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Utility Transformations: Moving the Needle

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Presentation on theme: "Utility Transformations: Moving the Needle"— Presentation transcript:

1 Utility Transformations: Moving the Needle
July 22, 2013

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

3 Introduction North American electrical utilities are using increasing volumes of smart grid data today. Some 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 “Utility Transformations: Moving the Needle” study sought to: Measure preparedness to handle the big data influx Determine how data is being used to improve utility operations and the customer experience Identify future short- and long-term plans to use smart grid data Evaluate the potential of cloud-based solutions for data management and analysis Determine 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 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 Sample Demographics Respondent Title: 3% Owner, Partner, President, CEO, or COO 3% CFO, Controller, or Treasurer 1% CIO or CTO 1% EVP or SVP 3% VP, Assistant VP, or Principal 16% Director of Customer Service 12% Director of Distribution 31% Director of Smart Grid or Smart Metering 30% General Manager or Managing Director 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 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

5 Executive Summary The Good News: The Opportunity:
Utilities are increasingly prepared for the smart grid data influx. Almost twice as many utilities say they are completely prepared this year compared to one year ago Data security is an emerging success story. Nearly three out of four (72%) utilities give themselves an “A” in their ability to secure and safeguard data Utilities are accessing valuable data from a variety of sources, including outage management systems, supervisory control and data acquisition (SCADA) history and customer data and feedback The Opportunity: While utilities are collecting and using more data today, there is room to increase the translation of information into actionable intelligence and leverage it for strategic decision making Despite increased preparedness and data usage, less than half of utilities are using smart grid data to improve customer service today. Opportunities exist to provide customers with usage pattern information and alert them to usage spikes 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

6 Utilities Are Starting to Move the Needle
Almost twice as many utilities say they are completely prepared for smart grid data today vs. one year ago. Utilities also 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% Where have utilities improved most? 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% Capitalize on Successes, Realign Processes to Drive Additional Data Value TAKE AWAY 1Those who rated their utility a 10 on a scale of 1 to 10, where 1 was very poor and 10 was excellent 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% Where have utilities improved the most? 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 Solid data policies may contribute to preparedness
Data Security Confidence Climbs Ability to safeguard data remains utilities’ most effective response to handle the data influx from smart grid/smart meter programs 72% of utilities give themselves an “A” in their ability to secure safeguard data1 (up from 61% in 2012) Additionally, three out of four feel their smart grid/smart meter data privacy policy is sufficient for protecting/securing their data. Solid data policies may contribute to preparedness Those who feel prepared for the data influx are significantly more likely to have a sufficient data privacy policy than those who say they are not prepared2 78% have policy 94% have policy Prepared Not prepared Unfortunately, more than one in 10 utilities (13%) do not have a data privacy policy in place. Security and Privacy Policies Protect and Enable TAKE AWAY 1Those who gave themselves a 9 or 10 on a scale of 1 to 10, where 1 was very poor and 10 was excellent 2Prepared = 9 or 10 rating; Unprepared = 1-6 rating 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: 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: Securing/safeguarding data Less than 100K = 70% K = 66% K= 64% 1mil+= 71%

8 Utilities Are Data Rich
95% of utilities indicated they gather valuable data from sources other than smart meters In addition to smart meters, which of the following data sources provide the most valuable information to your organization?1 Outage management systems SCADA history Customer data and feedback Alternative energy sources Data-rich Utilities Need Comprehensive Data Management Tools & Techniques TAKE AWAY 1Respondents asked to name their top three additional data sources 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/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 / market data = 11%

9 Data Ownership Often Overlaps
Utilities say a combination of metering, IT and the back office own smart grid data Metering department IT Back office 58% 47% 41% 15% 12% 17% 14% 3% 9% Who owns or is responsible for smart meter and/or smart grid data?1 58% Metering 47% IT 41% Back office/billing 37% Customer service 23% Transmission & distribution 16% Business analysts 8% Other Encourage Collaboration, but Identify a Clear Departmental Lead TAKE AWAY 1Respondents asked to select all that apply Venn Diagram Guide: Percentages in black = The percentage of all respondents that indicated a department is responsible for smart meter and/or smart grid data. Percentages in white = The percentage of all respondents that indicated a given combination of departments is responsible for smart meter data. All of the percentages in white within a given circle add up to the black percentage in black. For example, 17% indicated the metering and the IT departments are responsible for smart meter data, and 15% indicated the metering department, the IT department, and the back office are responsible for smart meter data.

