1. Utilities and Big Data: Accelerating the Drive to Value
July 22, 2013
Last year’s title: Big Data, Bigger Opportunities: Plans and Preparedness for the Data Deluge

2. Contents Introduction 3 Methodology 4 Executive Summary 5 Findings 6
Our Take
Contents

3. Introduction
Oracle’s “Utilities and Big Data” study is the second annual in a series examining how North American electrical utilities are using increasing volumes of smart grid data.
The 2013 “Utilities and Big Data” study picks up where the 2012 “Big Data: Bigger Opportunities” study left off: examining how utilities are using data to improve operations and the customer experience. Today, more utilities say they are completely prepared to deal with the big data influx, but most still grapple to manage, analyze and fully leverage the information.
The “Utilities and Big Data” study explores:
Preparedness to handle the big data influx
How data is being used to improve operations and customer service
Future short- and long-term plans to use smart grid data
The potential of cloud-based solutions for data management and analysis
Where utilities will derive the greatest value from predictive analytics
The resulting report is based on the views of more than 150 North American senior-level electrical utility executives surveyed by Oracle.

4. Current Smart Meter Status
Methodology
Oracle conducted telephone interviews with 151 North American senior-level electrical utility executives in April and May The sample consists of 136 U.S. and 15 Canadian responses1
Current Smart Meter Status
29% Completed a pilot program
24% Completed a partial rollout
47% Completed a full rollout to all customers/service points
1This report has a margin of error of ±7.95% at a 95% confidence level
(NOT for external distribution)
2013 Survey: Utility Size by Number of End-User Metered Customers
15% Fewer than 100,000 customers
43% 100,000 to 499,999 customers
15% 500,000 to 999,999 customers
27% One million customers or more
2012 report smart meter status question:
Has your utility implemented at least one smart metering pilot program?
Yes
No (terminate)
Unsure (terminate)

5. Executive Summary The Good News: The Opportunity:
Utilities are making some progress in preparing for the smart grid data influx. More utilities say they are completely prepared this year compared to one year ago.
Utilities are accessing valuable data from a variety of sources in addition to smart meters, including outage management systems, supervisory control and data acquisition (SCADA) history and customer data and feedback.
The Opportunity:
While utilities are using more data today, significant opportunity remains to harness data to improve grid performance and customer service. Less than half of utilities are using smart grid data to improve customer service today.
Predictive analytics can help utilities boost the bottom line. Seventy percent of utilities said they expect predictive analytics to improve revenue protection, and 61 percent said they expect it to reduce asset maintenance costs.
Most utilities lack sufficient data analytics expertise. Recruiting, training, and third-party solutions can help close the skills gap.
More than 80 percent of utilities see potential benefits in cloud-based solutions. More than a quarter (26%) of utilities are either planning, implementing or maintaining cloud-based solutions for data management and analysis. Another 38% are in the initial discovery phase.
More than 80 percent of utilities see potential benefits in cloud-based solutions: This statistic comes from the question, “What do you see as the most significant benefits to implementing a cloud-based solution for managing smart grid/smart meter data?”  More than 80% of respondents indicated they saw some benefit to cloud-based solutions.  The other two stats in the cloud computing bullet point above are from the question, “What is your utility's status regarding cloud-based solutions for smart grid/smart meter data management and analysis?”

