Productivity can vary considerably across firms within the same detailed industries.  Aggregate productivity indicators can mask these important differences in productivity across firms as well as the allocation of resources among them. Therefore, merely tracking aggregate figures does not fully capture the sources of productivity growth and gaps across countries.

Understanding how firm-level patterns shape aggregate productivity is crucial for crafting effective policies. For instance, it offers valuable insights into whether weak productivity performance stems from an underlying lack of innovation, a lack of technology and knowledge diffusion, or weak market selection and barriers to efficient resource reallocation.

Enhancing the measurement of productivity indicators through microdata is challenging, especially in a cross-country setting. It requires access to detailed information while preserving confidentiality, and harmonisation of concepts and statistical treatments across various data sources to compute complementary measures of productivity.

To tackle these challenges and to obtain comparable insights on productivity dynamics and its micro-drivers, the OECD conducts distributed microdata analysis projects in close collaboration with participating countries.

The OECD collects granular information that accurately represents the entire business population. This offers insights into productivity heterogeneity that reflects differences in technology and knowledge, management, organisation and practices, economies of scale and market power, among others. This approach notably identifies the performance of leading "frontier" firms alongside the least productive “laggard” firms, within countries and sectors, and accounts for other important dimensions, such as firm size and age.

Moreover, the OECD tracks productivity dynamics and assesses the contributions of within-firm productivity growth, the efficiency of resource (re)allocation and the role of firm creation and closure. These are key indicators for countries’ productivity dashboards.

Suitable data is crucial for analysing productivity across micro and macro levels. Therefore, it is key for countries to develop and enhance comprehensive data infrastructures capable of supporting rich measurement and in-depth analyses.

Achieving this objective entails reducing barriers to data access and integrating diverse sources to harness synergies across datasets, while safeguarding confidentiality. Simultaneously, there is a critical need to enhance the information content of firm surveys and administrative data to enrich analytical capabilities. Furthermore, implementing state-of-the-art productivity measurement and analysis necessitates investments in IT infrastructure to empower entities involved in the processing and use of microdata.