- Commodity Management & Trading
- Customer & Marketing Strategy
- Digital Engineering
- Station Studio
- Supply Chain & Industry 5.0
- Sustainability
Advanced Analytics for Grid Operations
This delivers operate with insight—leveraging Big Data, ML, and AI to improve and streamline grid management, anticipating potential risks, building scenarios, and identifying optimization windows across the full transmission and distribution value chain.
Forecasting, simulation, and optimization techniques model cost, demand, and anomalies, improving planning accuracy and enabling more confident decisions.
AI and ML applied to grid data anticipate risks and failures, enabling proactive interventions and reducing unplanned incidents.
Advanced platforms and proven algorithms ensure robust, explainable, and trusted models for operational and business decision-making.
NLP and Generative AI transform unstructured data into actionable insights, enabling easy analytics adoption without deep technical expertise.
How NTT DATA helps
Advanced analytics platforms (20+ years, 50+ projects) leverage Big Data, ML, and AI to enhance grid operations using leading tools like Python, R, SAS, AWS, and Azure.
Machine learning (supervised and unsupervised) identifies patterns, anomalies, and optimization opportunities across grid assets and operations.
Forecasting and simulation techniques (10+ years, 30+ projects) optimize operations by modeling cost, demand, and anomalies to support data-driven decisions.
Advanced process mining solutions (15+ years, 50+ projects) identify risks and bottlenecks, leveraging NLP and GenAI to transform unstructured data into actionable insights.
NTT DATA enables utilities to turn grid data into a strategic asset, anticipating risks and enabling faster, more informed decisions across the network lifecycle.
Advanced forecasting models and simulation tools improve the precision of demand, cost, and anomaly predictions—enabling more accurate planning, better resource allocation, and reduced operational uncertainty.
Predictive AI and ML anticipate asset failures, enabling proactive maintenance and reducing incidents. Proven results show up to ~80% lower failure risk and ~5% KPI improvement.
Real-time analytics and visualization dashboards reduce the time needed to identify risks, detect anomalies, and respond to grid events—enabling faster, better-informed decisions at both operational and strategic levels.