6. Utilities Are Improving, but Underprepared
While almost twice as many utilities say they are completely prepared for smart grid data today vs. one year ago, the majority still say they are underprepared. Utilities report slight improvements in information sharing and strategic decision making
How would you grade your utility’s preparedness to manage the smart grid/smart meter data influx?
Percentage who said completely prepared:1
2012 – 9%
2013 – 17%
How effective is your utility in handling the data influx?
Percentage doing an excellent job:1
2012
2013
Putting timely information into the hands of people who need it most 8%
20%
Making strategic decisions based on the information 4%
11%
Make Sure Strategic Decisions are Made on Data
UTILITIES T
AKE AWAY
1Those who rated their utility a 10 on a scale of 1 to 10, where 1 was very poor and 10 was excellent
How would you grade your utility’s preparedness to manage the smart grid/smart meter data influx? Please rank on a scale of 1 to 10, where 1 is not at all prepared and 10 is completely prepared.
On a scale of 1-10, where 1 is very poor and 10 is excellent, how would you rate your utility’s effectiveness in handling the data influx in the following areas: [Matrix format with 1-10 and N/A for each]
Putting timely information into the hands of people who need it most
Translating information into actionable intelligence
Reporting on information
Making strategic decisions based on the information
Delivering useful information to our customers
Ensuring storage capacity
Securing/safeguarding data
Finding/hiring the right talent to help analyze our data
Visualizing data (showing data on a spatial map)
Note for internal review: After reviewing the data by utility size, we are confident that the year-over-year changes displayed on this slide are not due to the change in sample composition.
Results by utility size are as follows:
How would you grade your utility’s preparedness to manage the smart grid/ smart meter data influx?
Percentage who said completely prepared:1
Less than 100K = 22%
K = 9%
K= 18%
1mil+= 24%
How effective is your utility in handling the data influx?
Putting timely information into the hands of people who need it most:
Less than 100K = 26%
K = 12%
K= 27%
1mil+= 22%
Making strategic decisions based on the information:
Less than 100K = 13%
K = 6%
K= 14%
1mil+= 12%

7. Multiple Data Flows Contribute to the Influx
95% of utilities gather valuable data from sources other than smart meters. They have significant potential to harness data to improve grid performance and customer service
In addition to smart meters, which of the following data sources provide the most valuable information to your organization?1
64%
58%
54%
12%
11%
Outage management systems
SCADA2 history
Customer data and feedback
Alternative energy sources
Social media
Weather–monitoring systems
Wholesale market data
Other smart grid points
Leverage Data from Reliability and Customer Services Areas of Business
TAKE AWAY
1Respondents asked to name their top three additional data sources 2 Supervisory control and data acquisition
In addition to smart meters, which of the following data sources provide the most valuable information to your organization? Please select the three most important sources.
Other smart grid points such as smart appliances, in-home portals, or electric vehicles
Supervisory control and data acquisition (SCADA) history, including advanced sensors, controls, and grid-healing elements
Alternative energy sources
Outage and distribution management systems
Weather-monitoring systems
Energy traders/wholesale market data
Customer data and feedback
Social media
There are no other significant data sources
Other, please specify:
Unsure
Full rollout Partial rollout Pilot
Outage management systems 68% 61% 60%
SCADA history 52% 67% 62%
Customer data and feedback  48% 64% 57%
Alternative energy sources 15% 17% 5%
Social media 16% 6% 10%
Weather-monitoring systems 13% 6% 12%
Other smart grid points 10% 17% 7%
Energy traders/wholesale market data 7% 17% 12%
Overall usage stats:
Outage management systems = 64%
SCADA = 58%
Customer data = 54%
Alternative energy sources = 12%
Social media = 11%
Weather-monitoring systems = 11%
Other smart grid points = 11%
Energy traders / wholesale market data = 11%

8. Utilities Are Taking Advantage of Data
Utilities are using more information today than one year ago.1 Utilities that are not using data from multiple sources can look to their peers for best practices 2
Data Being Used
Year-Over-Year Data Shows Wider Adoption, but Additional Improvements are Possible
TAKE AWAY
1Year-over-year changes are not statistically significant 2 Power quality data response option was not used in 2012 survey
Of the smart grid data your utility collects, which of the following are you actively using to support business processes and decision making? Please select all that apply.
Interval data
Tamper events
Voltage (including high/low voltage alarms)
Outage
Diagnostic flags
Power quality data (including flicker and harmonics)
[Other responses from Q2: Other, please specify]
Unsure

