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Data Driven Strategies are Transforming the Energy Sector

December 20, 2018 by Lape Runsewe

Data driven strategies are transforming the energy sector

A study this September by analytics database firm Exasol explored how energy companies are becoming more data-centric in their decision-making, but it found that surprisingly still only 17 per cent of energy companies are implementing a data-driven strategy. This is despite rising competitive threats that are providing major incentives to change. Utilities in many competitive, as well as regulated countries, are also struggling to retain customers and fend off new threats in distributed generation.

Digitising the customer experience is at the heart of effective data strategies
By digitising the customer experience and leveraging the massive benefits of resultant data flows and analytics, utilities can provide a response to many of these various threats by improving both customer satisfaction and also building a lower cost base; the latter through much greater efficiencies and dramatically improved management information. In many areas, there is also the potential to improve revenues as innovation possibilities are unleashed. In recognition of these opportunities, many more energy suppliers have been starting to invest in both online and more mobile channels, though many still lag behind regarding usability and the interface between online and the more traditional sales channels.

These days, most customers treat a multichannel platform that seamlessly connects their interactions across all channels pretty much as a norm from service providers —online, mobile, call centre, and local sales that are all integrated. For utilities, the improved customer processes, as a result, are also much more cost effective. A seamless multichannel platform is a requirement for the profitable analysis of customer behaviour through the entire customer journey.

So energy companies are starting to use advanced analytics from such platforms to enhance service quality, lower costs, and preserve and deepen customer relationships. There are some interesting examples of the changes that data-driven strategies can bring. Data quality and operating efficiencies were both significantly improved by the German energy company Uniper. They centralised their multiple pricing systems for their European-wide network of power stations onto a single, centralised energy platform, built by Digiterre. By using customer data analytics to make process improvements, one other large northern European energy supplier has been able to increase up-selling and cross-selling significantly, while simultaneously increasing usage of its digital channels. Disruptors are being even more fleet of foot with data-driven strategies: start-ups energy companies such as Thermondo in Germany (Source: McKinsey), a provider of highly customized heating solutions, have based their business model on improving various customer interaction points and so are altering business dynamics in the industry.
The convergence of multiple channels is enabling huge potential for change
With digital, mobile, cloud and analytics technologies converging more and more all the time, the potential for dramatically improved business outcomes is produced for energy players. Four particular developments are contributing to a current ‘tipping point’, unleashing many new possibilities for faster and smarter business decisions from faster and better data. These are:

  1. The convergence of information technology (IT) and operations technology (OT). Data from machines is generated, captured and integrated into IT systems for analysis, often in real time.
  2. Mobility and technology consumerisation. Mobility and user-friendly IT provide remote access to data, affording improved visibility and faster response times.
  3. Disruptive architectures, including cloud computing. The cloud provides cost-effective options to access large-scale computing and storage capability, as well as tools, all essential for analytics. Also, “on demand” is reshaping the IT operations model with the option for analytics-as-a-service.
  4. Big data analytics and in-memory computing. The application of advanced analytic techniques to very large data sets is aided by in-memory databases that greatly reduce query time.

The same survey Exasol survey we highlighted earlier also showed that, though relatively few are currently implementing such data strategies, over 71 per cent of energy companies have a strategy planned to be implemented in the next two to five years. Albeit later than many other sectors, a data storm is about to hit the energy sector!

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