Evaluation of Data Management within the School Meals Program At Netherlands Red Cross

Leave a Comment / Netherlands / By

Please follow the following link to the terms of reference and purchasing conditions: INK-2025-001_Data management within the school meals program

Terms of Reference (ToR): Evaluation of Data Management within the School Meals Programme

Lessons for future data-driven work within the Dutch Red Cross

  1. Background and context

The Netherlands Red Cross (NRK) implements the School Meals Program to help children from low-income households access sufficient food at school. To implement this program effectively and at scale, NRK uses digital systems and data management. These systems help us register families, organize support, securely record data, and generate clear reports. Examples of data management support include 121, EspoCRM, Redline, Kobo Toolbox, and Powerbi.

The program offers valuable lessons on how data management can contribute to effective and responsible aid delivery. With this evaluation, the NRK aims to learn how data management can be better integrated into future programs.

2. Objectives

The aim of this evaluation is to ensure that data management – ​​how data is collected, managed and used, with an eye for people, processes and technology – is considered in a timely and thoughtful manner when setting up every programme within the Netherlands Red Cross.

Using the School Meals Programme as a case study, we aim to:

  1. Learn what works well in the field of data management and what can be improved in collaboration, processes and systems;
  2. Formulate concrete recommendations to structurally integrate data management into future programs within the Netherlands Red Cross.

In this way, we contribute to more effective, efficient and responsible National Aid provided by the Dutch Red Cross.

Main question :

What can we learn from the School Meals Program about organizing data management, so that we can apply this more structured and intelligently in future programs of the Dutch Red Cross?

3. Scope

This evaluation focuses on the organization, implementation, and collaboration around data management within the School Meals Program. The substantive programmatic results (such as the number of children reached or the impact on nutrition) are beyond the scope of this evaluation.

The scope includes three closely related components:

Setting up data management within the program

The evaluation examines how data management was set up during the School Meals Programme: what choices were made regarding people, processes and technology, how these choices were made, and to what extent they contributed to the efficient implementation of the programme.

Effect of data management on implementation

The evaluation analyzes how data management and digital systems (such as 121, EspoCRM, Redline, Kobo Toolbox, and Power BI) have contributed to the program’s efficiency, effectiveness, and accountability. It examines concrete effects, such as time savings, error reduction, data quality, and the usability of information for decision-making and reporting.

Preconditions and cooperation

The evaluation maps out which organizational, personnel, and technical conditions were necessary for data management to function properly, and how collaboration took place between program teams, 510, and IV-ICT in the design, implementation, and support of the systems.

In addition to these three components, the evaluation explicitly focuses on the applicability of the lessons learned for future NRK programmes .

The focus is on the following questions:

  1. Which elements of data management from this program are reusable or standardizable?
  2. How and when should data management be integrated into the program cycle (design, implementation, completion)?
  3. What preconditions are needed to organize data management in a sustainable, secure and scalable way within future programs?

4. Evaluation questions

Main question

What can we learn from the School Meals Program about organizing data management, so that we can apply this more structured and intelligently in future programs of the Dutch Red Cross?

Sub-questions – divided into themes

1. Setting up data management within the program

  • What choices were made in the data management setup (people, processes, technology)?
    – Who did what? Which systems were selected? Which processes were documented?
  • How did these choices come about?
  • What worked well, and what were the bottlenecks during implementation?
    – Consider scalability, error sensitivity, data quality, and ease of use.

– Were data needs considered during the design phase? Was there a standard approach or an ad hoc approach?

2. Effect of data management on implementation

  • To what extent did data management contribute to the program’s effectiveness?
    – Did it help make data-driven decisions? Was the data useful for monitoring or adjustments?
  • To what extent has it contributed to efficiency?
    – How fast are processes (e.g., registration, distribution, reporting)?
  • To what extent did it contribute to accountability?
    – Was NRK able to report clearly to donors and partners? Was there insight into who received what?

3. Preconditions & cooperation

  • What were the minimum requirements for successful data management?
    – Consider skills, involved teams, agreements, and support capacity.
  • How did the collaboration between program teams, 510, and IV-ICT proceed?
    – Was there clarity about roles? Was collaboration timely? Were there any issues that got stuck?
  • How was ownership of data management decisions assigned, and to what extent was there governance or oversight of data processes?
  • What arrangements are in place for transfer, data storage, and system management after the program ends?
    – Who has access? Where is data stored? Is there an exit strategy?

