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© 2014 IBM Corporation
Transforming Energy and Utilities
through Big Data & Analytics
Anders Quitzau, Innovation Executive, IBM
28. maj 2014
© 2014 IBM Corporation2
What is changing in the Energy and Utilities industry?
Smart meters become mainstream
The grid gets older
Consumers want more control &
insight into energy consumption
Alternative energy enters the mix
60% of electric grid
assets will need
replacement in this
decade
In 2020, all Danish
electric utilities will
have smart metering
infrastructure (AMI)
installations
Global installed wind
power capacity
increased by 12.4
percent to more than
318 gigawatts in 2013
The number of U.S.
customers capable of
accessing information on
their energy use online
increased from 5.4M in
2010 to 17.5M in 2012
© 2014 IBM Corporation3
To sustain growth, leaders across energy & utilities are prioritizing
four imperatives…
Transform the
utility network
Transform customer
operations
Improve generation
performance
Continually improve
operational excellence
© 2014 IBM Corporation4
Big Data is not ’just’ data, there are a few new considerations
Volume
Data at
Rest
Terabytes to
exabytes of
existing data to
process
Velocity
Data in
Motion
Streaming data,
milliseconds to
seconds to
respond
Data in
Many Forms
Variety
Structured,
unstructured, text,
multimedia
Veracity
Data in
Doubt
Uncertainty due to
data inconsistency
& incompleteness,
ambiguities, latency,
deception, model
approximations
Value
Data of
Many Values
Large range of data
values from free (data
philanthropy to high
value monetization)
ValueVisibility
Data in
the Open
Open data is
generally open to
anyone. Which raises
issues of privacy.
Security and
provenance
Big	
  Data	
  
‘Big data’ is defined by IBM as any data that
cannot be captured, managed and/or processed
using traditional data management
components and techniques
Open	
  Data	
  
© 2014 IBM Corporation5
Big data makes a big difference
Organizations using big data and analytics are up to
23xmore likely to report they are
substantially outperforming
their competitors
than those who do not use big data and analytics
Source: Analytics: The real-world use of big data, a collaborative research study by the IBM Institute for Business Value and the Saïd Business
School at the University of Oxford. © IBM 2012
© 2014 IBM Corporation6
OutperformersUnderperformers
Translate
insight into
action
54%
108%
more likely
Make data
accessible
57%
84%
more likely
54%
108%
more likely
Draw insights
from data
26%
31%
26%
Using data, outperformers excel
in three key areas
Source: Leading through connections, Insights from the 2012 Global Chief Executive Officer study, IBM Institute for Business Value © IBM 2012
© 2014 IBM Corporation7
Big Data & Analytics capabilities help utilities leverage data to meet the
challenges of a connected world
45%
Increasing consumer
expectations and concerns
49%
>50% of surveyed consumers
with an opinion expect smart
grid technologies will lower total
household costs for energy use.
But . . .
of consumers were concerned
that erroneous smart meter
readings would result in
overcharges
By 2050, the Electric Power
Research Institute estimates
that the average electric bill
will probably go up by about
50 percent if the smart grid is
deployed.
is the expected increase in the
average electric bill if the smart
grid is not deployed
ca. 400%
In the utilities industry, the
number of connected devices –
participants in the “Internet of
things” – is growing
exponentially:
Compound annual growth
rate, 2010-2015
Data explosion Cost and pricing pressures
Data is emerging as
the world’s newest
resource for
competitive
advantage
Decision-making is
moving from the elite
few to the
empowered many
As the value of data
continues to grow –
current systems
won’t keep pace
© 2014 IBM Corporation8
Big data & analytics are transforming energy and utilities
Energy and Utilities are turning knowledge into power by using
big data & analytics to better understand and shape customer
usage, improve service levels and availability, and detect and
prevent energy theft.
