Industrial Internet Insights report - for 2015
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Industrial Internet Insights Report
for 2015
According to new research from GE
and Accenture, executives across the
Industrial and healthcare sectors see
the enormous opportunities of the
Industrial Internet and in many cases
are deploying the first generation
of solutions. The vast majority
believe that Big Data analytics
has the power to dramatically
alter the competitive landscape
of industries within just the next
year and are investing accordingly.
Yet challenges around security,
data silos and systems integration
issues between organizations
threaten to delay Industrial Internet
solutions that could offer distinctive
operational, strategic and competitive
advantages. Spurred on by board-
level direction, surveyed executives
feel a sense of urgency in moving
more briskly toward the Industrial
Internet future.
2
Table of contents
Introduction 4
Tapping the potential value 5
The formula for the Industrial Internet 7
A sense of urgency 8
About the research 9
Moving to growth and value creation 10
But are companies up for the challenge? 12
Moving from today’s implementation to tomorrow’s strategies 14
Big Data analytics in the healthcare industry: A diagnosis 16
Positive outcomes 17
Shaking up the healthcare space 18
Expectations are high and driven by the Board 18
An urgency to deliver improved patient outcomes 19
Talent issues 20
Driving better patient outcomes 21
Becoming an Industrial Internet value creator 22
Invest in end-to-end security 23
Break down the barriers to data integration 24
Focus on talent acquisition and development 26
Consider new business models needed to be successful with the Industrial Internet 31
Actively manage regulatory risk 32
Leverage mobile technology to deliver analytic insights 32
Conclusion 34
About GE 36
About Accenture 36
About GE and Accenture Alliance 36
3
Introduction
How big is the economic power of the Industrial
Internet? Consider one analysis that places a
conservative estimate of worldwide spending at $500
billion by 2020, and which then points to more optimistic
forecasts ranging as high as $15 trillion of global GDP
by 2030.1
The Industrial Internet—the combination of Big Data
analytics with the Internet of Things (see sidebar)—
is producing huge opportunities for companies in all
industries, but especially in areas such as Aviation,
Oil and Gas, Transportation, Power Generation and
Distribution, Manufacturing, Healthcare and Mining.
Why? Because, as one recent analysis has it, “Not all Big
Data is created equal.” According to the authors, “data
created by industrial equipment such as wind turbines,
jet engines and MRI machines … holds more potential
business value on a size-adjusted basis than other types
of Big Data associated with the social Web, consumer
Internet and other sources.”2
1. David Floyer, “Defining and Sizing the Industrial Internet,” Wikibon, June 27, 2013; Peter C. Evans and Marco Annunziata, “General
Electric: Industrial Internet, Pushing the Boundaries of Minds and Machines,” November 2012.
2. http://wikibon.org/wiki/v/The_Industrial_Internet_and_Big_Data_Analytics:_Opportunities_and_Challenges.
4
Tapping the 61 percent of those surveyed noted
that analytics is their top-ranked
surveyed. Strong board-level support
can also be seen in industries such
potential value priority; this number drops to about 30
percent or less for industries such as
as Manufacturing (67 percent noted
the Board as the primary influencer),
Power Distribution (28 percent), Power Aviation (61 percent) and Rail (60
Executives of industrial companies
Generation (31 percent), Oil and Gas percent).
are well aware of the potential power
and source of value of the Industrial (31 percent) and Mining (24 percent).
Internet, according to new research (See Figure 2.)
from GE and Accenture. (See “About This prioritization of spending
the research.”) For example, according becomes clearer when we look at
to our survey, 73 percent of companies
are already investing more than 20
who is supporting Big Data initiatives.
