This report draws upon the results of three projects in different regions in Italy, covering distinct regulatory areas, to assess the increasingly important role played by data analytics in applying and enforcing rules.

The importance of risk-based approaches to regulatory inspections and enforcement is well known. However, regulators seeking to incorporate risk-based approaches still encounter roadblocks in terms of insufficient data generally and inadequate data management tools specifically. While using some risk analysis is more efficient than no risk analysis at all, data-related roadblocks have made it more difficult to identify risk factors. This problem has become more pronounced during the COVID-19 pandemic, where regulatory inspections and enforcement activities and related interventions had to be prioritised in order to balance safety concerns. However, recent developments have shown that data management can help improve inspection systems quite quickly, in an easier and cheaper way than in the past, because costs for equipment are lower, less specialist staff time is required, and computing power has increased. Developments in machine learning have also made the analysis of large volumes of data faster.