Organizational Context

Community insights, data, and evidence are essential for effective decision-making, community level action and humanitarian diplomacy. Decades of evidence demonstrates the harm that can occur when local needs, vulnerabilities, capacities, voices, and perspectives are not leveraged for decision making.

The IFRC network has done major investment into data-driven decisions. However, there are critical gaps around quality, consistency, and use of data. Many tools, initiatives, and efforts exist; however, they are still compartmentalized by sector and/or thematic, ultimately hindering RCRC capacity to grasp this complex web of community needs and dynamics and effectively address it in a holistic way.

Humanitarian needs and challenges are interconnected, requiring a systemic understanding of communities. Investing into a systematic collection, analysis, and utilization of local and indigenous knowledge, perspectives and insights can shed light on the underlying factors contributing to inequities and enable the IFRC network to gain and share foresight into the community needs (as communities express them), innovations, capacities and vulnerabilities, therefore positioning the National Societies as a key actor to elevate people’s voices, risks and needs to those that can support.

Job Purpose

If future climate programming is to be handled better, the RCRC must adopt an integrated community evidence approach and improve its ability to define, generate, analyse, interpret, synthetize and use a unique set of community data for action and advocacy by and for communities. This consultancy is to support the building up, streamlining and strengthening of a community-based/community-led information and analysis system/function within the NS.

Objectives of the consultancy

1. Define approaches, tools and methodology to provide the unique RCRC approach to integrated evidence, insights and analysis of community needs, capacities and voices to regularly inform climate programming which are locally led.
2. Support the testing of approach in selected countries to define an integrated data model with National Red Cross Red Crescent Societies.
3. Support the definition of gaps and investments needed to expand and sustain an integrated community data driven approach.

Job Duties and Responsibilities

Activities and products

• Undertake a review of existing methods and tools to be leveraged from existing RCRC investments (ex. eVCA, IM tools, rapid assessments methodologies, perception surveys, community feedback) and best practices outside the Movement.
• Design a multi-dimensional analytical model to gather community-based evidence and facilitate interpretation and integrated analysis based on existing methods and tools.
• Prepare and facilitate a workshop (HCD methodology) to align on the RCRC unique data tools and methodology toward integrated community evidence for planning and humanitarian diplomacy. This will include co-designing approaches, platform, tools and methodologies, based on existing tools and agreeing on key investments, deliverables and costs for phase1, including NS data system and capabilities to be reinforced and sustained.
• Support the testing approach in 2 countries to propose the NS data operating model.
• Lead preparation of a training to finalize the roadmap and get participants from different sectors (CEA, IM, HD, Climate, Health and others) and expertise to gain a common understanding of integrated data collection methodologies, tools to be used in countries across regions.
• Develop a roadmap to define steps, roles and responsibilities and timeframe towards a simplified integrated community data approach which support an interoperable information management system.
• Finalize the comprehensive “how-to” guidance notes and tools for testing NS-led integrated community data system in 2 countries.

Desired outcomes

• Mapping of existing tools and initiatives to be leveraged (including from outside the Movement)
• An online workshop and training organized and delivered
• Workshop and training materials for replicating and scaling up the approach
• Development and finalization of tools and guidance.

Duration

50 days from September to December 2024.

Management of consultancy

IFRC CEA team.

Notes

The consultant will be contracted by the IFRC and the standard contractual terms will apply. Travel is expected as part of this consultancy.

Job Requirements

Education

Required

• Advanced degree (Master or higher) in social sciences, international development and data management or demonstrated equivalent experience – preferably in operational research, applied anthropology or sociology.

Experience

Required

• IFRC/Red Cross Red Crescent experience in undertaking and managing humanitarian information and data in operations and climate related programming (with focus on eVCA assessments and participatory planning processes).
• Experience in coordinating diverse and multidisciplinary teams, humanitarian partners and networks to strengthen community-centred approaches.
• Experience in delivering capacity building and training courses for local teams to produce and use operational social science data.
• Experience in low resource settings, including in emergency response settings.
• Experience working with the UN or an international organization or NGO.
• Practical experience in community-based programming at the national and international level.
• Experience with design thinking and human centered design methodologies to support data to action efforts and solutions generation.
• Demonstrated experiences and abilities to conduct human-centered research in low resource settings with various audiences and more specifically to support community-based decision making processing.

Knowledge, Skills and Languages

Required

• Fluent in spoken and written English.
• High level of familiarity with IFRC PMER approach, indicators, data standards, tools and processes.
• Demonstrated ability to use mixed methods with an emphasis on qualitative research methods and approaches.
• Demonstrated ability in manipulating large data sets and in using data analysis tools, artificial intelligence (AI), and languages.
• Knowledge of and experience with Information Management particularly in the areas of mobile data collection, data visualisation, including mapping and M&E.