4.2 Collaborative IM and Multi-Stakeholder Management
Information Management does not operate in a vacuum. In humanitarian settings, multiple actors — including NGOs, UN agencies, government bodies, donors, and clusters — often collect, use, and share overlapping data. This creates opportunities for coordination, but also introduces challenges around duplication, data quality, privacy, and consistency.
This chapter outlines key strategies for managing IM in multi-stakeholder environments, with a focus on consortium coordination, reporting to multiple layers, and harmonizing terminology. It also integrates essential principles of responsible data sharing and governance.
4.2.1 IM in Consortiums and Inter-Agency Coordination
Consortiums are increasingly common in humanitarian response — where multiple organizations pool resources to deliver coordinated programming. From an IM perspective, consortiums introduce both complexity and value, particularly for coordinated programme service delivery:
Shared service tracking frameworks and data standards Define common variables for participant registration, case management, or activity tracking across partners to ensure consistency in service delivery.
Joint assessments and harmonized intake tools Develop shared needs screening, eligibility scoring, or registration forms that enable partners to implement aligned targeting and response strategies.
Common systems for operational data entry and exchange Use interoperable platforms (e.g., shared databases, mobile data collection systems) that allow partners to input, access, and synchronize programme data in real time.
However, coordination challenges include:
Varying IM capacities among partners
Differing data protection practices
Resistance to centralization or external visibility of raw data
Best Practices:
Agree early on a common IM strategy: This includes roles (who collects, who cleans, who reports), data formats, and ownership.
Develop a joint data-sharing protocol or Data Sharing Agreement (DSA): Clarify what data will be shared, the purpose, protection measures, and access rights. DSAs should outline obligations, storage rules, and accountability structures.
Introduce Data Sensitivity Classification: Label data by levels (e.g., public, internal, confidential) to guide protection, visibility, and sharing parameters.
Conduct Data Protection Impact Assessments (DPIAs): Especially important when personal or sensitive data is involved, DPIAs help assess and mitigate risk in advance.
Design interoperable tools and shared platforms: Excel formats, UUIDs, or open-source platforms (e.g., ActivityInfo, KoBo) support smoother integration.
Standardize partner training and onboarding: Align understanding of tools, definitions, timelines, and reporting expectations.
Build capacity across organizations: Ensure all stakeholders understand responsible data management, especially smaller local partners.
📌 The Humanitarian Data Academy emphasizes that responsible data sharing starts with clarity: who needs access, for what purpose, under what safeguards. See also: IASC Operational Guidance on Data Responsibility
4.2.2 Cross-NGO Collaboration for Programme Service Delivery
Beyond formal consortiums, programme teams frequently collaborate across NGOs in more informal or ad hoc ways to coordinate direct service delivery. Strong Information Management systems help ensure that these collaborative efforts are coherent, efficient, and responsibly managed.
Examples of Cross-NGO Collaboration in Programme Service Delivery Contexts:
Tool / Process
Description
Shared referral systems
NGOs working in the same geographical area (e.g., protection and livelihoods actors) agree on a unified referral mechanism and tracking system to streamline participant pathways and avoid duplication.
Common registration or intake tools
Organizations agree on shared forms or registration platforms for multisector response (e.g., emergency shelter and WASH), ensuring participants don't need to re-register across NGOs.
Harmonized service maps
Partners maintain a joint service map showing who provides what, where, and for whom — updated regularly to guide field teams in planning and coordination.
Interoperable case management systems
Where continuity of care is needed (e.g., in GBV or child protection), NGOs may adopt interoperable systems or shared UUIDs to ensure safe data transfer and service continuity.
Local partner-led coordination
In locally-led responses, national NGOs play a central role in coordinating and documenting shared response plans, using lightweight tools (e.g., shared spreadsheets or forms) with support from INGOs.
Key Considerations for Effective Cross-NGO PSD IM:
Ensure data protection and referral protocols are jointly defined and respected.
Clarify roles and responsibilities for data management, follow-up, and feedback loops.
Use lightweight, low-bandwidth tools where partners have limited infrastructure or connectivity.
Align terminologies and classification systems (e.g., types of services, population groups) to ensure interoperability.
Establish a shared understanding of data retention, consent, and access rights, especially in the absence of formal consortium agreements.
4.2.3 Navigating Reporting Layers: HQ, Donors, and Clusters
Field teams are often required to report the same data in multiple formats — for internal HQ use, donor reports, and inter-agency coordination mechanisms like clusters or the HRP. Without clear planning, this creates duplication, confusion, and reporting fatigue.
Strategies to manage complex reporting demands:
Map reporting requirements early: Identify which indicators are required by each layer (internal, donor, cluster).
Align reporting calendars and formats to reduce duplicate work.
Use a core indicator set that feeds multiple formats, with annexes or adaptations for specific stakeholders.
Build a ‘single source of truth’ database: This ensures the same data feeds all outputs, minimizing re-entry and version errors.
Automate report generation where possible (e.g., using Power BI or standard Excel exports).
Validate use permissions for each reporting layer — not all audiences need full access to granular or sensitive data.
💡 Organizations like NRC have developed Power BI dashboards that generate audience-specific reports from a centralized dataset — saving time and reducing errors.
4.2.4 Creating Libraries of Terminologies
One of the most overlooked but powerful tools in collaborative IM is the library of standardized terms — a collection of agreed-upon definitions, population groups, assessment classifications, vulnerability categories, service types, delivery modalities and sector-specific language, indicator names.
Why it matters:
Avoids confusion (e.g., “households reached” may differ between agencies)
Supports automated aggregation of data
Enhances clarity in joint service delivery, enabling partners to coordinate activities, align targeting, and ensure that services reach the right participants efficiently and equitably
How to build and use them:
Co-develop glossaries with partners during project design
Use standard references where possible (e.g., Sphere standards, IASC indicators, or HXL tags)
Maintain version control and allow contextual adaptation where needed
Link to internal indicator banks or metadata sheets
📎 Terminology libraries are living tools — they should be reviewed and updated regularly, especially in multi-year programs or responses involving localization. For more details on how to build Libraries of Terminologies refer to the Taxanomies secton in 5.2 Data Standardization & Data Harmonization
4.2.5 Key Takeaways
Effective programme service delivery in consortiums and inter-agency setups depends on early IM alignment, including shared data structures, clarity on roles, and agreement on technical workflows that support front-line implementation.
Data Sharing Agreements (DSAs) and Data Protection Impact Assessments (DPIAs) are essential for managing sensitive programme data responsibly, especially when multiple actors are involved in delivering services to the same communities.
Classifying data sensitivity supports safe service delivery by helping partners determine who can access which data and under what conditions, reducing the risk of misuse or harm to participants.
Building interoperable tools that support both service tracking and coordination reduces the burden on field teams and ensures that frontline data flows smoothly into inter-agency planning and resource allocation.
Standardized terminology libraries enhance consistency in how needs, services, and participants are defined — enabling smoother joint implementation, aligned targeting, and coherent participant experience across agencies.
REFERENCES & FURTHER READINGS
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