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UTILITIES
BIG DAT A & ANAL YTICS
10 W ays UK U tility Fi rm s
Can B oost Opera tional Value
OCTOBER 2015
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As more tools surface for capturing and analysing data, new designstrategies to improve processes and generate transformational change
for their businesses are being increasingly seen in the energy and utility
sector. Inefficiencies in the industry encompass a plethora of wasted
energy each year. Advanced technology, such as big data, analytics
and smart metering can help UK utility companies to eliminate this
waste and improve customer experience to gain full control of their
resources.
The UK utility and energy market is characterised by high levels of
churn and a 38% average switching rate with domestic consumers
changing electricity or gas supplier every week. With the advent of
Smart Grid too, the levels of data collection are dramatically increasing
which is opening up huge opportunities for utilities to exploit. The big
question though, is how do utility companies leverage the hugevolumes of datasets to create value for their businesses?
Ahead of the Big Data & Analytics Utilities event in London (06 – 08
October, 2015), we bring you ten quick ways utility organisations are
improving their operations, uncovering monetisation opportunities and
understanding customers better across their value chains.
Jason McGee-Abe
Editor, PEX Network
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1
MANAGING CHURN USING CUSTOMER INSIGHT
Creating a dedicated analytics function to focus on key areas
including customer segmentation, churn assessment, probability
modelling and product placement modelling helps to address this.
The Customer Insight team of EDF Energy (part of EDF Group), one
of Europe’s largest power companies, is using a Statistical Analysis
System (SAS) to deliver strategic analysis of data and gain new
insight into factors that motivate and drive customer behaviour. “Wecan meet customers’ needs better by learning more about how they
think, what they buy, what they use and how they want to interact
with their supplier,” says Clifford Budge, Customer Insight Manager,
B2C Energy Sourcing and Customer Supply (ESCS), EDF Energy.
2
DATA MINING AND PREDICTIVE MODELING
Using analytics to forecast the impacts of weather helps to
streamline utilities’ processes. For example, Yorkshire Water, a
water supplier and waste management firm which supplies around
1.4 billion litres of water each day, has been using analytics to
forecast flooding and pollution in its network of 62,000 miles of
water and sewage mains. These systems enable water engineers to
predict when damaging pollution may occur in sewer overflow. Datamining tools forecast the overflow sites likely to develop blockages,
helping operators to better target engineer visits.
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3
ALIGNING AND INTEGRATING FUNCTIONS
Jan Staack, Lead Enterprise Architect at DONG Energy says that
data helps to closer align and integrate IT and Business Functions.
DONG Energy is collaboratively working in collaboration to manage
a high energy demand by using data insight and forecasting
analytics to pro-actively manage resources and maintain a
consistent supply. Higher quality of data collected supports business
cases for strategic change within an organisation and helps to buildmore robust data architectural designs and foundations for
continuous improvement. DONG Energy also has a mobile solution
that supports the workforce management and tasks in connection
with maintenance of the electrical distribution network.
4
GREEN ENERGY POWER
Danish energy firm, Vestas Wind Systems, has adopted Big Data to
define and establish preferred sites for smarter wind energy. Vestas,
which produces 20% of the world’s wind energy, is addressing the
issue of turbine placement by analysing petabytes of structured and
unstructured data such as weather reports, tidal phases, geospatial
and sensor data, and weather modelling research to pinpoint the
optimum locations to install new wind turbines. By using Big Datatechnology, the analysis for pinpointing new optimum locations can
now be done in less than one hour; a job that used to take weeks. It
also assists with determining the best times to schedule
maintenance of the turbines.
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5
DISTRIBUTING GRID SENSORS
Deploying distribution grid sensors and control systems, including
smart meters, is an area of focus for a number of utility companies
as they set the future foundations of data collection engines to
analyse energy demand. It enables intelligent maintenance,
minimising faults and reducing downtime and disruption, delivering
better service and better systems.The addition of grid sensors puts
pressure on utility organisations to find profitable uses for collecteddata. They can tap into other sources of data, including smart city
projects, including data on water usage and carbon emissions.
6
SMART METERS
Converting billions of data points coming from millions of smart
meters deployed around the country will enable utilities to turn them
into actionable intelligence on the operating conditions of their grids
to improve network reliability and efficiency.
Smart meter adoption varies across European companies though.
Some EU members, such as Italy and the Scandinavian countries,
have largely completed their smart meter rollouts. Others, including
France, Germany, the U.K., are just getting started. Benefits of
smart meter rollouts include being able to better estimate the state
of the grid and assess lifetime durations of distribution grid
equipment. However, there are challenges, such as embedding the
right algorithms into substations for smarter operations of the grid.
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7
SECURITY
Across the pond in the US, a Verizon report states that $6 billion of
electricity is stolen each year. Smart grid solutions can detect where
this power is being lost, plus enable remote control and automation
of grid equipment to help keep costs down.
Smart meters keep consumers informed and enable more accurate
billing and demand forecasting. This opens up the window ofopportunity for more transparency, and cost savings. In 2011, the
UK’s Department of Energy and Climate Change mapped out plans
for the installation of 53 million smart meters in 30 million homes
and businesses by 2020. Given that utility firms have typically
struggled with the accuracy of customer and billing data, mass
smart metering can address this, but it also raises concern as to
how utility companies will manage the huge volume of meter
readings.
8
INTEGRATION
European utilities have put a big emphasis on integrating utility-
scale wind and solar power, integrating on-site power generation,
and managing new sources of demand such as plug-in electric
vehicles, according to an Accenture executive survey. Unlike our US
counterparts, the survey also found that European utilities have put
much less emphasis on data analytics as a top investment category
over the next five years.
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9
MONETISATION
From a customer point of view, utilities now have a better picture on
how their products are used. This provides an opportunity to create
new revenue streams, such as advantageous smart home tariffs for
residential owners, or packages designed to promote use of spare
capacity during periods of low demand. Smart meters also allow
energy firms to make recommendations to customers designed to
help them use energy more efficiently and reduce bill shock.
Big Data and Analytics bring vast monetising opportunities, both
internal and external, for utility companies. Internally, advanced data
insight helps you to truly understand your customer from marketing
and sales points of view, tailoring bespoke products, services, or
indeed marketing campaigns based on your respective customers’
preferences. The external monetisation potential will boom as
homes become smarter and products and services are created tocoincide with customers’ behavior and habits.
10
EFFICIENT FORECASTING AND CONTINUOUS IMPROVEMENT
Through the use of big data-enabled utility management systems,
utilities can become smarter at asset and infrastructure
management. Having a system which constantly monitors andevaluates events across an organisation’s footprint will not only
identify inefficiencies, but deliver actionable scenario insights from
predictive modeling tools. Creating dashboards for data
visualisations to identify information gaps and communicate insights
enterprise-wide is helping to develop pro-active cultures.
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