) members using Tool 1. The primary purpose of the analysis is to assess the Completeness, consistency, and reliability of CDC members data collected during field verification exercises, and to identify updated, replaced, or missing members,
including the availability of contact information. The findings aim to inform program monitoring, reporting, and decision making by providing a clear and evidence-based overview of CDC membership status across sampled communities.

A total of 1,787 CDC members interviews were conducted across 236 Community
Development Councils (CDCs) as part of the CRLP Tool 1 verification process.
• The dataset demonstrates broad geographic coverage, with data collected from 21
provinces, representing approximately 62% of CDCs in Afghanistan.
• CDC membership shows a near-balanced gender distribution, comprising 962 male
(54%) and 825 female (46%) respondents.
• The largest concentration of sampled CDCs was observed in Nimroz (12%), Baghlan
(11%), and Kapisa (8%), reflecting areas with higher program coverage.

Key Features

End-to-end data pipeline: audit → cleaning → analysis → reporting
Robust data quality validation (missing values, duplicates, consistency checks)
Standardization of CDC member records across multiple provinces
Gender and role-based analytical segmentation
Reproducible and structured R-based workflow
Donor-ready outputs (tables, charts, and formal report)
Clear handling of sensitive data through anonymization practices

Tools and Technologies Used

This project was implemented using the R programming language, leveraging a structured and reproducible analytical workflow. Core libraries such as tidyverse, janitor, skimr, and lubridate were used for data manipulation, cleaning, auditing, and transformation. Data validation and consistency checks were systematically applied to ensure high data quality standards. Visualizations were developed using ggplot2 to produce clear and publication-ready charts, while final outputs were compiled into professional PDF reports aligned with donor reporting requirements. The entire workflow was managed within a project-based environment to ensure reproducibility and scalability.

Results and Outcomes

The project resulted in a fully cleaned and analysis-ready dataset covering 1,787 CDC members across 21 provinces, enabling reliable and structured analysis. Key data quality issues, including missing values, inconsistencies, and duplication risks, were identified and resolved to enhance data integrity. The analysis provided clear insights into gender distribution, role composition, and geographic coverage, supporting program monitoring and evaluation. Additionally, operational constraints related to member availability, tracing challenges, and replacement patterns were highlighted. The final outputs included standardized tables and visualizations that meet donor reporting standards and facilitate evidence-based decision-making.

Role and Responsibilities

In this project, I was responsible for designing and executing the complete data analysis pipeline, starting from raw data audit through to final reporting. This included conducting comprehensive data quality assessments, performing data cleaning and standardization, and ensuring consistency across all variables. I developed the analytical framework, generated descriptive insights, and created visualizations tailored to stakeholder and donor needs. Furthermore, I ensured that all processes adhered to principles of data integrity, confidentiality, and reproducibility, while aligning the analysis with the operational and strategic objectives of the CRLP program.