9. Employ Data to Drive Greater Customer Value
Fewer than half of utilities today use smart grid data to provide alerts or make other direct customer service improvements
How are utilities leveraging smart grid data to improve customer service today?1
The average utility has taken just two of these steps.
Use Data to Enhance Program Design for Customers to Ensure higher adoption
TAKE AWAY
1Respondents asked to select all that apply
Which of the following steps, if any, does your utility plan to take in the next five years to leverage smart grid data to improve customer service? For each, please indicate if you have already taken the step, plan to within the next year, plan to in 1-2 years, plan to in 2-3 years, plan to in 3-4 years, plan to in 4-5 years, plan to in more than five years, or if you do not plan to take the step.
Use predictive analytics to minimize outages or improve service delivery quality/power reliability
Implement demand-response programs
Establish new pricing programs (i.e., time variable pricing)
Provide customers with information about their usage patterns
Alert customers of usage spikes
Target customers for new programs (i.e., implementing renewable energy sources)
Compare historical data to identify trends and forecast demand
Improve compatibility with regulatory requirements
Implement and/or improve conservation and efficiency programs

10. Reliability Improves with Data Analytics
Currently, just half of utilities are fully leveraging smart grid data to improve customer service through forecasting, demand management and improved reliability
How are utilities leveraging smart grid data to improve customer service today?1
The average utility has taken just two of these steps.
Incorporate Predictive Analytics Capabilities in Overall Reporting Strategies
TAKE AWAY
Which of the following steps, if any, does your utility plan to take in the next five years to leverage smart grid data to improve customer service? For each, please indicate if you have already taken the step, plan to within the next year, plan to in 1-2 years, plan to in 2-3 years, plan to in 3-4 years, plan to in 4-5 years, plan to in more than five years, or if you do not plan to take the step.
Use predictive analytics to minimize outages or improve service delivery quality/power reliability
Implement demand-response programs
Establish new pricing programs (i.e., time variable pricing)
Provide customers with information about their usage patterns
Alert customers of usage spikes
Target customers for new programs (i.e., implementing renewable energy sources)
Compare historical data to identify trends and forecast demand
Improve compatibility with regulatory requirements
Implement and/or improve conservation and efficiency programs
1Respondents asked to select all that apply

11. Percentage who gave themselves an “A” in the following measures:1
Data Analysis is Key to Operational Transformation
Utilities grapple with each step of the data review and reporting cycle, especially extracting data value
Percentage who gave themselves an “A” in the following measures:1
No difference since last year = Must Take Data to the Next Level
TAKE AWAY
!Those who gave themselves a 9 or 10 on a scale of 1 to 10, where 1 was very poor and 10 was excellent
On a scale of 1-10, where 1 is very poor and 10 is excellent, how would you rate your utility’s effectiveness in handling the data influx in the following areas: [Matrix format with 1-10 and N/A for each].
Putting timely information into the hands of people who need it most
Translating information into actionable intelligence
Reporting on information
Making strategic decisions based on the information
Delivering useful information to our customers
Ensuring storage capacity
Securing/safeguarding data
Finding/hiring the right talent to help analyze our data
Visualizing data (showing data on a spatial map)

12. Percentage who gave themselves an “A” in the following measures:1
Data Analysis is Key to Operational Transformation
Utilities grapple with each step of the data review and reporting cycle, especially extracting data value
Percentage who gave themselves an “A” in the following measures:1 2 2
Utilities Must Take Their Data to the Next Level with Analytics
TAKE AWAY
!Those who gave themselves a 9 or 10 on a scale of 1 to 10, where 1 was very poor and 10 was excellent; 2 Did not ask in 2012
On a scale of 1-10, where 1 is very poor and 10 is excellent, how would you rate your utility’s effectiveness in handling the data influx in the following areas: [Matrix format with 1-10 and N/A for each].
Putting timely information into the hands of people who need it most
Translating information into actionable intelligence
Reporting on information
Making strategic decisions based on the information
Delivering useful information to our customers
Ensuring storage capacity
Securing/safeguarding data
Finding/hiring the right talent to help analyze our data
Visualizing data (showing data on a spatial map)