Simply put, it’s no longer the usual
Across the industries
percent of their overall technology
budget on Big Data analytics—and
suspects such as the CIO or COO. surveyed, 80 to 90
Indeed, 53 percent of all survey
more than two in 10 are investing respondents indicated that their Board percent of companies
more than 30 percent. Moreover,
three-fourths of executives expect that
of Directors is the primary influencer
of their Big Data adoption strategy—
indicated that big data
spending level to increase just in the
next year. (See Figure 1.)
more than those citing the CEO (47 analytics is either the
percent), the CIO (37 percent) or
a business line P&L executive (15 top priority for the
Across the industries surveyed, 80 to
90 percent of companies indicated percent). (See Figure 3.) company or in the top
that Big Data analytics is either the
top priority for the company or in the
This board-level influence particularly three.
stood out in several industries such
top three. This finding is especially as Mining, where the Board is the
strong in the Aviation industry, where top influencer for 73 percent of those
Figure 1:
Figure 1: InvestmentsWhat
in Big Data analytics are strong
portion of your overall technology expenditure is Do you expect this to increase, stay the same
made in analytics Big Data? or decrease over the next year?
1. What portion 3% 2. Do you expect
of your overall this to increase,
22%
technology stay the same or
expenditure is 24% decrease over 24%
made in Big Data the next year?
analytics?
76%
51%
More than 30% Increase
21%-30% Stay the same
10%-20% Decrease (0%)
Less than 10%
5
FigureFigure
2: 2: Big Data analytics is one of the top corporate priorities
How important is Big Data analytics relative to other
How important is Big Data analytics relative to other priorities in your company?
priorities in your company?
Aviation 61% 29% 10%
Wind 45% 45% 6% 3%
Power Generation 31% 63% 6%
Power Distribution 28% 56% 16%
Oil & Gas 31% 56% 9% 3%
Rail 40% 47% 10% 3%
Manufacturing 42% 45% 9% 3%
Mining 24% 55% 18% 3%
Top/highest priority Within the top three priorities Within the top five priorities Not a priority
Figure3:3: Support for Big Data analytics initiatives is coming from the top of the organization
Figure
Please rate the level of influence of each of the following in setting the strategy for Big Data analytics adoption
in your company.
Figure 2
Our Board of Directors 53% 32% 11% 1% 3%
The CEO 47% 39% 9% 2% 2%
The COO 28% 46% 19% 4% 2%
Business line P&L executive 15% 47% 31% 4% 2%
The CIO 37% 35% 21% 5% 2%
The CFO 22% 36% 29% 7% 5%
Mid-level management 10% 25% 44% 15% 6%
Our customers 17% 23% 31% 17% 11%
2%
6
The formula for the
Industrial Internet
The Industrial Internet can be described as a source of both
operational efficiency and innovation that is the outcome of a
compelling recipe of technology developments:
• Take the exponential growth in data volumes—that is, “Big
Data”— available to companies in almost every industrial
sector, primarily the ability to add sensors and data
collection mechanisms to industrial equipment.
• Add to that the Internet of Things, which provides even
more data—in this case about equipment, products,
factories, supply chains, hospital equipment and much
more. (Cisco predicts that by 2020 there will be 50 billion
“things” connected to the Internet, up from 25 billion in
2015.3) With new technologies such as data lakes, the
ability to capture and process such data is now a reality.
• Then add the growing technology capabilities in the area of
analytics—the ability to mine and analyze data for insights
into the status of equipment as part of Asset Performance
Management (APM), or the delivery of healthcare, and then
even to predict breakdowns or other kinds of occurrences.
• Finally, add in the context of industries where equipment
itself or patient outcomes are at the heart of the
business—where the ability to monitor equipment or
monitor patient services can have significant economic
impact and in some cases literally save lives.
The resulting sum of those parts gives you the Industrial
Internet—the tight integration of the physical and digital
worlds. The Industrial Internet enables companies to use
sensors, software, machine-to-machine learning and other
technologies to gather and analyze data from physical
objects or other large data streams—and then use those
analyses to manage operations and in some cases to offer
new, value-added services.
3. “The Internet of Things,” Cisco, http://share.cisco.com/internet-of-things.html.
7 7
A sense of urgency do not adopt a Big Data analytics
strategy in the next year risk losing
There is risk in not taking action now,
according to surveyed executives.
A striking finding from our survey market share and momentum. Asked to name their top three fears
was the sense of urgency felt by if they are unable to implement a Big
Executives are looking over their Data strategy in the next few years,
respondents in implementing Industrial shoulders at competitors as well.
