Real-time Demand Analytics
for Energy and Utilities

Improve customer insight and risk management with first-class business analytics

The energy sector is transforming rapidly and competition among the energy providers in the market is fierce. Business foresight and the development of new business models are key strategies in achieving competitive advantage. Utilizing intelligent business analytics is essential to having better customer insights and managing risks.


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Customer insight improvement

  • Predict customer demand and behaviour
  • Customer profitability measurement
  • Acquisition, retention and communication
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Planning and forecasting

  • Tariff optimization and trade risk management
  • Network investment management and proactive maintenance
  • Financial planning and 'what-if' scenarios
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Transformation of energy and utilities

  • Load balancing for efficient resource utilization
  • Transformation of energy generation
  • Transformation of consumption


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Use of Data Analytics

  • The use of new analytical methods for compiling and presenting business critical information provides an effective method for decision making
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Smart Grid and Smart Metering Systems

  • Smart meters have been widely adopted across Europe, new generations of smart meters will also be implemented as will further global roll outs
  • Consumption data is typically collected daily showing hourly usage and is required for next day trading and longer term planning such as for customer segmentation and new product and pricing innovation
  • The huge amount of data provided even by the milli-second in the smart grid needs to be analysed in real time to obtain valuable information
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Customer and market data mining

  • Data mining from internal and external sources provides the necessary insight for new business development opportunities with greater accuracy for risk management, financal reporting and much more such as pro-active maintenance
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Real-time Demand Analytics

Real-time analytics enables production of modern and understandable dashboard reports and analysis to support decision making, bringing a level of report automation, rapid queries and clarity for business efficiency

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Real-time Demand Analytics - Metadata Management

Creates data models for use in business analytics and continued learning and improvements

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Real-time Demand Analytics - Predictive Analytics

Processes and classifies information with predictive analysis techniques, aiming to predict the future for better business outcomes such as improved margins and customer satisfaction

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Real-time Demand Analytics - Data Warehousing

Connects and stores the data collected from different sources even in real-time, and creates the basis for analytics bringing efficiencies from such automation and increased speed of data processing


Data Sources

Social Media Correspondence OMS Billing CIS/CRM MDMS 3rd Party Call Center