13. Necessary Expertise is in Short Supply
Fewer than one in three utilities say they have sufficient expertise around smart grid data analytics or data science
Do you believe your utility has a skills gap around smart grid data analytics or data science?
62% Yes   
31% No
7% Unsure
Utilities in all phases of smart meter rollouts are equally likely to have a data analytics skills gap
Additionally, 58% of respondents who gave themselves a 9 or 10 in overall preparedness see a skills gap
Have an action plan to Train Staff and Supplement Them With Data Analytics Solutions and Services
TAKE AWAY
Do you believe your utility has a skills gap around smart grid data analytics or data science?
Yes No

14. Skills Gap Requires Internal, External Remedies
To address the skills gap, utilities are combining training and hiring with packaged solutions and third parties
Those with a gap:
Which of the following steps is your utility taking to address this skills gap?1
Those that have closed the gap:
Which of the following steps did your utility take to eliminate or avoid this skills gap?1
Training our current employees
Hiring/building our internal capability
Investing in pre-packaged analytics solutions
Outsourcing analytics to a third party
Training our current employees
Hiring/building our internal capability
Investing in pre-packaged analytics solutions
Outsourcing analytics to a third party 
Close the Skills Gap Through Recruitment, Training and Third-Party Solutions
TAKE AWAY
1Respondents asked to select all that apply
Which of the following steps is your utility taking to address this skills gap? Please select all that apply.
Building our internal capability (i.e., hiring from schools and/or industry)
Training our current employees
Investing in pre-packaged analytics solutions
Outsourcing analytics to a third party (analytics as a service)
We are not taking any steps
Other, please specify:
Which of the following steps did your organization take to eliminate or avoid this skills gap? Please select all that apply.
Built our internal capability (i.e., hired from schools and/or industry)
Trained our current employees
Invested in pre-packaged analytics solutions
Outsourced analytics to a third party (analytics as a service)
We did not take any steps

15. Many See Potential in Cloud-Based Solutions
Two out of three utilities are considering cloud-based solutions for smart grid/smart meter data management and analysis
Those planning, implementing or maintaining: What do you expect to see as the top benefits of your cloud-based solution?1 #1 #2 #3 #4 #5
What is your utility’s status regarding cloud- based solutions for smart grid/smart meter data management and analysis?
38% Discovery
7% Planning
11% Implementing
8% Maintaining
36% None of the above – we are not currently considering cloud-based solutions
Improved speed of service and
application deployment (44%)
Improved information security (38%)
Increased flexibility/scalability to handle peak
computing needs on demand (34%)
Improved data storage capabilities/capacity (31%)
Reduced IT capital expenditure (28%)
Guerry needs to edit - Cloud offers the opportunity to collaborate; Leverage the Cloud for Growing Data Management and Analysis Needs
TAKE AWAY
1Respondents asked to select all that apply
What is your utility’s status regarding cloud-based solutions for smart grid/smart meter data management and analysis? Please select one.
Discovery – we are learning about cloud-based solutions and how they can work for our utility
Planning – we are preparing a business case and/or strategic plan for cloud-based solutions
Implementing – we are currently in the process of adopting at least one cloud-based solution
Maintaining – we have fully implemented at least one cloud-based solution
None of the above – we are not currently considering cloud-based solutions
Unsure
What do you see as the most significant benefits to implementing a cloud-based solution for managing smart grid/smart meter data? Please select up to three benefits.
Reduced IT operating expenses
Reduced IT capital requirements
Improved speed of service and application deployment
Automatic software upgrades
“Anywhere access” to documents and applications
Improved information security
Improved data storage capabilities/capacity
Flexibility/scalability to handle peak computing needs on demand
Do not see any benefits
Other, please specify:

