Jamil Shoaib Jabbie

Leading the Analysis Process: Building Analysis Framework Using Excel

Assist in Finalizing Data Collection Tools

· Review and Feedback: Ensure that data collection tools (like surveys or interview guides) are clearly designed, unbiased, and aligned with research objectives. Provide feedback to refine questions and format.

· Pilot Testing: Conduct pilot tests to identify any issues in the tools and make necessary adjustments based on feedback from test participants.

· Ensure Validity and Reliability: Make sure the tools are valid (measure what they are supposed to measure) and reliable (produce consistent results over time).

Data Collection

· Field Management: Coordinate with enumerators and field staff to manage data collection activities, ensuring they follow protocols and ethical guidelines.

· Quality Control: Implement procedures to monitor data collection, such as random checks or reviews of collected data for accuracy and completeness.

· Ethical Standards: Ensure that data collection adheres to ethical standards, including obtaining informed consent and protecting participants' confidentiality.

· Conduct Focus Groups Discussion, Rapid Interviews, Key Informant Interviews, In-depth Interviews.

· Data Cleaning and Preparation: Organize and clean data in Excel, removing duplicates, handling missing values, and formatting for analysis.

· Framework Development: Develop a structured analysis framework in Excel, including data categorization, filtering, and sorting tools to systematically examine data.

· Statistical Analysis: Use Excel functions and formulas such as pivot tables.

Training Enumerators on Coding of Qualitative Data

· Introduction to Coding: Teach enumerators the basics of qualitative data coding, including open coding, thematic coding, and axial coding.

· Use of Coding Frameworks: Develop and provide a coding framework or codebook, guiding enumerators on how to apply codes consistently across transcripts.

· Practice Sessions: Conduct practice sessions where enumerators apply coding to sample data, providing feedback to ensure accuracy and consistency.

Transcription, Editing of Transcripts

· Transcription Guidelines: Provide clear guidelines for transcribing audio recordings, focusing on accuracy, completeness, and formatting.

· Quality Assurance: Do effective transcription, review transcripts for errors and consistency, ensuring that they accurately reflect the recorded data.

· Editing for Clarity: Edit transcripts for clarity while retaining the original meaning, correcting grammatical errors and standardizing formatting.

Data Inputting and Coding

· Accurate Data Entry: Ensure that data is entered accurately into databases or spreadsheets, using double-entry methods or cross-checks to minimize errors.

· Systematic Coding: Apply codes systematically to both qualitative and quantitative data, following predefined coding frameworks to ensure consistency.

· Data Management: Maintain an organized database or spreadsheet, with clear labels and documentation for all variables and codes.

Developing Summary Paragraphs Alongside Relevant Quotes

· Thematic Summarization: Create concise summaries of qualitative data that capture key themes and insights, using relevant quotes to support findings.

· Contextual Quotes: Select quotes that illustrate the main points and provide context to the themes being discussed.

· Clear and Coherent Writing: Write summaries that are clear and coherent, logically linking themes and quotes to provide a comprehensive overview of the data.

Integrating Completed Frameworks from Enumerators

· Consolidation: Gather and consolidate frameworks developed by different enumerators, ensuring consistency and completeness.

· Review and Harmonization: Review integrated data frameworks for consistency in coding and categorization, harmonizing discrepancies where necessary.

· Preparation for Analysis: Prepare integrated frameworks for final analysis, ensuring all data is correctly formatted and coded.

Submission and Presentation for Final Report Preparation

· Drafting Reports: Assist in drafting sections of the report, presenting data findings clearly and accurately.

· Visual Presentation: Develop visual aids (charts, graphs, tables) using Excel or other tools to effectively communicate key findings.

· Feedback Incorporation: Integrate feedback from stakeholders to refine and finalize the report.

Support in Generating Findings and Reports

· Report Compilation: Compile data analysis and findings into comprehensive reports, following the established report structure and guidelines.

· Summaries: Develop summaries that highlight key findings, implications, and recommendations.

· Review and Revision: Participate in the review and revision process, ensuring the report is accurate, clear, and aligned with research objectives.

