2026 Event Schedule

Amid mounting pressure to justify capital investments, extend asset life, and improve reliability, ENMAX Power has undertaken a transformative modernization of its asset management ecosystem. This session presents a technical case study of how ENMAX, in collaboration with Engineered Intelligence, re-built its asset management ecosystem to shift from fragmented, manually transformed datasets to a fully integrated, system-wide risk decision platform.

Previously, asset management decisions were constrained by fragmented data sources, manual processes, and limited visibility into system-wide risk. Critical datasets, such as system connectivity, inspection records, and asset health indicators were siloed across platforms like Power BI, Denodo, and Maximo, requiring time-consuming manual transformation. This not only introduced errors but also hindered ENMAX’s ability to model outage impacts, forecast failures, or justify capital investments in clear terms of reliability metrics. These challenges created a pressing need for a more integrated, transparent, and analytically rigorous approach to asset management.

The deployment of Engineered Intelligence’s platform, ENGIN, coupled with direct integrations to GIS and Maximo, enabled real-time ingestion of grid topology and asset condition, health, and inspection data. This eliminated manual data wrangling and significantly improved the fidelity of the distribution connectivity model, critical for accurate outage modeling and Customer Minutes of Interruption (CMI) calculations.

Additionally, ENMAX introduced ALRIS, a custom-built analytical layer that automates scenario analysis, failure forecasting, and lifecycle modeling. ALRIS provides a structured interface for analyzing risk, evaluating investment scenarios, and examining asset demographics, enabling consistent interpretation of complex data across planning and executive functions.

With this transformation, ENMAX has established a more transparent and analytically robust asset management ecosystem. ENMAX has enabled detailed tracing of restoration sequences used in Customer Minutes of Interruption (CMI) calculations, improving the accuracy and interpretability of outage impact assessments. Enhanced risk modeling capabilities allow users to analyze risk over time, identify contributing factors, and evaluate mitigation strategies in the context of investment planning. These tools support a more structured and data-driven approach to operational and strategic decision-making.