Network research competences are necessary for the proper functioning of modern societies organised on a network basis. The ability to navigate complex social, economic and relational networks, to solve complex problems based on the analysis of large volumes of unstructured data and decision making, and to innovate through networked collaboration have become the leading competences of the 21st century, not only for business but also for public administrations, thanks to the development of digitalisation. At present, Hungarian public administration legislation, law enforcement and operations are still dealing with and using the opportunities and challenges of the digital ecosystem, including network research methods and tools, in a potential way. Neumann's key public policy objective is to ensure that the adaptation of network research methods and tools and the exploitation of their results take place in the Hungarian public administration and at the level of the national economy. The aim is to provide professional support to governmental activities in such a way that data-driven decision making supported by network research is integrated into policy-making processes. One of the prerequisites for this is the development of a proactive, innovation-driven network research ecosystem in Hungary, which will prepare public policy makers for the challenges of the 21st century by strengthening analytical and data-driven decision-making capabilities, actively contribute to the growth of the data-driven economy, foster network-based innovation and scientific and methodological discovery, and contribute to accelerating the growth rate of the Hungarian economy.

A Neumann Nonprofit Közhasznú Kft. ennek megfelelően felelősen közreműködik:

  • in the design, preparation and implementation of the network science governance strategy,
  • managing and implementing sectoral network science-based management/development projects in line with the objectives,
  • the development of methodologies and projects in the field of administrative organisation and process diagnostics,
  • to support the domestic network science ecosystem.