During March and April, the RAMSES project initiated its first implementation phase, aimed at supporting the development of a Handbook for Multi-Source Statistics (MSS). The project is structured around four key thematic areas.

Since March, a Project Manager has been appointed, and four sub-teams have been formed each dedicated to one thematic area. Team leaders have been identified and initiated coordination activities with their sub-teams as below. Initial planning and familiarization meetings focused on clarifying roles and the main thematic priorities, while also aligning team members to key challenges and objectives.

• Holistic transition - Sweden (Marie) 
• Interoperability - Canada (Flavio) 
• Ethics - New Zealand (Celeste Cutting) and US National Academy of Science (Jennifer Park)
• Quality - Australia (Claire Clarke)

Dedicated meetings with each sub-team allowed for early exploration of their respective thematic scope. Initial tasks included identifying relevant use cases, reviewing existing literature and prior projects, and clarifying shared challenges and expectations across themes.

On April 16th, a plenary meeting was held to present and discuss the first findings from the sub-team discussions. The meeting served both to share initial insights and raise open issues, and to start building a shared understanding of emerging priorities and interconnections across the four themes.

An in-person sprint meeting was proposed to take place in early June. Sweden offered to host the meeting. A questionnaire was prepared to collect from the members of the working group their preference as regards the dates of the meeting.

Key Insights

The work to date has surfaced several important findings:

National Statistical Offices (NSOs) face increasing demand for new statistics as well as more detailed and timely data, while simultaneously constrained by limited human and financial resources. Moreover, the decline in survey response rates and increasing respondent burden highlight the urgency of leveraging alternative data sources (e.g., administrative, private sector, and big data). MSS can be a cornerstone for transforming statistical systems by offering flexibility, efficiency, and innovation in data production.

Many NSOs begin by using alternative sources for specific needs (e.g., filling data gaps), and, through experience, evolve toward more comprehensive multi-source, multi-purpose systems. The proposed Handbook aims to guide NSOs through the transition to a multi-source statistical system, providing a step-by-step approach, structured around five key pillars:

1. Strategic Foundation:(vision definition, stakeholders’ engagement, governance establishment).
2. Legal and Infrastructure Readiness: (Ensuring institutional and legal frameworks).
3. Data Ecosystem and Methodology: (data sources mapping, quality assessment, integration methods development).
4. Pilot Use Cases and Implementation
5. Capacity Building and Communication: staff skills and users engagement

Emerging Themes and Questions

Areas of strong convergence:

• Shared understanding of the need for a holistic MSS framework
• Demand for practical, operational use cases
• Recognition of cross-cutting dependencies (e.g., interoperability and quality; ethics and design processes)

Open reflections

• Should MSS be viewed as part of a broader organizational transformation?
• How does MSS intersect with the concept of multi-purpose statistics?
• Where do current policy or practice gaps lie, and how can they be addressed?

Next Steps

• Finalize arrangements and agenda for the June sprint meeting
• Synthesize insights into a working draft structure for the Handbook
• Begin drafting content for thematic sections based on sub-team input