In the context of the global energy transition, the energy sector faces challenges that demand a deep integration between data management and strategic planning. The growing availability of data, driven by commercial cloud tools, is enabling real-time decision-making and more resilient architectures. While some stakeholders are progressing toward strategic decision-making models based on real-time data, others with less technical capacity are still transitioning toward more modern infrastructures. At the same time, planning models are becoming increasingly complex thanks to the integration of artificial intelligence and machine learning, which allow for predictive simulations using more accurate weather and demand data.
However, significant challenges remain regarding data quality and standardization, as official sources do not always maintain uniform standards, making data consolidation difficult. The granularity of data also affects its usefulness for planning models, particularly in high-uncertainty scenarios such as renewable supply forecasting. Additionally, current models face a trade-off between robustness and detail level, which opens the door for hybrid approaches that combine deterministic and stochastic methods. In this context, the panel aims to discuss how public and private actors interact with regional data, identify success stories, and explore which challenges could be addressed through technical dialogues facilitated by OLADE.