Data Analysis and Interpretation Team Leadership and Mentorship

• Perform Complex Data Analysis: Conduct advanced statistical analyses to extract actionable insights from large datasets. This often involves using tools such as Excel and Pivot tables.
• Interpret Data Trends: Identify patterns and trends in data sets, and use this information to provide actionable recommendations to stakeholders.
• Guide a Team of Data Analysts: Provide leadership and direction to a team of data analysts, ensuring they are properly trained and able to meet the analytical needs of the organization.
• Mentorship and Development: Mentor junior analysts and help them develop their technical skills, and analytical thinking.

Data Strategy and Planning

• Develop Data Strategies: Collaborate with senior management to develop data strategies that align with business goals. This involves setting data management standards and ensuring consistent and accurate data collection.
• Project Management: Plan and manage data projects from inception to completion, ensuring that project goals are met on time and within budget.

Collaboration with Stakeholders

Communicate Insights: Present data findings and insights to stakeholders in a clear and concise manner, often through reports, decks, tables, dashboards, and visualizations.

Data Quality Assurance

• Ensure Data Accuracy and Integrity: Establish data validation processes and oversee data cleansing efforts to ensure high data quality.
• Develop and Enforce Data Standards: Create guidelines and best practices for data collection, storage, and analysis to maintain consistency across the organization.

Tool and Technology Management

• Manage Analytical Tools and Software: Oversee the selection and implementation of data analysis tools and software, ensuring they meet the needs of the team and organization.

Data Analysis and Interpretation Team Leadership and Mentorship

• Perform Complex Data Analysis: Conduct advanced statistical analyses to extract actionable insights from large datasets. This often involves using tools such as Excel and Pivot tables.
• Interpret Data Trends: Identify patterns and trends in data sets, and use this information to provide actionable recommendations to stakeholders.
• Guide a Team of Data Analysts: Provide leadership and direction to a team of data analysts, ensuring they are properly trained and able to meet the analytical needs of the organization.
• Mentorship and Development: Mentor junior analysts and help them develop their technical skills, and analytical thinking.

Data Strategy and Planning

• Develop Data Strategies: Collaborate with senior management to develop data strategies that align with business goals. This involves setting data management standards and ensuring consistent and accurate data collection.
• Project Management: Plan and manage data projects from inception to completion, ensuring that project goals are met on time and within budget.

Collaboration with Stakeholders

Communicate Insights: Present data findings and insights to stakeholders in a clear and concise manner, often through reports, decks, tables, dashboards, and visualizations.

Data Quality Assurance

• Ensure Data Accuracy and Integrity: Establish data validation processes and oversee data cleansing efforts to ensure high data quality.
• Develop and Enforce Data Standards: Create guidelines and best practices for data collection, storage, and analysis to maintain consistency across the organization.

Tool and Technology Management

• Manage Analytical Tools and Software: Oversee the selection and implementation of data analysis tools and software, ensuring they meet the needs of the team and organization.

Leading the Analysis Process: Building Analysis Framework Using Excel

Assist in Finalizing Data Collection Tools

· Review and Feedback: Ensure that data collection tools (like surveys or interview guides) are clearly designed, unbiased, and aligned with research objectives. Provide feedback to refine questions and format.

· Pilot Testing: Conduct pilot tests to identify any issues in the tools and make necessary adjustments based on feedback from test participants.

· Ensure Validity and Reliability: Make sure the tools are valid (measure what they are supposed to measure) and reliable (produce consistent results over time).

Data Collection

· Budgeting for data collectors, transcribers and analysts: (Fees and wages)

Field Management: Coordinate with enumerators and field staff to manage data collection activities, ensuring they follow protocols and ethical guidelines.

· Quality Control: Implement procedures to monitor data collection, such as random checks or reviews of collected data for accuracy and completeness.

· Ethical Standards: Ensure that data collection adheres to ethical standards, including obtaining informed consent and protecting participants' confidentiality.

· Data Cleaning and Preparation: Organize and clean data in Excel, removing duplicates, handling missing values, and formatting for analysis.