10 are collecting some from of
The Usage Gap Remains While utilities collect and use more information today than one year ago, they still struggle to take full advantage of the data Data Being Used 97% 85% are collecting some from of smart grid data are using some type of smart grid data Collecting Using Close the Usage Gap with Data that Offers the Greatest Operational Impact TAKE AWAY

11 Utilities Have a Customer Service Opportunity
In many cases, fewer than half of utilities are using smart grid data to improve customer service today How are utilities leveraging smart grid data to improve customer service today?1 While 57% provide customers with information about their usage, just 26% alert customers of usage spikes Focus Efforts on Improving the Customer Experience TAKE AWAY 1Respondents asked to select all that apply Alternate Slide Title: Opportunity to Gain CX Advantage

12 Percentage who gave themselves an “A” in the following measures:1
Utilities Have an Operational Opportunity Utilities are confident in data security, but grapple with extracting data value Percentage who gave themselves an “A” in the following measures:1 While 72% feel confident in their ability to safeguard data, only a quarter feel confident in their ability to translate information into actionable intelligence (26%) or use it for strategic decision making (25%) Establish Frameworks for Consistent, Thorough Data Analysis 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 Alternate Slide Title: Opportunity to Grow Data Value

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 Prioritize Hiring and Training Staff to Manage the Data Influx TAKE AWAY

14 Nearly All are Working to Improve Talent
To address the skills gap, utilities are combining training and hiring with packaged solutions 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 (90%) Building our internal capability (60%) Investing in pre-packaged analytics solutions (45%) Outsourcing analytics to a third party (30%) Training our current employees (89%) Building our internal capability (53%) Investing in pre-packaged analytics solutions (34%) Outsourcing analytics to a third party (21%) Take a Multi-Pronged Approach to Closing the Skills Gap TAKE AWAY 1Respondents asked to select all that apply

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%) Consider the Cloud for Growing Data Management Needs TAKE AWAY 1Respondents asked to select all that apply

16 What’s in it for the Utility
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 How long do you think it will take your utility to realize a positive return on its smart grid analytics investment? 15% Within the year 17% 1 year – less than 3 years 23% 3 years – less than 5 years   18% 5 years – less than 10 years 5% More than 10 years    22% Unsure Improving revenue protection (70%) Reducing asset maintenance (61%) Reducing asset replacement  (57%) Reducing infrastructure costs (54%) Analyzing distributed generation (50%) Payoff Takes Time, but the Return Can be Substantial TAKE AWAY 1Respondents asked to select all that apply Alternative Slide Title: Predictive Analytics Offer Strong ROI Complete List 70% Improving revenue protection  61% Reducing asset maintenance 57% Reducing asset replacement   54% Reducing capital infrastructure costs 50% Analyzing and assessing distributed generation 41% Reducing generation planning costs 39% Reducing generation operations costs 26% Assessing electric vehicle impact

17 What’s in it for the Customer
Customers can expect smart grid infrastructure and data to 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 Establish Short-, Medium-, and Long-Term Goals for Leveraging Data TAKE AWAY Alternate Slide Title: Data Delivers Reliable Customer Experience

18 Our Take … Recruit the Right Talent: Fewer than one in three utilities have sufficient expertise in smart grid data or general data science today. Finding and hiring the right talent is key to leveraging the power of the smart grid 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 Prioritize Data Security and Privacy: Thorough security and privacy policies protect the customer and the utility – and prepare utilities to make the best use of smart grid data Clarify Data Ownership: Smart metering and smart grid data is often housed or managed by multiple departments. Utilities must ensure they have an enterprise-level data strategy in place that is clearly understood and adhered to within the organization Consider the Customer: Utilities should expand efforts to use smart meter and smart grid data to improve customer service and the customer experience

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

20 Appendix: Additional Data by Rollout Status
In addition to smart meters, which of the following data sources provide the most valuable information to your organization?1 1Respondents asked to select top three 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/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 / market data = 11%

21 Appendix: Additional Data by Rollout Status
How are utilities leveraging smart grid data to improve customer service today?1 Percentage who gave themselves an “A” in the following measures:1 1Respondents asked to select all that apply


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