Course Introduction
Gender-based violence programmes generate sensitive and complex information about prevention activities, survivor support, referrals, case management, service utilization, community interventions, protection mechanisms, and programme outcomes. Effective analysis of this information can help organizations understand service demand, identify delivery gaps, monitor programme reach, strengthen referral pathways, and improve the allocation of resources while maintaining survivor safety, confidentiality, dignity, and informed decision-making.
This course provides practical approaches for collecting, managing, analyzing, and interpreting gender-based violence programme data across prevention, response, referral, protection, and recovery interventions. Participants examine information relating to programme activities, service access, referrals, case management processes, training, community engagement, and institutional performance. Particular emphasis is placed on data quality, appropriate aggregation, safe handling of sensitive information, and analytical approaches that avoid exposing survivors or creating additional risks.
Participants will develop practical skills in spreadsheet analysis, database management, descriptive statistics, dashboards, business intelligence, trend analysis, segmentation, and programme performance reporting. They will learn how to analyze service demand, referral completion, response times, programme coverage, training participation, prevention activities, and institutional performance. The course also explores how to distinguish activity and output measures from outcome indicators and how to communicate findings without compromising confidentiality or survivor protection.
The programme introduces advanced applications including geographic analysis, service accessibility mapping, predictive analytics, artificial intelligence, digital case management, and automated reporting. Participants explore how these technologies may support programme planning, resource allocation, referral coordination, service-demand forecasting, and early identification of operational pressures. The course emphasizes that analytics involving GBV data require heightened safeguards, careful interpretation, human oversight, and strong controls against profiling, discrimination, re-identification, and inappropriate automated decision-making.
Data governance is a central component of the programme because GBV information can contain highly sensitive personal, health, protection, and case-related details. Participants examine confidentiality, data minimization, informed consent, secure data storage, role-based access, encryption, retention, controlled information sharing, cybersecurity, and responsible use of aggregated data. The course also addresses ethical risks associated with collecting information from survivors and vulnerable populations, ensuring that analytical processes support rather than undermine survivor-centered principles.
By the end of the course, participants will be able to develop practical analytical workflows for monitoring GBV programmes while protecting sensitive information and maintaining responsible data practices. They will be better equipped to develop safe dashboards, assess service coverage, analyze referral pathways, monitor programme performance, identify implementation gaps, and communicate evidence to decision-makers. The course ultimately supports stronger, data-informed programming while recognizing that analytical efficiency must never take precedence over survivor safety, confidentiality, dignity, and ethical practice.
Duration
5 days
Who Should Attend
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Gender-based violence programme managers responsible for planning, coordination, implementation, and performance management.
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GBV programme officers working on prevention, response, protection, referral, and survivor support initiatives.
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Monitoring and evaluation professionals responsible for GBV programme indicators, results frameworks, and reporting.
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Data and information management officers supporting GBV information systems and programme databases.
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Case management professionals responsible for service coordination, referrals, follow-up, and programme-level reporting.
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Protection officers working with safeguarding, protection monitoring, referral mechanisms, and survivor-centered programmes.
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Social workers and community service professionals supporting GBV prevention and response programmes.
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Health and psychosocial support programme professionals working with GBV-related service delivery and referrals.
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Government officials involved in gender, social protection, justice, health, protection, and GBV response programmes.
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NGO and humanitarian professionals implementing GBV prevention, response, and community-based protection interventions.
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Programme quality and accountability professionals supporting evidence-based GBV programming and service improvement.
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Research professionals analyzing aggregated GBV programme, service access, prevention, or protection data.
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Referral and coordination officers monitoring service availability, referral pathways, and inter-agency coordination.
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Safeguarding and compliance professionals responsible for responsible information management and organizational controls.
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Professionals seeking practical analytics skills for sensitive, survivor-centered GBV programme monitoring and decision support.
Course Objectives
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Develop practical skills for collecting, organizing, validating, aggregating, and analyzing GBV programme data while maintaining confidentiality and survivor-centered data practices.
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Apply appropriate analytical techniques to understand programme reach, service demand, referral pathways, response processes, prevention activities, and organizational performance.
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Use spreadsheets, databases, dashboards, and business intelligence tools to generate useful programme-level insights from appropriately protected and aggregated GBV information.
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Develop meaningful indicators for monitoring service availability, referral completion, response times, prevention activities, training, outreach, programme coverage, and service quality.
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Analyze programme trends and service patterns without unnecessarily exposing personally identifiable or sensitive survivor information through reports or visualizations.
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Apply geographic, segmentation, comparative, and trend analytics to identify service-access gaps, underserved populations, programme coverage differences, and operational priorities.
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Explore predictive analytics, artificial intelligence, automation, and digital information systems while recognizing risks related to bias, re-identification, profiling, and inappropriate automated decisions.
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Strengthen data governance practices covering consent, confidentiality, data minimization, secure storage, access controls, retention, information sharing, cybersecurity, and ethical use.
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Develop safe dashboards, analytical reports, and management summaries that communicate programme performance without compromising survivor safety, dignity, privacy, or confidentiality.
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Integrate analytical evidence into programme planning, resource allocation, referral-system strengthening, quality improvement, and strategic decision-making while maintaining human oversight and ethical safeguards.
Comprehensive Course Outline
Module 1: Foundations of Data Analytics for Gender-Based Violence Programmes
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Understanding the role of data analytics in GBV prevention, response, protection, referral, survivor support, and programme management.
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Mapping the GBV programme data lifecycle from activity planning and service delivery through monitoring, referral, follow-up, reporting, and programme learning.