4. Applicability to future programmes

  • What can we standardize or simplify for future programs?
    – Are there processes or tools that are widely applicable?
  • When is the ideal time to integrate data management into a new program?
    – At the concept stage, during the initial pilot, or during scaling up?
  • What choices do we have to make as a result of laws and regulations (e.g., NIS2, privacy legislation)?
    – What is/is not permitted in terms of central systems, file management, and data sharing?
  • How can the lessons learned be translated into practical guidelines or standards for future NRK programmes?

5. Methodology

The evaluation primarily uses qualitative research methods , with an emphasis on interviews with stakeholders involved in the School Meals Program. The focus is on understanding experiences, choices, and collaboration regarding data management, and translating these insights into practical recommendations for future programs.

5.1 Research approach

The purpose of the evaluation is not to assess performance, but to understand how data management is structured, what worked , and what could be improved . The approach consists of four steps:

Documentanalyse

  • Objective: To gather context and factual information about the program design and system usage.
  • Sources: Project documentation, SOPs, GitHub overviews, audit reports, process descriptions, and reports.
  • Result: overview of existing working methods, roles and technical choices.

Semi-structured interviews

  • The core of the evaluation.
  • Objective: To gain insight into the experiences, challenges and success factors of those involved.
  • Expected participants:
    • School Meals Program Team (management, implementation, customer service)
      • 510 Data & Digital (technical and IM support)
      • IV-ICT (data infrastructure, privacy, security)
      • PMEAL (methodological input)
      • Selection of schools and/or district teams (user experience)
  • Method: To be determined by the performer.

Joint reflection session(s)

  • Objective: To validate findings and jointly formulate lessons that can be used for future programs.
  • Format: interactive workshop with representatives from the key teams (programme, 510, IV-ICT, PMEAL).
  • Output: shared priorities and concrete areas for improvement

Synthesis & validation

  • All findings are brought together in a draft report.
  • This will be shared with the involved teams for feedback to check the accuracy, completeness and applicability of conclusions.
  • The final version contains validated lessons and recommendations.

5.2 Expected output of the analysis

The interviews and reflections provide insights that are brought together around four main themes:

  1. How data management was organised in practice;
  2. How this affected performance and quality;
  3. Which conditions and collaborations were essential;
  4. How these lessons can be translated into guidelines for future programs.

6. Output

The evaluation produces a number of concrete products that support NRK in learning, improving, and strategically acting in the field of data management in (future) programs:

  • Evaluation report with key findings and recommendations
  • Summary in accessible language for internal communication
  • Toolkit/checklist for program teams with practical considerations for data management in new programs

Profile of the desired consultant

1. Education

  • The consultant has completed a relevant academic degree (e.g. social sciences, public administration, international cooperation or a similar field).
  • Additional training or experience in monitoring & evaluation, data analysis or digital systems is an advantage.

2. Experience

  • At least 3 to 5 years of experience conducting evaluations or similar research assignments.
  • Demonstrable experience working within the humanitarian sector or with civil society organisations.
  • Affinity with data-driven work and digital tools (such as dashboards, data management systems or digital registration tools).
  • Experience with the Red Cross or similar international networks is an advantage.

3. Skills

  • Can write clear, structured and concise reports.
  • Possesses strong analytical and communication skills.
  • Can work independently, but also coordinate well with different teams and stakeholders.
  • Works efficiently with digital tools (Microsoft Office, Excel, online surveys, data analysis tools).

4. Attitude and working style

  • Independent and objective in the execution of the assignment.
  • Results-oriented, careful and able to work within agreed timelines.
  • Interested in innovation, data and digital solutions within humanitarian aid.

How to apply

7. Timeline

  • Start date: as soon as possible
  • Concept rapport: 15/01/2026
  • Final rapport: 15/02/2026
  • Contact person Dutch Red Cross:
  • Pim Kemperman (pkemperman@redcross.nl)

8. Submission Requirements and Judging Criteria

Interested consultants or agencies are invited to submit their interest to the Logistics department (logistics@redcross.nl) by November 30th, with Pim Kemperman (pkemperman@redcross.nl) in CC of the Netherlands Red Cross (NRK). Applications will be reviewed on an ongoing basis.

Please include in the subject of your email:

Subject: INK-2025-001: Evaluation – data management Dutch Red Cross

The submission must contain the following:

  1. A brief summary of relevant experience for this assignment.
  2. CV
  3. Technical proposal
  4. Financial proposal
  5. Sample(s) of previous work
  6. Extract from the Chamber of Commerce registration

The technical and financial proposal can be based on a total of up to 25 days.

Please note: Incomplete submissions will not be considered.

Only selected candidates will receive a response. An interview may be held as part of the selection process.