Check out this white paper from eInfochips which showcases how energy and utility providers can unlock potential service opportunities using our predictive analytics solution across all stages of the business cycle. Major utility players are set to roll out millions of smart meters with the aim of generating actionable insights even though as per the industry’s own admission, any serious effort toward monetization is being offset by a lack of core IT capabilities, especially in big data technology. Capturing proactive intelligence on consumer behavior is the way to go. In this white paper, eInfochips demonstrates how utility players can predict demand response, generation response and create new revenue models around coincidental peak demands, smart expenditure modeling and other forms of end user data.

2. 2
Why Utility Players Need BI/Analytics
- Energy and utility industry players to invest US$7 billion on big data and
analytics in 2014, cross-industry spending at 15% (ABI Research, 2014)
- At an annual CAGR of 25%, the same figure is likely to increase by three times
to US$21 billion by 2019
- Key business drivers: Demand response and generation programs,
personalized customer care, complex customer data, regulatory norms
The Challenge? Utilities lack core IT capabilities in unlocking value data from
millions of smart meters and converting them into business models

3. 3
Smart Meter Era – Need for Change in Utility Business
- Watershed moment: Utilities worldwide have
announced smart meter roll-outs in their millions
- Transition from predictable business models to a
customer-centric one
- Transition from supply-side business model to a data-
driven, demand-based approach
- Which is better?
- Option A: Real time controls over generation, consumption and costs
OR
- Option B:Blindly augmenting capacity and surprising end users with bill shock

4. 4
The Challenge of “Disaggregated” Data!
- Compared to any other point of time in history, utility providers have access to
the largest data set of consumer behavior – over 1 billion data points daily
- “Disaggregated” data of no use to utilities unless convertible to revenue
models
The Solution? Utility Players are looking to leverage Big Data-based predictive,
statistical models derived from historical inputs to create predictable load
forecasting and innovative pricing plans

5. 5
New Utility Revenue Models based on BI/Analytics
- Predicting demand response can lead to up to 90 per cent cost savings
compared to other alternatives such as increasing generation capacity
- Predicting generation response will go a long way in accumulating supply side
cost savings
- Meeting regulatory compliance
- Reducing customer churn: Providing BI-based loyalty programs for customers
without increasing tariff

6. 6
eInfochips’ BI/Analytics Framework to Visualize Energy Data
- Data Collection: Fire/smoke,
floods, weather outage, peak
demand, HVAC, smart home data
- Data Analysis: Predictive
analytics on Normalized to create
demand-side patterns
- Data Visualization: Alarms and
failures mapping, pattern
prediction, prioritized responses

7. 7
Monetization Example – Smart Home Use Case
- 1 million smart devices generate 3 billion
records a month
- Time needed to individually profile 3 billion
records = 2 mins. X 3 billion = 10,000 years!
The Solution? A tool like MongoDB inserts
only 1 million records and retrieves 300,000
saving valuable time, costs and productivity in
data analysis

8. 8
Potential Business Areas for Utilities
- Demand Response Services: Putting the end user in control of their actual
consumption
- Coincidental Peak Demand Programs: When lots of consumers are involved,
utilities can guide them to save on energy bills based on accurate prediction
of coincidental peak demand
- Predicting Resource Demand: Using smart analytics tools, utilities can predict
future resource demand originating from historical data thus avoiding service
disruptions as well as overcapacity concerns.

9. eInfochips Smart Energy Analytics Solution
Smart
Homes
SMAC Internet of Things
(IoT)
Data integration
module
MongoDB – Events
and device data
processing integration
Tableau – Charts and
Reports for
visualization
Intelligently integrates
application, device,
online and
unstructured data
As a MongoDB
solutions partner,
eInfochips deliver
operational
insights, reduces
costs, improves
customer service
and creates new
revenue streams
Cloud Enablement
Predictive analytics
using Hadoop,
MongoDB, CRM/ERP
BI and ad hoc
reporting over
Tableau
Operating across
public, private and
hybrid cloud
environments,
eInfochips supports
device
integration across
millions of device
endpoints
with security features
like role-based access,
HTTPS and crypto-
secure tokens and
Spring
security framework.
Areas of Expertise

10. To learn more on smart energy analytics and the
eInfochips solution, please visit the link below to
download our white paper
http://einfochips.viewpage.co/smart-energy-
analytics-for-utilities-whitepaper
Read our White Paper

11. eInfochips Work Portfolio
11
Application
System
Hardware
Mechanical
BI and Big Data
Cloud
Mobility
e-Commerce
Firmware
Operating System
BSP and Drivers
On-Chip Features
Electronic / PCB
FPGA
ASIC and SoC
IP Integration
Enclosures
CAD Modelling
Ergonomics
Industrial

12. Thank You
12
marketing@einfochips.com