· Framework Development: Develop a structured analysis framework in Excel, including data categorization, filtering, and sorting tools to systematically examine data.

· Statistical Analysis: Use Excel functions and formulas such as pivot tables.

Training Enumerators on Coding of Qualitative Data

· Introduction to Coding: Teach enumerators the basics of qualitative data coding, including open coding, thematic coding, and axial coding.

· Use of Coding Frameworks: Develop and provide a coding framework or codebook, guiding enumerators on how to apply codes consistently across transcripts.

· Practice Sessions: Conduct practice sessions where enumerators apply coding to sample data, providing feedback to ensure accuracy and consistency.

Transcription, Editing of Transcripts

· Transcription Guidelines: Provide clear guidelines for transcribing audio recordings, focusing on accuracy, completeness, and formatting.

· Quality Assurance: Do effective transcription, review transcripts for errors and consistency, ensuring that they accurately reflect the recorded data.

· Editing for Clarity: Edit transcripts for clarity while retaining the original meaning, correcting grammatical errors and standardizing formatting.

Data Inputting and Coding

· Accurate Data Entry: Ensure that data is entered accurately into databases or spreadsheets, using double-entry methods or cross-checks to minimize errors.

· Data Management: Maintain an organized database or spreadsheet, with clear labels and documentation for all variables and codes.

Developing Summary Paragraphs Alongside Relevant Quotes

· Thematic Summarization: Create concise summaries of qualitative data that capture key themes and insights, using relevant quotes to support findings.

Integrating Completed Frameworks from Enumerators

· Consolidation: Gather and consolidate frameworks developed by different enumerators, ensuring consistency and completeness.

· Review and Harmonization: Review integrated data frameworks for consistency in coding and categorization, harmonizing discrepancies where necessary.

Submission and Presentation for Final Report Preparation

· Drafting Reports: Assist in drafting sections of the report, presenting data findings clearly and accurately.

· Visual Presentation: Develop visual aids (charts, graphs, tables) using Excel or other tools to effectively communicate key findings.

· Feedback Incorporation: Integrate feedback from stakeholders to refine and finalize the report.

Data Analysis and Interpretation Team Leadership and Mentorship

• Perform Data Analysis: Conduct advanced statistical analyses to extract actionable insights from large datasets. This often involves using tools such as Excel and Pivot tables.
• Interpret Data Trends: Identify patterns and trends in data sets, and use this information to provide actionable recommendations to stakeholders.
• Guide a Team of Data Analysts: Provide leadership and direction to a team of data analysts, ensuring they are properly trained and able to meet the analytical needs of the organization.
• Mentorship and Development: Mentor junior analysts and help them develop their technical skills, and analytical thinking.

Data Strategy and Planning

• Develop Data Strategies: Collaborate with senior management to develop data strategies that align with business goals. This involves setting data management standards and ensuring consistent and accurate data collection.
• Project Management: Plan and manage data projects from inception to completion, ensuring that project goals are met on time and within budget.

Collaboration with Stakeholders

Communicate Insights: Present data findings and insights to stakeholders in a clear and concise manner, often through reports, decks, tables, dashboards, and visualizations.

Data Quality Assurance

• Ensure Data Accuracy and Integrity: Establish data validation processes and oversee data cleansing efforts to ensure high data quality.
• Develop and Enforce Data Standards: Create guidelines and best practices for data collection, storage, and analysis to maintain consistency across the organization.

Tool and Technology Management

• Manage Analytical Tools and Software: Oversee the selection and implementation of data analysis tools and software, ensuring they meet the needs of the team and organization.

M&E Oversight: Manage M&E frameworks to assess CHWs’ effectiveness in the "Caring for Caregivers" project.
Data Collection and Analysis: Conduct interviews with caregivers, CHWs, and DHMT staff; handle transcription, editing, and data analysis.
- **Reporting and Feedback**: Prepare reports, address client feedback on behalf of the Managing Director, and ensure project goals are met.
- **Quality Control**: Ensure data integrity and adherence to quality standards in all M&E activities.