Internet solutions. This is driven in part the number one answer was, “Our
Seventy-four percent said that their competitors will gain market share at
by the impact being felt at an industry main competitors are leveraging
level as well as the competitor level. our expense.” The second top answer
Big Data analytics proficiencies to was the concern that investors will lose
For example, 84 percent of those differentiate their capabilities with
surveyed indicated that the use of confidence in their company’s ability to
clients, investors and the media. grow. (See Figure 4.)
Big Data analytics “has the power to New entrants are also coming into
shift the competitive landscape for their industries, according to 93
my industry” within just the next year. percent of respondents, and these
A full 87 percent believed it will have newer entrants are leveraging Big
that power within three years. Eighty- Data analytics as a key differentiation
nine percent say that companies that strategy.
Figure 4: Companies are aware of the risks of not implementing a Big Data strategy soon
Figure 4:
If Ifwe are unable to implement our Big Data strategy in the next one to three years, my top three fears are:
we are unable to implement our Big Data strategy in the next one to three years, my top-three fears are:
Our competitor(s) will gain market 28%
share at our expense
66%
We will not be able to recover and 18%
“catch up” if we delay
45%
We will start to lose qualified talent 18%
to competitors
48%
Our investors will lose confidence in our 17%
ability to effectively grow our business
61%
Our product(s)/solution(s) cannot be 9%
competitively priced 52%
I don't believe there will be any 3%
impact 3%
We have already implemented our 5%
Big Data strategy
5%
Top
None of the above
2% Top 3
2%
8
About the research
Recognizing that Big Data analytics is the foundation of the
Industrial Internet, GE and Accenture fielded a survey in China,
France, Germany, India, South Africa, the UK and the United
States that explored the state of Big Data analytics and how
it is being viewed across eight industries. Sectors surveyed
were Aviation, Wind, Power Generation, Power Distribution,
Oil and Gas, Rail, Manufacturing, and Mining. A similar survey
was conducted for the US Healthcare industry and results
are integrated into this report. Companies represented had
revenues in excess of $150 million, with more than half of
them having revenues of $1 billion or more. More than half of
the respondents were CEOs, CFOs, COOs, CIOs and CTOs, and
the sample also included vice presidents and directors from
information technology, finance, operations and other cross-
functional management areas.
This study adds to the growing portfolio of thinking and reports
on this topic–one of those being the recent Accenture report,
Driving Unconventional Growth through the Industrial Internet of
Things (IIoT), which explored the opportunity the IIoT represents
and implications for the workforce. The report also outlines
seven steps companies can take to overcome challenges they
may encounter as they prepare to use and analyze the vast
amount of data they have at their disposal to generate new
revenue-producing products and services. The report is available
at http://www.accenture.com/us-en/technology/technology-labs/
Pages/insight-industrial-internet-of-things.aspx.
9
Moving to growth Predictive maintenance of assets is
one such area of focus, saving up to
flight time by using full flight data, “tip
to tail,” as well as using performance
and value creation 12 percent over scheduled repairs,
reducing overall maintenance costs
analytics to combine an aircraft’s flight
data, weather, navigation, risk data
Industrial companies are at varying up to 30 percent, and eliminating and fuel operation, can result in direct
stages of adoption of Big Data analytics breakdowns up to 70 percent.5 For bottom-line savings.
and, as with all new technologies, example, Thames Water Utilities Limited,
the largest provider of water and Smart buildings are another prevalent
a maturity curve is emerging that type of Industrial Internet solution. The
delineates the early adopters from those wastewater services in the UK, is using
sensors, analytics and real-time data city of Seattle, for example, is applying
who are at a more foundational level. analytics to building management data
One of the first stages in that maturity to help the utility respond more quickly
to critical situations such as leaks or to optimize equipment and related
curve is connecting operating assets processes for energy reduction and
and performing monitoring and problem adverse weather events.6
comfort requirements. The software
diagnosis. Industrial companies are Another example comes from the identifies equipment and system
focused on moving from this type of Oil and Gas industry, where one of inefficiencies, and alerts building
asset monitoring to areas of higher America’s premier regulated energy managers to areas of wasted energy.
