General Electric (GE) is one of the world’s largest industrial

companies with products ranging from turbines to jet engines to

medical equipment, but it may not be much longer. The company is
transitioning to a much more technology-centric business strategy
and business model. GE is selling off its division that makes
refrigerators and microwave ovens along with most of GE Capital
financial services to focus on electric power generators, jet
engines, locomotives, and oilrefining gear and software companies
such as Oracle, SAP, and Microsoft have traditionally been focused
on providing technology for the back office. In contrast, GE is
putting its money on the technology that controls and monitors
industrial machines as well as software-powered, cloudbased
services for analyzing and deriving value from the data. GE hopes
this strategy will turn it into a major software company. GE is using
sensor-generated data from industrial machines to help customers
monitor equipment performance, prevent breakdowns, and assess
the machines’ overall health. This new technology is opening new
opportunities for GE customers while also helping to transform GE
from a traditional manufacturer to a modern digital business. GE has
committed $1 billion to installing sensors on gas turbines, jet
engines, and other machines; connecting them to the cloud; and
analyzing the resulting data to identify ways to improve machine
productivity and reliability. In other words, GE is betting its future
on software and the Internet of Things (IoT). In a number of
industries, improving the productivity of existing assets by even a
single percentage point can generate significant benefits. This is
true of the oil and gas sector, where average recovery rate of an oil
well is 35 percent. That means 65 percent of a well’s potential is
left in the earth because available technology makes it too
expensive to extract. If technology can help oil extraction
companies raise the recovery rate from 35 to 36 percent, the
world’s output will increase by 80 billion barrels—the equivalent of
three years of global supply. The oil and gas industry is also deeply
affected by unplanned downtime, when equipment cannot operate
because of a malfunction. A single unproductive day on a platform
can cost a liquified natural gas (LNG) facility as much as $25
million, and an average midsized LNG facility experiences about five
down days a year. That’s $125 to $150 million lost. Minimizing
downtime is critical, especially considering declining revenues from
lower energy prices. GE sees a $1 billion opportunity for its IoT
software. The foundation for all of GE’s Industrial Internet
applications is Predix, a software platform launched in 2015 to
collect data from industrial sensors and analyze the information in
the cloud. Predix can run on any cloud infrastructure. The platform
has open standards and protocols that allow customers to more
easily and quickly connect their machines to the Industrial Internet.
The platform can accommodate the size and scale of industrial data
for every customer at current levels of use, but it also has been
designed to scale up as demand grows. Predix can offer apps
developed by other companies as well as GE, is available for on-
premises or cloud-based deployment, and can be extended by
customers with their own data sources, algorithms, and code.
Customers may develop their own custom applications for the
Predix platform. GE is also building a developer community to
create apps that can be hosted on Predix. Predix is not limited to
industrial applications. It could be used for analyzing data in
healthcare systems, for example. GE now has a Health Cloud
running on Predix. Data security is embedded at all platform
application layers, and this is essential for companies linking their
operations to the Internet. GE currently uses Predix to monitor and
maintain its own industrial products, such as wind turbines, jet
engines, and hydroelectric turbine systems. Predix is able to
provide GE corporate customers’ machine operators and
maintenance engineers with real-time information to schedule
maintenance checks, improve machine efficiency, and reduce
downtime (Figure 1). Helping customers collect and use this
operational data proactively would lower costs in GE service
agreements. When GE agrees to provide service for a customer’s
machine, it often comes with a performance guarantee. Proactive
identification of potential issues that also takes the cost out of shop
visits helps the customers and helps GE. Figure 1. GE’s Predix In
early 2013, GE began to use Predix to analyze data across its fleet
of machines. By identifying what made one machine more efficient
or down-time-prone than another, GE could more tightly manage its
operations. For example, by using high-performance analytics, GE
learned that some of its jet aircraft engines were beginning to
require more frequent unscheduled maintenance. A single engine’s
operating data will only tell you there is a problem with that engine.
But by collecting massive amounts of data and analyzing the data
across its entire fleet of machines, GE was able to cluster engine
data by operating environment. The company found that the hot and
harsh environments in the Middle East and China caused engines to
clog, heat up, and lost efficiency, so they required more
maintenance. GE found that engines had far fewer of these
problems if they were washed more frequently. Fleet analytics
helped GE increase engine lifetime and reduce engine maintenance.
The company thinks it can save its customers an average of $7
million of jet airline fuel annually because their engines will be more
efficient. Predix’s robust data and analytics platform made it
possible for GE to use data across every GE engine all over the
world and cluster fleet data. Predix is starting to provide solutions
for GE customers. Irish Power is an early Predix user. The company
adopted GE’s predictive analytics tool suite Reliability Excellence
based on the Predix platform. Irish Power started out by using
operational data analytics to improve the efficiency of its Whitegate
plant, a 445-megawatt gas combined-cycle power plant located 25
miles east of the city of Cork, Ireland. Irish Power plans to roll out a
module for process optimization and will connect plant performance
to the real-time energy marketplace. These analytics help Irish
Power and customers identify ways of lowering production costs,
increasing plant capability, and improving system reliability.
