CONCLUSION There is everywhere concern for decreasing funding combined with increasing needs for data on new topics and emergence of alternative data sources. Also have come up:  Need for more focus on diversified user needs, oriented to taking decisions;  Importance of collaboration, integration, timeliness, coherence, standardisation, accessibility, partnership;  Movement from stovepipe to common production environment with centralised and generalised solutions, but still flexible;  Challenges related to changed expectations of skills and capabilities, including for strategic leadership and governance and enterprise architecture design;

 Creation of a culture of continuous improvement, agility and change;  Need to adapt to evolving digital society, with new products and services that reflect technological/ communication/media-oriented daily reality;  Dissemination in more interactive, dynamic, attractive, visually-oriented way;  Service-oriented attitude to connect, aggregate and tailor statistical information;  Open data and machine to machine communication.

RECOMMENDATIONS 1.Efforts and clear activities should run continuously in order to enhance the sharing of experiences, expertise, tools and methods. 2.NSIs should adopt standards at different levels considering the Enterprise Architecture layers. 3.A plan of joint experiments designed at international level to foster common results and sharing output, focusing on training for new skills within NSIs and on partnerships with public and private bodies, and with the scientific community.

4.NSIs should adopt a proper strategic and operational planning system, using project and portfolio management techniques to ensure a continuity in the modernisation process. 5.The need for modernisation should be communicated effectively within NSIs, in order to involve the whole human resources, working all together with motivation for the same goal, and to make it a leverage for change. 6. A common framework at international level should be adopted in order to drive increasingly integrated and cross-cutting analyses between different statistical domains, also in order to supersede organisational stovepipes.