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Identifying appropriate analytical questions concerning programme reach, service availability, referrals, response processes, prevention activities, and operational performance.
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Understanding descriptive, diagnostic, predictive, and prescriptive analytics while recognizing the heightened ethical requirements associated with sensitive GBV information.
Module 2: GBV Programme Data Collection, Quality, Aggregation, and Information Management
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Designing safe data collection processes for programme monitoring, service delivery, referrals, training, outreach, prevention, and institutional performance measurement.
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Identifying missing, inconsistent, duplicate, outdated, or incorrectly classified programme records that can affect the reliability of aggregate analysis.
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Applying appropriate aggregation, anonymization, pseudonymization, data minimization, and suppression approaches to reduce the risk of survivor identification.
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Establishing data dictionaries, validation procedures, metadata, quality checks, documentation, and controlled workflows for sensitive GBV programme information.
Module 3: Spreadsheet, Database, and Business Intelligence Analytics
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Using spreadsheet formulas, pivot tables, filters, charts, and data-cleaning techniques to analyze appropriately aggregated GBV programme datasets.
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Understanding database structures, unique identifiers, relationships, queries, and access controls relevant to secure programme information management.
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Developing safe dashboards for programme coverage, referral performance, prevention activities, service availability, response indicators, and organizational performance.
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Applying responsible visualization techniques that communicate useful programme insights without displaying unnecessary personal, case-level, or potentially identifying information.
Module 4: Survivor Services, Referral, and Service Access Analytics
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Analyzing aggregate service-demand patterns across appropriate service categories while protecting survivor confidentiality and avoiding unnecessary case-level exposure.
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Measuring referral volumes, completion rates, turnaround times, unsuccessful linkages, service availability, and coordination performance across referral pathways.
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Examining service accessibility by location, facility type, service category, operating period, and other appropriate programme-level dimensions.
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Developing indicators for service response, referral effectiveness, follow-up processes, case management performance, and continuity of survivor-centered support.
Module 5: GBV Prevention, Community Engagement, and Programme Reach Analytics
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Analyzing prevention activities, awareness initiatives, community engagement, training, outreach, and institutional strengthening interventions using appropriate programme indicators.
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Measuring participation, geographic coverage, target-group reach, activity completion, partner engagement, and other relevant prevention programme measures.
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Examining trends in programme reach and identifying communities or population groups that may have limited access to prevention or support services.
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Distinguishing programme activities, outputs, intermediate outcomes, and longer-term outcome measures when assessing prevention and response programme performance.
Module 6: Programme Performance, Resource, and Quality Analytics
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Developing performance dashboards for programme coverage, service availability, referral systems, training, outreach, implementation progress, and resource utilization.
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Applying trend, variance, cohort, and comparative analysis to identify operational bottlenecks, implementation delays, service gaps, and changing programme demands.
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Analyzing resource allocation, staffing, partner performance, programme expenditure, service capacity, and workload indicators at appropriate aggregate levels.
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Translating analytical findings into programme improvement actions while ensuring that quantitative indicators do not replace professional judgment or survivor-centered quality standards.
Module 7: Geographic, Risk, and Service Accessibility Analytics
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Applying GIS and geographic analysis to understand service availability, referral pathways, geographic coverage, and potential access barriers without exposing survivor locations.
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Developing appropriate programme-level risk indicators to support resource planning, prevention activities, service capacity assessment, and operational preparedness.
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Analyzing geographic and population-level disparities in programme access while applying disclosure controls to prevent re-identification of individuals or small groups.
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Using analytical evidence to support referral network planning, service mapping, outreach prioritization, emergency preparedness, and equitable programme coverage.
Module 8: AI, Predictive Analytics, Automation, and Emerging GBV Technologies
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Exploring artificial intelligence and machine learning applications for programme monitoring, service-demand forecasting, administrative automation, and aggregated trend analysis.
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Examining digital case management platforms, mobile data collection, automated reporting, secure information exchange, and other emerging technologies.
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Assessing predictive models for programme demand and operational pressures while recognizing limitations associated with biased, incomplete, or sensitive data.
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Applying responsible AI principles including human oversight, explainability, bias testing, privacy protection, accessibility, data minimization, and safeguards against harmful profiling.
Module 9: GBV Data Governance, Privacy, Cybersecurity, Ethics, and Safeguarding
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Establishing governance frameworks covering data ownership, access rights, confidentiality, retention, secure processing, documentation, accountability, and responsible information sharing.
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Protecting sensitive information through role-based access, authentication, encryption, secure storage, audit controls, breach-response procedures, and cybersecurity practices.
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Addressing ethical challenges involving informed consent, secondary data use, survivor confidentiality, vulnerable populations, data linkage, re-identification, and inappropriate disclosure.
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Developing responsible analytical practices that align data use with survivor-centered principles, safeguarding requirements, professional standards, legal obligations, and organizational policies.
Module 10: Integrated GBV Programme Data Analytics Project
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Designing an end-to-end analytical project using a realistic, appropriately anonymized or aggregated GBV programme dataset to address a practical management question.
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Cleaning, transforming, analyzing, and visualizing programme, service, referral, prevention, and performance data using safe and appropriate analytical methods.
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Developing a secure management dashboard and analytical report containing relevant indicators, trends, service gaps, programme findings, and evidence-based improvement opportunities.
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Presenting analytical findings responsibly and demonstrating how data can support stronger programme planning, referral systems, resource allocation, service quality, and organizational learning.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