operational benefits. By introducing providers, Columbia Pipeline Group, has Elements in each room of a building—
analytics and more flexible production placed a particular focus on pipeline such as lighting, temperature and
techniques, manufacturers, for instance, operations and safety. Using existing the position of window shades—can
could boost their productivity by as asset data integrated with digital then be adjusted, depending on data
much as 30 percent.4 visualizations, analytics and shared readings, to maximize efficiency.7
Industrial companies are addressing situational intelligence, pipeline operators
can respond to potential events even Although improving existing operations
their needs for better efficiency and through Big Data analytics is highly
profitability in two major categories: faster. This helps prioritize maintenance
tasks, resource allocation and capital valuable, it is, relatively speaking, low-
asset and operations optimization. hanging fruit. Moving up the maturity
In the area of assets, it’s clear that spend more effectively based on risk
assessment. curve are solutions that go beyond
Industrial companies are progressing being proactive to being predictive. For
in creating financial value by gathering The movement toward more example, a petrochemical producer
and analyzing vast volumes of machine sophisticated use of analytics is also can rely on predictive maintenance
sensor data. Additionally, some exemplified by fuel consumption to avoid unnecessary shutdowns
companies are progressing to leverage solutions in the airline industry. Fuel is and keep products flowing. Apache
insights from machine asset data to typically the largest operating expense Corporation, an oil and gas exploration
create efficiencies in operations and for an airline; over the past 10 years, and production company, is using
drive market advantages with greater fuel costs have risen an average of 19 this approach to predict onshore
confidence. percent per year. The ability to reduce and offshore oil pump failures to help
minimize lost production. Executives
Determine how your company compares with others in your industry along the
Industrial Internet maturity curve by engaging with the Industrial Internet Evaluator*
(gesoftware.com/IIEvaluator). See how others in your field are leveraging Big Data
analytics for connecting assets, monitoring, analyzing, predicting and optimizing
for business success.
* Note: Use of the Industrial Internet Evaluator is subject to the terms at the website referenced here.
4. “Industry 4.0: Huge potential for value creation 5. G. P. Sullivan, R. Pugh, A. P. Melendez and W. D. 7. “Accenture Analytics and Smart Building
waiting to be tapped,” Deutsche Bank Research, May Hunt, “Operations & Maintenance Best Practices: A Solutions are helping Seattle boost energy efficiency
23, 2014. Guide to Achieving Operational Efficiency, Release downtown,” Accenture, http://www.accenture.com/
3.0,” Pacific Northwest National Laboratory, US SiteCollectionDocuments/PDF/Accenture-Analytics-
Department of Energy, August 2010. and-Smart-Building-Solutions.pdf.
6. Press release, “Accenture to Help Thames Water
Prove the Benefits of Smart Monitoring Capabilities,”
March 6, 2014.
10“We’d like to take a more holistic approach to
asset maintenance—to look at an asset from
the point at which it went into service across
the entire lifecycle, leveraging analytics to
improve operations.”
Matt Fahnestock, Vice President IT Service Delivery,
NiSource Inc., Columbia Pipeline Group
“If you generate a small savings on each
flight, it translates to big savings at the end
of the year. Even a 1 percent savings can
translate into millions of dollars.”
Jonathan Sanjay, Regional Fuel Efficiency Manager,
Air Asia Berhad
“Using Big Data analytics can be powerful. It
moves us beyond being reactive and allows
industries to predict and prevent. There
are challenges with disparate data sources
and varying levels of quality. At Johnson
Controls, we are building an infrastructure
to standardize and manage information.
Ultimately, we want to be able to leverage
predictive analytics to prevent and solve
problems, while continuously improving
processes.”
Craig Williams, Vice President, Quality,
Johnson Controls Power Solutions
11at Apache claim that if the global Oil
and Gas industry improved pump
throughput metrics. The hospital
was able to achieve shorter lag But are companies
performance by even 1 percent, it
would increase oil production by half
time between discharge and patient
pickup, with most ambulatory patients up for the
a million barrels a day and earn the
industry an additional $19 billion a
on their way in about 30 minutes.