© 2014 IBM Corporation9
Big data & analytics capabilities are required to address these
challenges and opportunities
ERP/ MRP
Social
Media
Location
Call
Centers
Fraud
Mgmt
Outage
Management
Regulatory
Asset
Management
Warranty /
Quality
Telematics
Grid
Customers
New/Enhanced
ApplicationsAll Data
Information Integration & Governance
Systems Security
On premise, Cloud, As a service
Storage
What action
should I
take?
Decision
management
Landing,
Exploration
and Archive
data zone
EDW and
data mart
zone
Operational
data zone
Real-time Data Processing & Analytics What is
happening?
Discovery and
exploration
Why did it
happen?
Reporting and
analysis
What could
happen?
Predictive
analytics and
modeling
Deep
Analytics
data zone What did
I learn,
what’s best?
Cognitive
SCADA
© 2014 IBM Corporation10
Key usage patterns for big data & analytics have emerged
Grid
Operations
Smart
Metering
Asset &
Workforce
Management
© 2014 IBM Corporation11
Grid
Operations
© 2014 IBM Corporation12
Grid
Operations
Field Services
MV & LV Grid
Planning
Asset Management
Voltage Regulation &
Protection
Customer Operations
Regulatory Reporting
System Control
• Detailed Load & voltage data
• Embedded generation impacts
• Load & Phase Balance
• Topology & switching history
• Events & alarms
• Fault location
• Grid conditions
• Load History
• Temperature & Condition
• Ratings & Impedance
• Voltage & PF profiles
• Batteries & secondary equip
• Exceptions & Excursions
• Improved power quality
• Fewer outages & events
• Avoid manual collection
• Load & voltage surveys
• PQ & outage investigations
• SAIDI/SAIFI
• Improved risk assessment response
• Lower technical and non-technical
losses
Big data & analytics capabilities can drive real business value from
Grid Operations
© 2014 IBM Corporation13
Enhance Grid Operations
Demand
Forecasting
Load
Forecasting
Distribution
Mgmt
Outage
Mgmt
Energy
Trading
SCADA
ERP/ MRP
EAM
Social
Location
PMU
AMI
IBM Watson Foundations
New/Enhanced
Applications
All Data
Information Integration & Governance
SystemsSystems SecuritySecurity
On premise, Cloud, As a service
StorageStorage
What action
should I
take?
Decision
management
Landing,
Exploration
and Archive
data zone
EDW and
data mart
zone
Operational
data zone
Real-time Data Processing & Analytics What is
happening?
Discovery and
exploration
Why did it
happen?
Reporting and
analysis
What could
happen?
Predictive
analytics and
modeling
Deep
Analytics
data zone What did
I learn,
what’s best?
Cognitive
Analyze data from continuous
sources in real time. Import and
execute predictive models.
Discover and navigate through
structured and unstructured
data across the entire
enterprise
Deep analysis of energy
demand and loads and the
impact of distributed generation
resources
Master relationships and
build / maintain a single
view of the grid
Cleanse and validate data
from multiple customer or
outage management systems
prior to loading in the
warehouse
Monitor the performance and
status of the grid via reports
and dashboards.Increase generation capacity in
response to demand
Predict excessive loads on the
grid before they occur
High bandwidth time series data
ingestion and recall
Strong real-time, streaming
data performance across
distributed grid data
© 2014 IBM Corporation14
Big data & analytics capabilities are transforming Grid
Operations
Anticipate outages
• Synthesized and analyzed
a large stream of data from
5,500 cell relays and 2.3
million smart meters
• Predict and prevent
operational issues
• Respond to outages more
efficiently by dispatching
crews to the right place at
the right time
How can I uncover
anomalies in cell relay
signals to predict and
prevent power outages?
Simulate energy
demand
• Forecasts national
demand every 30 minutes
for a full year in advance,
versus daily in the past
• 35 million load curves
analyzed and modeled in
near-real time
How do I integrate
renewable energies on
the grid and forecast
energy consumption ?
Energy utility
company in the
United States
Utility company
in France
Manage the flow of
power through the
grid automatically
How can I manage the
load capacity of the
grid without relying on
manual calculations ?
