Digital transformation changes the way people live and work. Augmented reality, artificial intelligence, machine learning, remote sensing, automation, cybersecurity, big data, all these terms are ubiquitous now. Information and Communication Technology (ICTs) diffuse into all areas of life. The digital revolution radically changes social interactions and individual well-being. Cloud computing, 3D printing, biometric sensors, robotics, Internet of Things, and all other relevant digital systems affect business environments, models and product designs regarding accessibility, speed, consumer engagement, competition, and operational efficiency. This has a profound impact on all areas life and poses a continuous challenge to official statisticians to react swiftly to changing needs of stakeholders related to new socio-economic developments, varying environments and a need to progress. Measuring what matters is crucial in the context of the driving forces of societal and economic changes, like digital transformation. This challenge has many dimensions though. What matters? Does it still matter? Is the measurement tool appropriate? How broad and deep is the measurement? There are many ways in which statistical systems try to respond. Nevertheless, it’s always necessary to have a basis on sound theoretical foundations. The digital transformation is a challenging topic. The fast pace of new developments is unprecedented. However, it seems there is still a lack of robust conceptual frameworks capturing digital transformation in an easy to apply way.

The advent of information society and the digital economy, have led to an explosion of new phenomena and changes to existing relationships. At the same time, potential quantification is enriched through new data sources, providers, and collection methods. In this environment, social and economic phenomena become more complex, linked to multiple bodies of knowledge. This requires a multidisciplinary approach. This paper follows general methods used in the process of conceptual framework building.

Official statistics agencies must adjust their operations to remain a core pillar of information infrastructure. However, responding to a wide range of information needs poses potential risks. It is a challenge which needs to be addressed with a comprehensive and systematic approach to ensure both, agility in reacting to increasing and new information needs, and maintaining the highest quality of statistics achieved by adherence to rigorous methodology. This paper proposes a conceptual framework for the analysis of digitization and digitalization. This helps in identifying new measurement needs and challenges, that lead to assessing the impact of digital transformation. There are both lessons and opportunities for official statisticians.