• Design and Implement Data Collection Methods: Develop strategies for gathering both qualitative and quantitative data.
• Analyze Data Trends: Use statistical tools for quantitative data and thematic analysis for qualitative data.
• Ensure Accuracy in Reporting: Validate and verify data to maintain high-quality insights.
• Lead Data Projects: Oversee and manage data analysis projects from start to finish.
• Collaborate with Stakeholders: Work with team members and stakeholders to understand their data needs and provide insights.
• Communicate Findings: Present clear and actionable data insights to support decision-making and strategic planning.

• Study Coordination: Oversee qualitative and quantitative study for the Child Marriage Study.
• Preparation and presentation analysis framework, data collection, transcription, and coding.
• Data Management: Manage data collection processes, including surveys and interviews, and ensure data integrity.
• Analysis and Reporting: Analyze both qualitative and quantitative data and put together findings from the data .
• Stakeholder Engagement: Communicate with project stakeholders to ensure effective implementation and alignment with study objectives.

• Study Coordination: Oversee qualitative and quantitative study for the CHW Assessment Study with Focus 1000.
• Preparation and presentation analysis framework, data collection, transcription, and coding.
• Data Management: Manage data collection processes, including surveys and interviews, and ensure data integrity.
• Analysis and Reporting: Analyze both qualitative and quantitative data and put together findings from the data .
• Stakeholder Engagement: Communicate with project stakeholders to ensure effective implementation and alignment with study objectives.

• Study Coordination: Oversee qualitative study for the Town Hall Debate Project with BBC Media Action Sierra Leone.
• Preparation and presentation analysis framework, data collection, transcription, and coding, preparation and presentation of top findings.
• Data Management: Manage data collection processes, including surveys and interviews, and ensure data integrity.
• Analysis and Reporting: Analyze both qualitative and quantitative data and put together findings from the data .
• Stakeholder Engagement: Communicate with project stakeholders to ensure effective implementation and alignment with study objectives.

• Study Coordination: Oversee qualitative and quantitative studies for the Mobile Technology for Community Health (MOTEC) project with World Vision International Sierra Leone. Partook in the development of the study protocol document for the (MOTEC) study.
• Data Management: Manage data collection processes, including surveys and interviews, and ensure data integrity.
• Analysis and Reporting: Analyze both qualitative and quantitative data, and prepare detailed research reports.
• Stakeholder Engagement: Communicate with project stakeholders to ensure effective implementation and alignment with study objectives.

• Study Coordination: Oversee qualitative and quantitative study for the Mobile Technology for Community Health (MOTEC) project with World Vision International Sierra Leone. Partook in the development of the study protocol document for the (MOTS) study.
• Data Management: Manage data collection processes, including surveys and interviews, and ensure data integrity.
• Analysis and Reporting: Analyze both qualitative and quantitative data, and prepare detailed research reports.
• Stakeholder Engagement: Communicate with project stakeholders to ensure effective implementation and alignment with study objectives.

Research Coordination: Assist in managing the qualitative research study for the Communication Programme with Johns Hopkins University through Dalan Development and Management Consultants Data Collection: Conduct interviews, focus groups, and other qualitative data collection methods. Data Analysis and Reporting: Transcriptions, Analyze qualitative data and contribute to the preparation of research reports and findings. Stakeholder Communication: Liaise with project stakeholders and ensure alignment with research objectives.

Research Coordination: Assist in managing the qualitative research study for the Communication Programme with Johns Hopkins University through Dalan Development and Management Consultants Data Collection: Conduct interviews, focus groups, and other qualitative data collection methods. Data Analysis and Reporting: Transcriptions, Analyze qualitative data and contribute to the preparation of research reports and findings. Stakeholder Communication: Liaise with project stakeholders and ensure alignment with research objectives.

Research Coordination: Assist in managing the qualitative research study for the Communication Programme with Johns Hopkins University through Dalan Development and Management Consultants
Data Collection: Conduct interviews, focus groups, and other qualitative data collection methods.
Data Analysis and Reporting: Transcriptions, Analyze qualitative data and contribute to the preparation of research reports and findings.
Stakeholder Communication: Liaise with project stakeholders and ensure alignment with research objectives.