Australian Power
Company
• Implemented a rules
engine and advanced
analytics to continually
calculate the theoretical
load limits of assets within
the grid network
• Extended asset life and
subsequent deferred
unnecessary capital
investment via better asset
load ratings.
© 2014 IBM Corporation15
Smart
Metering
© 2014 IBM Corporation16
Big data and analytics capabilities drive real business value from
Smart Meter data
Smart
Metering
Grid Operations
Field Service
Resource Planning
Customer Service /
Customer Operations
Regulatory
Compliance
Efficient Regulatory
Compliance
Detect Energy Loss,
Theft & Fraud
Improve acceptance
rates for targeted
offerings
Improve load
forecasting & demand
accuracy
Optimize maintenance
& repair
Reduce Outages &
Downtime
© 2014 IBM Corporation17
Big data & analytics turns Smart Meter data into actionable
insight
Help customers
reduce energy
consumption
• Used smart meter data for
a customer web portal,
where customers can
access their personalized
information and learn how
much electricity
• Reduced load times by
more than 95 percent
• Decreased query times
more than 97 percent
• Reduced TCO from 1.3 TB
to 350 GB
How can I give
customers more control
over their energy use ?
End-to-end
management of the
grid
• Implemented a smart meter
infrastructure that provides
real-time, integrated view of
the grid
• Will reduce demand on the
grid by about 1,000
megawatts
• Will reduce greenhouse gas
emissions by at least
365,000 metric tons per year
How can I use smart
meter data to reduce
energy consumption?
US distributor &
transmitter of
electricity
Large California
Utility
Manage the flow of
power through the
grid automatically
How can I manage the
load capacity of the
grid without relying on
manual calculations ?
• Gathered & analyzed smart
grid data representing
diverse terrain, weather &
demographics
• 50% drop in short-term peak
loads
• 15% drop in overall peak
loads
• 10% reduction in electricity
bills
© 2014 IBM Corporation18
Gain insight from Smart Meter big data
Customer self-
serve portals
Fraud / theft
protection
Call Centers
Outage
Mgmt
Billing
systems
Meters
Grid
Customers
Location
ERP
IBM Watson Foundations
Information Integration & Governance
SystemsSystems SecuritySecurity
On premise, Cloud, As a service
StorageStorage
What action
should I
take?
Decision
management
Landing,
Exploration
and Archive
data zone
EDW and
data mart
zone
Operational
data zone
Real-time Data Processing & Analytics What is
happening?
Discovery and
exploration
Why did it
happen?
Reporting and
analysis
What could
happen?
Predictive
analytics and
modeling
Deep
Analytics
data zone What did
I learn,
what’s best?
Cognitive
New/Enhanced
Applications
All Data
Collect, store and analyze
up to 50,000 data points/
sec
Complex query processing of
historical meter usage data.
Cleanse and validate data from
multiple customer, billing or outage
management systems prior to
loading in the warehouse
Master relationships and
build / maintain a single
view of the grid
Discover and navigate
through structured and
unstructured data across the
entire enterprise
Analyze customer
energy usage, detect
energy theft or meter
tampering
Predict which customers
are candidates for TOU
pricing or demand /
response offerings
Offer TOU pricing or
demand / response
offerings
High availability of data and
analytics processing of
customer preferences
© 2014 IBM Corporation19
Asset &
Workforce
Management
© 2014 IBM Corporation20
Asset & Workforce Management drives real business value for
utilities
Easy access to all documents
needed to operate the assets
Populate work packages with
complete and accurate
information
Schedule maintenance based
on equipment conditions, not
fixed schedules
Asset &
Workforce
Management
Operate the Assets
Schedule Use of
the Assets
Maintain the Assets
Minimize planned and
unplanned maintenance
activity
Capture changes so “As-Built”
configuration is accurate
Use analytics to perform
Predictive Maintenance &
Condition Based Maintenance
Maintain accurate “As-Built”
documentation
Enforce business rules for
asset operations
© 2014 IBM Corporation21
PMQ
Capabilities
Enhance Asset & Workforce Management with big data & analytics
Load
Forecasting
Mobile
workforce
Asset Mgmt
Outage
Mgmt
Warranty /
Quality
SCADA
ERP/ MRP
EAM
Social
Media
DCS
Telematics
Grid
Information Integration & Governance
SystemsSystems SecuritySecurity
On premise, Cloud, As a service
StorageStorage
What action
should I
take?
