This document discusses how utilities can transform big data into smart data to realize business value. It defines big data and provides examples of large amounts of data being generated. The document outlines how utilities can leverage big data and analytics to improve grid operations, asset and workforce management, and smart metering. This enables benefits like increased customer intimacy, more relevant insights, and competitive advantages. It provides examples of business issues utilities may want to address and presents an approach to answering business questions by selecting and building intelligent solutions.

1. Big Data.
Smart Data.Transform Big Data into Smart Data
for realizing business value in the energy and
utilities sector
Sogeti Energy & Utilities

2. |
Introduction
Big Data for Energy & Utilities 2
Marc Govers
Management Consultant
marc.govers@sogeti.nl
Sogeti Energy & Utilities
energy-utilities@sogeti.nl

3. |
Introduction
Big Data for Energy & Utilities 3
Sogeti helps organizations to design, realise, implement, test and maintain
valuable ICT solutions
 ICT service provider since ’70
 Global reach - Local touch
 Global >20.000 employees
 Netherlands > 2.700 employees

4. |
Big Data + Small Data = Smart Data
of utilities gather valuable data
from sources other than smart
meters.
Significant potential is available
to harness data to IMPROVE
Grid performance
Customer service
Realize Business Value
Utilities should be looking
beyond smart meter data
Big Data for Energy & Utilities 4
95%

5. |
What is Big Data?
5Big Data for Energy & Utilities
76 million
smart meters
in 2009…
200m by 2014
2+ billion
people on
the Web by
end 2011
100s of
millions of
GPS enabled
devices sold
annually
4.6 billion
camera
phones world
wide
30 billion
RFID tags
today (1.3B
in 2005)
12+ TBs
of tweet
data
every day
25+ TBs
of log data
every day
Many PBs
of data
every day
80%
of world’s
data is
unstructured
The 3Vs: Volume, Variety & Velocity

6. |
Why is it important?
6Big Data for Energy & Utilities
A company whose offers are 10% more effective, which is able to provide the right service at
the right time 10% better and its supply network 10% cheaper, is the company that will be
around tomorrow.
Smart Meters and Grid
Vast volumes of data will be generated. Getting
insights to optimize the grid, provide customer energy
advice and offers will need Big Data processing
Understanding the customer
Through social media, how they navigate on web pages,
telecoms usage… gives a step change in understanding
and tailoring offers for/retention of the customer
Internet of things
Equipment everywhere is getting real-time remote
monitoring. (>4bn connected IPs). Analyzing this data give
opportunities for preventative maintenance and proactive
system response
Planes, boats and trains
Now provide continuous telemetry data – allows
performance to be optimized, risks are identified early
and support is more effective
Extended Supply Chain
RFID allows a whole new level of supply chain
monitoring and optimization
Risk Mitigation
Understanding systems and processes better and
customer sentiment early can radically reduce risk
Business Performance
Understanding market perception of your company and
products from call center voice and social media
sources, detailed analysis of operations from machine
sensor data and competitor analysis from market data

7. |
Big Data Business Challenge
7Big Data for Energy & Utilities
Grid Operations
Big Data & analytics
drives real value from
grid operations
 MV & LV Grid Planning
 System Control
 Asset Management
 Voltage Regulation &
Protection
 Customer Operations
 Field Services
 Regulatory Reporting
Asset & Work Force
Management
Asset & workforce
Management drives real
business value of utilities
 Operate the Assets
 Maintain the Assets
 Schedule Use of the
Assets
Smart Metering
Big Data & analytics
drives real value from
smart meter data
 MV & LV Grid Planning
 Grid Operations
 Field Service
 Resource Planning
 Customer Service/
Customer Operations
 Regulatory
Compliance

8. |
Business value - Customer intimacy
Big Data for Energy & Utilities 8
 Less churn and more customer loyalty
 Individual advice towards clients
 Better customer focus

9. |
Business value - Relevant insights
Big Data for Energy & Utilities 9
 Improved BI
 Trends analysis
 Improved decision making
 New products and services

10. |
Business value - Competitive edge
Big Data for Energy & Utilities 10
 Enlarge your marketshare
 Celebrate results

