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Opower CONFIDENTIAL: DO NOT DISTRIBUTE How To Go From Big Data to Big Insights Nicole Poindexer, Director Global Business Development 28 May 2013
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
How To Go From
Big Data to Big Insights Nicole Poindexer,
Director Global Business Development
28 May 2013
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Agenda
2 28 May 2013
How Does Opower Use Big Data?
What Are Keys to Big Data Success?
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Opower overview
3 28 May 2013
Our Company
• 80 utility partners in 6 countries
• Actively engaging 15 million homes
• $200M in verified savings
• 300+ employees in Washington DC, San Francisco, London, Singapore
Our DNA
• Behavioral science
• Big data analytics
• Software engineering
• Consumer marketing
Technology Investment
• $25M R&D investment annually
• World-class partners: Facebook, Honeywell, Home Depot, Best Buy
A Customer Engagement Platform for Utilities
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Using Big Data to Engage Customers
4
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Scale and scope of Opower Big Data
5 28 May 2013
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Agenda
6 28 May 2013
How Does Opower Use Big Data?
What Are Keys to Big Data Success?
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Keys to Big Data Success
7 28 May 2013
Identify key business questions
Create a “sandbox”
for data discovery
Refine questions through iterative analysis
Validate hypotheses
Use findings to enhance
process/ product
Analytics Pipeline
Enabling Infrastructure
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Keys to Big Data Success
8 28 May 2013
Identify key business questions
Create a “sandbox”
for data discovery
Refine questions through iterative analysis
Validate hypotheses
Use findings to enhance
process/ product
Analytics Pipeline
Enabling Infrastructure
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE
Data <> Insights
9 28 May 2013
?
Do the heavy lifting for your customers
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE
Can we use AMI data to help increase
understanding of energy use?
10 28 May 2013
Data from one AMI household
Insight requires 60 minute data or better
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE
Idle load varies by customer
11 28 May 2013
5000 customers from Utility X
Insight requires 60 minute data or better
High: 30%+
Average: 17%
Idle load % of total energy usage 5,000 customers at utility x
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE 12
Target messages to reduce idle load
High: 30%
Identify customers with high
idle load, based on load
profile…..
Average: 17%
…then target relevant tips
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE
Unusual usage alerts
» Empower customers and
manage expectations with alerts
based on energy use
» Being leveraged for unusual
usage (high bill) alerts in the US
and UK
13 28 May 2013
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
0
20
40
60
80
100
120
2/1 2/8 2/15 2/22
Bil
l To
tal ($
)
Actual
Forecast
Forecasting your next bill: example
$70
$91
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE
Information Flow
Collect usage
data from
customer
meters
Transfer
daily interval
data to
Opower
Opower
processes latest
data
High Bill
Calculator
Data
Import/
Validate
Generates and
sends high bill
alerts
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE
Keys to Big Data Success
16 28 May 2013
Identify key business questions
Create a “sandbox”
for data discovery
Refine questions through iterative analysis
Validate hypotheses
Use findings to enhance
process/ product
Analytics Pipeline
Enabling Infrastructure
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE
The data challenge
17 28 May 2013
Our Scale:
• 50M Households, 15M with AMI
• 30TB of Usage Data
• 100k events per day per t-stat
• High Throughput Requirements
• ~10M Bill Forecasts in 12 hours
• High Sequential IO Requirements
• 1-3 years of data for each personalized comparison
• Comparisons may require processing data for 100s of other consumers
OPOWER CONFIDENTIAL: DO NOT DISTRIBUTE
Components of “Enabling
Infrastructure”
• Use Cases –Reporting
–Data Visualization
–Statistical Analysis
–Batch Calculations
–ETL
–Real-time Engagement
Channels
–Testing
• Data Set
Requirements –Transactional
–Size/Scale
–Access Patterns
–Latency Requirements
–Security
18 28 May 2013
» Align Infrastructure components with use case and data set
requirements:
Conflicting requirements must be handled with replication and
technology diversification.
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Appendix
28 May 2013
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
Opower leads in Big Data Analytics and
Applications for utilities
20 28 May 2013
Opower CONFIDENTIAL: DO NOT DISTRIBUTE
1 2 3 4 5
8.8 GWh 50 GWh 192 GWh
732 GWh
Continuous optimization delivers results
21
2 TWh
3B lbs CO2
$220 M
