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Data-driven Utilities

  • October 2013
  • -
  • Frost & Sullivan
  • -
  • 48 pages

Business Intelligence and Analytics to become the Top Investment Area for Energy Companies

Utilities have always dealt with data management, but the volume and velocity of data in a smart grid is something that they are not prepared for. Utilities do not know where to start with big data development. They have neither the requisite skills nor vision. First movers often search for help from ICT vendors, especially analytics software providers. This market insight examines the role of data management and analytics in the smart energy sector, top investment opportunities for ICT suppliers and an overview of the big data challenges. The base year for this service is 2013 and the forecast period is 2013 to 2025.

Smart Utilities—Realizing the Potential of Data

Changes in the energy sector that are gaining momentum today
• Increasing expectations of customers
• Strong pressure on cost efficiency
• Development of renewable energy sources and on-site generation
• Concerns about reliable energy supplies and grid limitations

Emergence of a new set of business needs, driven by changes in the energy landscape
• Process and cost optimisation
• Adjusting the grid to cater for the increasing share of renewable energy sources
• Delivering better services and higher satisfaction to customers

Investigation of available technologies to meet new business needs
• Deployment of sensing and metering equipment for better insight into utilities’ assets, processes and customers
• Research on data use cases and data management system architecture

Shift in utilities business models
• Advanced data management systems to become a core element of decision making processes
• Focus on analytics to provide faster return on investment
• Adoption of new pricing models for data management cost reduction

Emergence of Data-driven Utilities

Advanced Analytics and Forecasting
2020–2025: Commercial use of big data analytics and visualization
• Flexible intelligence for synchronization and analysis of big data spread across separate systems
=> Emergence of data-driven utilities

New Sources of Data Large in Volume
2015–2020: Slow adoption of big data:
• Collection, processing and storage of smart meter data for billing, reporting and settlement on a commercial scale
• Steady leverage of new big data sources and clarification of use cases
=> Data-based business model transformation

Simple Reporting Tools
2013–2015: Simple business intelligence (BI) and traditional data management tools
• Big data pilot projects run only by the most innovative utilities and organisations
• Most pilot projects focused on smart metering
=> Traditional approach to data and data management

Market Trends in the Energy Sector

More Demanding Customers
Price is still an important factor for choosing an energy supplier. However, it is slowly being overtaken by service quality in terms of importance. Customers, both industry and residential, want to be served better and expect high quality energy supply. To improve their services, utilities need to know their clients better. They will have to gain insight into their consumption patterns and incorporate new data sources like social media and other web content into their customer relationship management (CRM) systems.

Drive towards Higher Cost Efficiency
Utilities are under rising pressure to improve the efficiency of day-to-day operations and minimise cost. To optimise their business, they first need to gain more insight into their resources and day-to-day processes. Also, they will have to put this newly acquired information into the context in which they operate.

Changes in the Generation Mix
The share of renewable energy is on increase. However, the energy system is not prepared for integration of new generating units the deliver volatile output. Without detailed forecasts of production and possibility of production capacity management, renewables may negatively affect stability of the energy system.

Key Takeaway: Utilities need more insight into their business, which will not be achieved unless utilities integrate new data sources and data-based decision making models.

Concerns about Energy System Capacity
Energy infrastructure gradually deteriorates leading to poor services and high energy loses. Much of the production capacity is obsolete. Energy companies responsible for grid balancing are searching for new ways of matching supply and demand. More and more utilities decide to try out demand side measures. To offer commercial-scale demand side programmes to customers, they need detailed information on forecasted demand and available reduction potential.

Emergence of Smart Grid
Utilities are deploying some elements of intelligent energy networks. Smart grid involves changes in consumption metering and obligatory deployment of smart meters. Deployment of sensing and metering devices will enable access to new data and trigger adata explosion, creating new opportunities for energy market participants.

Table Of Contents

Data-driven Utilities
Table of Contents

1. Executive Summary
2. Data-driven Transformation of the Energy Sector
3. Stage I—Traditional Approach to Data Management
4. Stage II—Business Model Transformation
5. Stage III—Data-driven Utilities
6. Conclusions
7. The Frost and Sullivan Story

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