11. |
UTILITY INDUSTRY (GENERATION, TRANSMISSION, DISTRIBUTION, SALES)
Key Business
Processes
Smart Grid
T&D System
Planning
Outage
Management
Asset
Management
Efficiency
Improvement
Reliability
Improvement
Customer
Management
Demand
Management
Participation
Most Beneficial
Rate Analysis
Energy Efficiency
Program
Subscription
Renewable Energy
Subscription
Customer
Communication
Revenue
and Cost
Management
Revenue
Protection
Meter to Cash
Revenue
Enhancement
Revenue
Assurance
Credit Risk
Reduction
Receivables
Management
Operations
Management
Condition Based
Maintenance
Wholesale Market
Analysis
Fuels
Management
Environmental
and Safety
Management
Supply Chain
Management
Finance &
Performance
Management
Rate Plan Design
Profitability
Analysis
Rate Case Analysis
and Support
Budgeting and
Reporting
Real Time
Pricing
Data
Management
Data Mart
Consolidation
Enterprise Data
Warehouse
Roadmap
Master Data
Management
Utility Logical
Data Model
Data Quality
Improvement
Data Information Insight Intelligence
Areas for data and analytics
11Big Data for Energy & Utilities

12. |
AMI System - Data Exchanges
Big Data for Energy & Utilities 12
Meter Data
Management
System
Meter
Inventory
System
Demand
Response
System
CIS
Outage
Management
System
Data
Warehouses
Online
Presentment
 Billing related demand response
 Meter-related events needing service orders
 Meter reads and billing determinants
 Requests for meter reads
 Premise and account updates
 New meters in inventory
 Meter configuration changes
 Outage alerts
 Meter status requests
 Near real-time usage,
by customer
 Event initiation
notifications
 Reads, events, etc., etc. Customer energy history
 On-demand meter
status and reads
 Meter reads
 Meter events and alerts
 On-demand meter status
Meter
Head-End
System

13. |
AMI quantitative cost benefit analysis
13Big Data for Energy & Utilities
Process/Function
Benchmark Cost Savings/Cost
Avoidance
Benefits Apply To
Billing and Customer Service
Automation of On/Offs
High bill complaint investigations
2-7 % Field customer service costs
Metering
Field Meter Reading
2-4 % Field meter reading costs
Collections
Non-payment and theft prevention
15-25 % Non-collectible expense
Settlement
Retail and wholesale reconciliation
2-4 % Loss/unaccounted retail revenue
Demand Management
Peak demand reduction/shift
2-22 % Marginal peak capacity costs
System Control
System Automation
Power quality management
4-11 %
System line loss and associated energy
costs
Outage Restoration
Trouble response and restoration
3-8 % Trouble field labor

14. |
Approach & Method
We have developed an approach to Big Data,
associated methods and delivery capabilities.
14Big Data for Energy & Utilities
Journey to Business Improvement
Acquisition
Data Collection
Marshalling
Data organization
Analysis
Finding insights
Predictive
modelling
Action
Contributing to
business outcomes
Data Governance
Managing
integration of
data sources
Data
Integration
Business,
Functional
and Technical
Architecture
Dealing with
new customer
data sources
Privacy &
Security
M2M, ERP
injection,
dialog with
suppliers...
Action
Models that
deliver
business value
Analytics
Value
Be sure the first
project step
will be a
success !
First use
Master data,
governance &
data quality
Data
Integrity
Structured,
non structured
modelling...
Data Storing
Data Governance
Design to
implementation
to benefits: Key
considerations
Approach to Big
Data and
Leveraging it for
business
improvement

15. |
How to answer your business questions?
15Big Data for Energy & Utilities
Business
issue
Start
roadmap
Selection
Delivery
Operation
Changes/
Fixes*
Business
impact
Project Maintenance
Intelligent Solution Build
►Business drivers
►Business requirements
►ROI and next steps
►Solution, approach, budget

16. |
Business issue
16Big Data for Energy & Utilities
Asset Management
 Which assets are under performing?
Outage Management & Distribution Optimization
 How long were my customers out of power? When were
my customers restored?
Demand Response
 How do I evaluate demand response and energy
efficiency strategies for my company?
Customer Analytics
 As a customer, can I track how my usage profile
compares to people in my region with a similar profile?
Revenue Management/Meter to Cash
 Who will be my most undependable customers for
payment?
Theft/Fraud Analytics
 How do I detect fraud/theft of power based on usage/
consumption analysis and identify lost revenue?
Head End Analytics
 How do I diagnose and analyze potential Faults and
Tampers and do the trend analysis for Head end Systems
based on alerts from MDMS Data?
Project Beheer
Intelligent Solution Build
Business
issue*

17. |
And in summary…
17Big Data for Energy & Utilities
BIG DATA + ANALYTICS =
Enhanced customer
experience
Reliable Network
Safety & Security
Agile business
Satisfied employee
Business
Initiatives
The right
approach
Business
Strategy
Technology
Customer
participation
Capability

18. Big Data.
Smart Data.
More info:
energy-utilities@sogeti.nl