Applying analytics built on the Predix platform can enable GE to
offer customers like Irish Power anomaly detection or enable cost
savings by reducing the need for preventative maintenance thanks
to the visibility of the operational data GE can now provide. British
oil and gas company BP had been using its own software to monitor
conditions in its oil wells. Recently, however, BP management
decided to get out of the software business and became a GE
customer. By the end of 2015, BP equipped 650 of its thousands of
oil wells with GE sensors linked to Predix. Each well was outfitted
with 20 to 30 sensors to measure pressure and temperature,
transmitting 500,000 data points to the Predix cloud every 15
seconds. BP hopes to use the data to predict well flows and the
useful life of each well and ultimately to obtain an enterprise-wide
view of its oil fields’ performance. GE identified pipeline risk
management as a major challenge for the oil and gas industry.
There are 2 million miles of transmission pipe throughout the globe,
moving liquid oil or gas from its point of extraction to refining,
processing, or market. About 55 percent of transmission pipeline in
the United States was installed before 1970. Pipeline spills are not
frequent, but when they occur, they cause serious economic and
environmental damage as well as bad publicity for pipeline
operators and energy companies. Pipeline operators are always
anxious to know where their next rupture will be, but they typically
lacked the data to measure pipeline fitness. Operators had no way
of integrating multiple sources of data into one place so they could
see and understand the risk in their pipelines. GE developed a
pipeline-management software suite for accessing, managing, and
integrating critical data for the safe management of pipelines,
including a risk assessment tool to monitor aging infrastructure.
GE’s risk-assessment solution combines internal and external
factors (such as flooding) to provide an accurate, up-to-the minute
visual representation of where risk exists in a pipeline. This risk
assessment tool enables pipeline operators to see how recent
events affect their risk and make real-time decisions about where
field service crews should be deployed along the pipeline. The risk
assessment tool visualization and analytics capabilities run on
Predix. GE is also pulling data from weather systems and dig-
reporting services to provide a more comprehensive view of a
pipeline network. Weather has a sizable impact on risk for pipelines
in areas prone to seismic activity, waterways, and washouts.
Checking weather patterns along thousands of miles of pipe for rain
or flood zones and integrating those data with other complex
pipeline data set is very difficult to perform manually. But by
bringing all relevant together data in one place, GE gives pipeline
operators easier access to information to help them address areas
with the greatest potential impact. GE expects customers to benefit
immediately from having all of their data integrated. But it wants
them to be able to do more. In addition to being able to examine all
current risk, pipeline operators would benefit from a “what-if”
calculation tool to model hypothetical scenarios, such as assessing
the impact of adjusting operating pressures or addressing particular
areas of corrosive pipe. GE would give them the tools for a color-
coded view of how those actions affect pipeline risk. In addition, GE
wants to go beyond helping its customers manage the performance
of their GE machines to managing the data on all of the machines in
their entire operations. Many customers use GE equipment
alongside of equipment from competitors. The customer cares
about running the whole plant, not just GE turbines, for example,
and 80 percent of the equipment in these facilities is not from GE. If,
for example, if an oil and gas customer has a problem with a turbo
compressor, a heat exchanger upstream from that compressor may
be the source of the problem, so analyzing data from the turbo
compressor will only tell part of the story. Customers therefore
want GE to analyze non-GE equipment and help them keep their
entire plant running. GE is in discussions with some customers
about managing sensor data from all of the machine assets in their
operation. If a customer purchases a piece of GE equipment such as
a gas turbine or aircraft engine, GE often enters into a 10- to 15-year
contractual services agreement that allows GE to connect to and
monitor that machine, perform basic maintenance and diagnostics,
and provide scheduled repairs. GE receives a bonus payment for
keeping the equipment running at a specific threshold. GE may now
be able to apply such outcome-based pricing to coverage of non-GE
machines. GE CEO Jeffrey Immelt wants GE to become a top 10
software company by 2020. In order to do this, GE needs to sell vast
amounts of applications and Predix-based analytics. Although few
businesses have the capital or infrastructure to operate a platform
for integrating and analyzing their IoT data, GE faces competition
from many sources. Amazon, Google, IBM, and Microsoft are all
getting into IoT platforms, and dozens of start-ups have similar
ambitions. The biggest question is whether other large industrial
companies will turn to GE or to another cloud platform to manage
their information. And if you are a manufacturer of some size and
sophistication, will you allow GE to “own” the data on your
business, or will you manage and analyze the data yourself?