Product Code: IT002-000272
We first wrote about analytics in our 2010 report BI and Analytics: Making the Smart Utility Intelligent. In the three years since, some utilities have started to make the transition toward becoming an analytical utility. This report is based on interviews with several utilities and their partners.
- The road to becoming an analytical utility is not easy. Legacy architectures were not designed with cross-disciplinary collaboration in mind, which leads to problems with data quality.
- Siloed applications and data are just the start of utilities' problems, and one of the biggest challenges they face is purely cultural: utility employees sit in organizational silos, and breaking down these barriers can be utilities' toughest task.
- Analyzes the maturity of analytics in the utilities industry.
- Assesses the many barriers to creating an analytical utility.
- Provides strong recommendations to utilities seeking to implement enterprise-wide analytics.
- How mature are analytics in the utilities industry?
- What are the barriers to creating an analytical utility?
About Ovum, Ltd.
Table of Contents
- Ovum view
- Key messages
- INDUSTRY PRESSURES DRIVE THE NEED FOR CONVERGENCE
- The industry faces unprecedented pressure
- Regulators and governments up the ante
- Regulators focus on improving customer service
- Government policies to reduce carbon emissions rely on renewables
- Utilities must protect existing revenues, build new revenue streams,
and invest their capex wisely
- Rising energy prices and make customers more demanding
- Smart technologies help address these issues, but create problems of
- There is a need for better analytics across the utility value chain
- Retail businesses must use analytics to protect and grow revenues, and
improve the customer experience
- Revenue protection is vital in the economic climate
- Revenue growth will be achieved through unregulated services
- Network operators must manage far more dynamic low-voltage networks
- Energy trading departments rely heavily on analytics
- Generation relies on analytics to optimize portfolios
- While data volumes are big, this is not Big Data
- THERE ARE HUGE BARRIERS TO ENTERPRISE-WIDE ANALYTICS
- Legacy architectures do not support enterprise-wide analytics
- Cultural barriers are significant
- Utilities lack analytical skills
- Regulations place constraints on what is possible
- The economic case is hard to make
- Nascent technology increases risk in analytics procurement
- UTILITIES MUST CREATE THE RIGHT ENVIRONMENT TO INNOVATE
- Hadoop is pure hype
- Your technology architecture must support analytics
- Democratize your data
- Strong project governance breaks down cultural barriers to foster
- Project teams require the most experienced project managers
- Build a strong business case that includes quick wins
- Cloud-based analytics and sandboxing can reduce initial capital costs
- Share the incredible value of customer data with the customer
- Analytics-as-a-service can address skills shortfalls, if data can be
- Data strategy must be addressed early
- Data quality relies on long-term change management
- Further reading
- Ovum Consulting
- Figure 1: European wind capacity installations (MW), 2010-12
- Figure 2: Domestic electricity prices (pence/kWh), 2008-2011
- Figure 3: Utilities' involvement in smart grid projects, 2012
- Figure 4: Utilities' storage requirements, 2012-2017
- Figure 5: Analytics use cases across the utility value chain
- Figure 6: The flow of power in a decentralized power generation model
- Figure 7: Locations and communication networks used by utilities to creata