Decision
management
Landing,
Exploration
and Archive
data zone
EDW and
data mart
zone
Operational
data zone
Real-time Data Processing & Analytics What is
happening?
Discovery and
exploration
Why did it
happen?
Reporting and
analysis
What could
happen?
Predictive
analytics and
modeling
Deep
Analytics
data zone What did
I learn,
what’s best?
Cognitive
Internetscalemessaging
IBM Watson Foundations New/Enhanced
Applications
All Data
Real-time analysis of
grid / generation asset
data
Monitor the performance of
equipment and assets during
operation
Predict an equipment failure and
avoid an outage
Recommend preventative
maintenance
Pre-built data schema
for quality, machine and
production data
Define and manage the product
master data
Protocol
conversion, message mediation &
transformation of grid or power
generation data
Landing zone for data
collected from grid assets
for off-line analytics
Consolidate grid data for a
360 degree view of the grid
or generation plant
Strong real-time, streaming data performance
across distributed asset info
© 2014 IBM Corporation22
Big data & analytics is transforming Asset & Workforce
Management
Early failure
detection
• Used text mining methods
for extracting insights from
unstructured sources
• Achieved 90% failure
prediction accuracy for gas
turbine compressor
subsystem
• Identified 11 month early
warning of production and
supplier issues
How do I reduce
unscheduled
maintenance costs?
Analytics Driven
Mining Asset
Management
Performed analytics on data
from trucks / mining
equipment, weather,
operational performance and
ore price to assess asset
health
Estimated $3B increased
profit on $30B operation
• Reduced 10-day failure
probability to less than 1%
How can I minimize down
time related to asset
maintenance?
Gas Turbine
Manufacturer
Large Mining
Company
Asset & Workforce
Management
Optimization
How do I measure the
risk of failure and
optimize repair /
replacement work?
Water Utility
Company
• Used advanced analytics to
identify potential problems
based on location, time,
weather and maintenance
history
• 25%+ increased crew
utilization; 10-15% fuel
savings
•  30-50% savings on
selected inspection and
preventive maintenance
© 2014 IBM Corporation23
•  Find the most compelling use-
cases and the business sponsor
•  Enable and motivate your people
•  Infuse analytics into key business
processes
•  Deploy the full range
of analytics
Build a culture that
infuses analytics
everywhere
Be proactive about
privacy, security
and governance
Invest in a big data
& analytics platform
How to move strategically to transform your business
•  To trust the insights you have
to trust the facts. Big Data
also requires data
governance
•  Privacy and security to
protect the data
•  Enable risk-aware decisions
•  Build towards a platform for
all data and analytics
•  Analyze data in motion
•  Cultivate new partnerships
and roles
ibmbigdatahub.com/industry/energy-utilities

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Big Data Analytics in Energy & Utilities

  • 1. © 2014 IBM Corporation Transforming Energy and Utilities through Big Data & Analytics Anders Quitzau, Innovation Executive, IBM 28. maj 2014
  • 2. © 2014 IBM Corporation2 What is changing in the Energy and Utilities industry? Smart meters become mainstream The grid gets older Consumers want more control & insight into energy consumption Alternative energy enters the mix 60% of electric grid assets will need replacement in this decade In 2020, all Danish electric utilities will have smart metering infrastructure (AMI) installations Global installed wind power capacity increased by 12.4 percent to more than 318 gigawatts in 2013 The number of U.S. customers capable of accessing information on their energy use online increased from 5.4M in 2010 to 17.5M in 2012
  • 3. © 2014 IBM Corporation3 To sustain growth, leaders across energy & utilities are prioritizing four imperatives… Transform the utility network Transform customer operations Improve generation performance Continually improve operational excellence
  • 4. © 2014 IBM Corporation4 Big Data is not ’just’ data, there are a few new considerations Volume Data at Rest Terabytes to exabytes of existing data to process Velocity Data in Motion Streaming data, milliseconds to seconds to respond Data in Many Forms Variety Structured, unstructured, text, multimedia Veracity Data in Doubt Uncertainty due to data inconsistency & incompleteness, ambiguities, latency, deception, model approximations Value Data of Many Values Large range of data values from free (data philanthropy to high value monetization) ValueVisibility Data in the Open Open data is generally open to anyone. Which raises issues of privacy. Security and provenance Big  Data   ‘Big data’ is defined by IBM as any data that cannot be captured, managed and/or processed using traditional data management components and techniques Open  Data  