16. Predictive Analytics Can Boost the Bottom Line
Utilities expect smart grid rollout and the corresponding implementation of predictive analytics to improve revenue protection and reduce asset maintenance costs
In what utility processes do you expect to achieve the greatest value from predictive analytics?1
Improving revenue protection Reducing asset maintenance costs
Reducing asset replacement costs Reducing infrastructure costs Analyzing distributed generation Reducing generation planning costs Reducing generation operations costs Assessing electric vehicle impact
70%
61%
57%
54%
50%
41%
39%
26%
You now have the ability to see into the future are you structured to be a data- driven buisness?Improve Operations, Investment Planning with Predictive Analytics
TAKE AWAY
1Respondents asked to select all that apply
With the expected growth in predictive analytics associated with combined mash-ups of meter, SCADA, field sensors (i.e., dissolved gas analysis, line monitors, fault indicators), network connectivity, operations/reliability, weather, and economic data; in what utility processes do you expect to achieve the greatest value from predictive analytics?  Please select all that apply.
Asset risk analysis – reducing asset maintenance costs
Asset risk analysis – reducing asset replacement costs
Asset risk analysis – improving asset performance and reliability
Spatial load and renewables forecasting for transmission & distribution network planning – reducing capital infrastructure costs
Long-range forecasting for generation planning – reducing generation planning costs
Short-term forecasting for generation operations – reducing generation operations costs
Distributed generation impact analysis
Electric vehicle impact on load and infrastructure

17. Positive ROI Anticipated from Analytics
More than half expect positive ROI within five years. Still, 22 percent are unsure.
How long do you think it will take your utility to realize a positive return on its smart grid analytics investment?
Re-examine analytics efforts to drive value quickly
TAKE AWAY
Given the benefits associated with smart metering and smart grid analytics, how long do you think it will take your utility to realize a positive return on investment?
Within the year
1-3 years
3-5 years
5-10 years
More than 10 years
Unsure

18. Utilities Plot Short- and Long-Term Gains
Smart grid infrastructure and data will enable more reliable energy, more intelligent usage information and custom pricing programs
The average utility with more than one million customers will invest approximately $180 million in the smart grid and smart metering over the next five years
Short Term: Utilities’ top three smart grid data plans for the next 1-2 years:
Long Term: Utilities’ top three smart gird data plans for the next 3+ years: #1 #2 #3
Compare historical data to identify trends
and forecast demand
Provide customers with information about
their usage patterns
Use predictive analytics to minimize outages
or improve service delivery and reliability #1 #2 #3
Alert customers of usage spikes
Establish new pricing programs (e.g., time variable pricing)
Use predictive analytics to minimize outages
or improve service delivery and reliability
Use Data Analytics to Better Manage Distribution Networks Stretched by Demand
TAKE AWAY
Which of the following steps, if any, does your utility plan to take in the next five years to leverage smart grid data to improve customer service? For each, please indicate if you have already taken the step, plan to within the next year, plan to in 1-2 years, plan to in 2-3 years, plan to in 3-4 years, plan to in 4-5 years, plan to in more than five years, or if you do not plan to take the step.
Use predictive analytics to minimize outages or improve service delivery quality/power reliability
Implement demand-response programs
Establish new pricing programs (i.e., time variable pricing)
Provide customers with information about their usage patterns
Alert customers of usage spikes
Target customers for new programs (i.e., implementing renewable energy sources)
Compare historical data to identify trends and forecast demand
Improve compatibility with regulatory requirements
Implement and/or improve conservation and efficiency programs

19. Our Take …
We’re Not Done with Smart Grid Yet: Most utilities still are not using their data as efficiently as possible. Make strategic plans and get on board. The time is now.
Enhance Customer Value through Data: Utilities should expand efforts to use smart meter and smart grid data to improve customer service and the customer experience. They should seize opportunities to make direct improvements today and, to build lasting relationships, ask customers what information would be helpful in the future
Use Data in Combination: Utilities are collecting data from multiple sources. Using that data in combination will deliver greater opportunities to improve smart grid performance and customer service
Leverage the Right Talent: Fewer than one in three utilities have sufficient expertise in smart grid data or general data science today. A three-pronged approach will help close the gap: recruitment, training and third-party solutions
Consider the Cloud: Cloud-based solutions can improve the speed, security, and scalability of data management systems. As data volumes grow, so will the need for cloud-based solutions for data management and analysis

20. For media inquiries, please contact:
Caroline Vespi
Oracle
Gail Repsher Emery
O’Keeffe & Company