  • 5. © 2014 IBM Corporation5 Big data makes a big difference Organizations using big data and analytics are up to 23xmore likely to report they are substantially outperforming their competitors than those who do not use big data and analytics Source: Analytics: The real-world use of big data, a collaborative research study by the IBM Institute for Business Value and the Saïd Business School at the University of Oxford. © IBM 2012
  • 6. © 2014 IBM Corporation6 OutperformersUnderperformers Translate insight into action 54% 108% more likely Make data accessible 57% 84% more likely 54% 108% more likely Draw insights from data 26% 31% 26% Using data, outperformers excel in three key areas Source: Leading through connections, Insights from the 2012 Global Chief Executive Officer study, IBM Institute for Business Value © IBM 2012
  • 7. © 2014 IBM Corporation7 Big Data & Analytics capabilities help utilities leverage data to meet the challenges of a connected world 45% Increasing consumer expectations and concerns 49% >50% of surveyed consumers with an opinion expect smart grid technologies will lower total household costs for energy use. But . . . of consumers were concerned that erroneous smart meter readings would result in overcharges By 2050, the Electric Power Research Institute estimates that the average electric bill will probably go up by about 50 percent if the smart grid is deployed. is the expected increase in the average electric bill if the smart grid is not deployed ca. 400% In the utilities industry, the number of connected devices – participants in the “Internet of things” – is growing exponentially: Compound annual growth rate, 2010-2015 Data explosion Cost and pricing pressures Data is emerging as the world’s newest resource for competitive advantage Decision-making is moving from the elite few to the empowered many As the value of data continues to grow – current systems won’t keep pace
  • 8. © 2014 IBM Corporation8 Big data & analytics are transforming energy and utilities Energy and Utilities are turning knowledge into power by using big data & analytics to better understand and shape customer usage, improve service levels and availability, and detect and prevent energy theft.
  • 9. © 2014 IBM Corporation9 Big data & analytics capabilities are required to address these challenges and opportunities ERP/ MRP Social Media Location Call Centers Fraud Mgmt Outage Management Regulatory Asset Management Warranty / Quality Telematics Grid Customers New/Enhanced ApplicationsAll Data Information Integration & Governance Systems Security On premise, Cloud, As a service Storage What action should I take? Decision management Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone What did I learn, what’s best? Cognitive SCADA
  • 10. © 2014 IBM Corporation10 Key usage patterns for big data & analytics have emerged Grid Operations Smart Metering Asset & Workforce Management
  • 11. © 2014 IBM Corporation11 Grid Operations
  • 12. © 2014 IBM Corporation12 Grid Operations Field Services MV & LV Grid Planning Asset Management Voltage Regulation & Protection Customer Operations Regulatory Reporting System Control • Detailed Load & voltage data • Embedded generation impacts • Load & Phase Balance • Topology & switching history • Events & alarms • Fault location • Grid conditions • Load History • Temperature & Condition • Ratings & Impedance • Voltage & PF profiles • Batteries & secondary equip • Exceptions & Excursions • Improved power quality • Fewer outages & events • Avoid manual collection • Load & voltage surveys • PQ & outage investigations • SAIDI/SAIFI • Improved risk assessment response • Lower technical and non-technical losses Big data & analytics capabilities can drive real business value from Grid Operations
  • 13. © 2014 IBM Corporation13 Enhance Grid Operations Demand Forecasting Load Forecasting Distribution Mgmt Outage Mgmt Energy Trading SCADA ERP/ MRP EAM Social Location PMU AMI IBM Watson Foundations New/Enhanced Applications All Data Information Integration & Governance SystemsSystems SecuritySecurity On premise, Cloud, As a service StorageStorage What action should I take? Decision management Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone What did I learn, what’s best? Cognitive Analyze data from continuous sources in real time. Import and execute predictive models. Discover and navigate through structured and unstructured data across the entire enterprise Deep analysis of energy demand and loads and the impact of distributed generation resources Master relationships and build / maintain a single view of the grid Cleanse and validate data from multiple customer or outage management systems prior to loading in the warehouse Monitor the performance and status of the grid via reports and dashboards.Increase generation capacity in response to demand Predict excessive loads on the grid before they occur High bandwidth time series data ingestion and recall Strong real-time, streaming data performance across distributed grid data
  • 14. © 2014 IBM Corporation14 Big data & analytics capabilities are transforming Grid Operations Anticipate outages • Synthesized and analyzed a large stream of data from 5,500 cell relays and 2.3 million smart meters • Predict and prevent operational issues • Respond to outages more efficiently by dispatching crews to the right place at the right time How can I uncover anomalies in cell relay signals to predict and prevent power outages? Simulate energy demand • Forecasts national demand every 30 minutes for a full year in advance, versus daily in the past • 35 million load curves analyzed and modeled in near-real time How do I integrate renewable energies on the grid and forecast energy consumption ? Energy utility company in the United States Utility company in France Manage the flow of power through the grid automatically How can I manage the load capacity of the grid without relying on manual calculations ? Australian Power Company • Implemented a rules engine and advanced analytics to continually calculate the theoretical load limits of assets within the grid network • Extended asset life and subsequent deferred unnecessary capital investment via better asset load ratings.
  • 15. © 2014 IBM Corporation15 Smart Metering
  • 16. © 2014 IBM Corporation16 Big data and analytics capabilities drive real business value from Smart Meter data Smart Metering Grid Operations Field Service Resource Planning Customer Service / Customer Operations Regulatory Compliance Efficient Regulatory Compliance Detect Energy Loss, Theft & Fraud Improve acceptance rates for targeted offerings Improve load forecasting & demand accuracy Optimize maintenance & repair Reduce Outages & Downtime
  • 17. © 2014 IBM Corporation17 Big data & analytics turns Smart Meter data into actionable insight Help customers reduce energy consumption • Used smart meter data for a customer web portal, where customers can access their personalized information and learn how much electricity • Reduced load times by more than 95 percent • Decreased query times more than 97 percent • Reduced TCO from 1.3 TB to 350 GB How can I give customers more control over their energy use ? End-to-end management of the grid • Implemented a smart meter infrastructure that provides real-time, integrated view of the grid • Will reduce demand on the grid by about 1,000 megawatts • Will reduce greenhouse gas emissions by at least 365,000 metric tons per year How can I use smart meter data to reduce energy consumption? US distributor & transmitter of electricity Large California Utility Manage the flow of power through the grid automatically How can I manage the load capacity of the grid without relying on manual calculations ? • Gathered & analyzed smart grid data representing diverse terrain, weather & demographics • 50% drop in short-term peak loads • 15% drop in overall peak loads • 10% reduction in electricity bills
  • 18. © 2014 IBM Corporation18 Gain insight from Smart Meter big data Customer self- serve portals Fraud / theft protection Call Centers Outage Mgmt Billing systems Meters Grid Customers Location ERP IBM Watson Foundations Information Integration & Governance SystemsSystems SecuritySecurity On premise, Cloud, As a service StorageStorage What action should I take? Decision management Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone What did I learn, what’s best? Cognitive New/Enhanced Applications All Data Collect, store and analyze up to 50,000 data points/ sec Complex query processing of historical meter usage data. Cleanse and validate data from multiple customer, billing or outage management systems prior to loading in the warehouse Master relationships and build / maintain a single view of the grid Discover and navigate through structured and unstructured data across the entire enterprise Analyze customer energy usage, detect energy theft or meter tampering Predict which customers are candidates for TOU pricing or demand / response offerings Offer TOU pricing or demand / response offerings High availability of data and analytics processing of customer preferences
  • 19. © 2014 IBM Corporation19 Asset & Workforce Management
  • 20. © 2014 IBM Corporation20 Asset & Workforce Management drives real business value for utilities Easy access to all documents needed to operate the assets Populate work packages with complete and accurate information Schedule maintenance based on equipment conditions, not fixed schedules Asset & Workforce Management Operate the Assets Schedule Use of the Assets Maintain the Assets Minimize planned and unplanned maintenance activity Capture changes so “As-Built” configuration is accurate Use analytics to perform Predictive Maintenance & Condition Based Maintenance Maintain accurate “As-Built” documentation Enforce business rules for asset operations
  • 21. © 2014 IBM Corporation21 PMQ Capabilities Enhance Asset & Workforce Management with big data & analytics Load Forecasting Mobile workforce Asset Mgmt Outage Mgmt Warranty / Quality SCADA ERP/ MRP EAM Social Media DCS Telematics Grid Information Integration & Governance SystemsSystems SecuritySecurity On premise, Cloud, As a service StorageStorage What action should I take? Decision management Landing, Exploration and Archive data zone EDW and data mart zone Operational data zone Real-time Data Processing & Analytics What is happening? Discovery and exploration Why did it happen? Reporting and analysis What could happen? Predictive analytics and modeling Deep Analytics data zone What did I learn, what’s best? Cognitive Internetscalemessaging IBM Watson Foundations New/Enhanced Applications All Data Real-time analysis of grid / generation asset data Monitor the performance of equipment and assets during operation Predict an equipment failure and avoid an outage Recommend preventative maintenance Pre-built data schema for quality, machine and production data Define and manage the product master data Protocol conversion, message mediation & transformation of grid or power generation data Landing zone for data collected from grid assets for off-line analytics Consolidate grid data for a 360 degree view of the grid or generation plant Strong real-time, streaming data performance across distributed asset info
  • 22. © 2014 IBM Corporation22 Big data & analytics is transforming Asset & Workforce Management Early failure detection • Used text mining methods for extracting insights from unstructured sources • Achieved 90% failure prediction accuracy for gas turbine compressor subsystem • Identified 11 month early warning of production and supplier issues How do I reduce unscheduled maintenance costs? Analytics Driven Mining Asset Management Performed analytics on data from trucks / mining equipment, weather, operational performance and ore price to assess asset health Estimated $3B increased profit on $30B operation • Reduced 10-day failure probability to less than 1% How can I minimize down time related to asset maintenance? Gas Turbine Manufacturer Large Mining Company Asset & Workforce Management Optimization How do I measure the risk of failure and optimize repair / replacement work? Water Utility Company • Used advanced analytics to identify potential problems based on location, time, weather and maintenance history • 25%+ increased crew utilization; 10-15% fuel savings •  30-50% savings on selected inspection and preventive maintenance
  • 23. © 2014 IBM Corporation23 •  Find the most compelling use- cases and the business sponsor •  Enable and motivate your people •  Infuse analytics into key business processes •  Deploy the full range of analytics Build a culture that infuses analytics everywhere Be proactive about privacy, security and governance Invest in a big data & analytics platform How to move strategically to transform your business •  To trust the insights you have to trust the facts. Big Data also requires data governance •  Privacy and security to protect the data •  Enable risk-aware decisions •  Build towards a platform for all data and analytics •  Analyze data in motion •  Cultivate new partnerships and roles