These achievements are all the more challenge?
year.8 impressive given that the hospital’s Are companies ready for more
census continues to rise: the average predictive and innovative kinds of
The Healthcare industry provides patient age is 74 years, and 85 percent
another example. Technology tools are value-creating solutions? The answer
of admissions come through the ED.10 here is mostly “Not yet,” but they are
enabling providers to collect health data
in real time and then use advanced As companies master these higher-level actively positioning themselves for
predictive analytics techniques to help capabilities they can also move into such solutions. Asked to describe their
uncover what will likely happen next. innovative, revenue-generating services. current capabilities in Big Data analytics,
By proactively measuring, monitoring For example, a global energy company almost two-thirds of respondents (65
and managing this data, providers is leveraging analytics to analyze tens percent) are focusing on monitoring—
can improve care management and of thousands of data points in a wind the ability to monitor assets to identify
address risk factors and symptoms farm every second. With this data, operating issues for more proactive
of chronic disease early and provide the company can use data science maintenance. Fifty-eight percent
positive reinforcement in new and more to direct a set of performance dials have capabilities such as connecting
effective ways. and levers (speed, torque, pitch, yaw, equipment to collect operating data and
aerodynamics and turbine controls) to analyzing the data to produce insights.
One leading US health system’s work fine-tune a wind turbine’s operation and However, only 40 percent can predict
in infection, or sepsis, management help enhance its energy production. By based on existing data, and fewer still
is an example of the power of having this level of control with a single (36 percent) can optimize operations
predictive analytics to improve clinical turbine and leveraging this technology from that data. (See Figure 5.)
delivery. Recognizing that sepsis is a across a farm, energy providers can
leading driver of in-hospital mortality, This finding is validated by other
gain up to 5 percent improvement responses. When asked about their
the medical center defined early on power output. With an integrated
leading indicators of sepsis and used progress in managing business
approach to providing fuel-powered operations, only one-fourth said they
technology tools to monitor patients to energy as well as renewable-produced
drive earlier diagnosis and intervention. had predictive capabilities and only 17
energy, analytics can contribute directly percent indicated the ability to optimize.
The new initiative saved hundreds of to new revenue streams with positive
lives and has saved millions of dollars In a separate query, when asked about
bottom-line impact. capabilities on the analytics spectrum
for the health system.9
Intelligence-based services are likely from connect to monitor to analyze
In another case, a leading Florida- to be the answer to “What’s next?” in to predict to optimize, answers were
based hospital and medical center the realm of information technology primarily on the lower end of that
used real-time tracking and analytics and the Industrial Internet. One of spectrum. Only 13 percent indicated the
to optimize patient flow, cutting the executives we surveyed as part ability to optimize, and 16 percent said
emergency department (ED) wait times of our research offered an insight they did not fall on the spectrum at all.
by 68 percent. Upon admission, an ED behind the urgency to implement more (See Figure 6.) However, connecting,
patient receives a tag. A dashboard innovative kinds of Industrial Internet monitoring and analyzing are necessary
then begins monitoring the patient’s solutions based on Big Data analytics: precursors to development of predictive
journey, combining patient Real-Time- information technology needs to move models and optimization capabilities,
Location System (RTLS), interfaces from the era of automation-based so the advancement of industrial
and bed placement timestamps to savings alone to an era of intelligence companies along the maturity curve
evaluate and display real-time patient and value creation. positions them to take advantage of
more sophisticated Big Data analytics.
8. Scott MacDonald and Whitney Rockley, “The
Industrial Internet of Things,” McRock Capital.
9. “Better Than a Crystal Ball: The Power of Prediction
in Clinical Transformation,” Accenture, http://www.
accenture.com/SiteCollectionDocuments/PDF/Accenture-
Cystal-Ball-Power-Clinical-Transformation.pdf.
10. “Losing the Wait,” GE Healthcare.
12Figure 5: Current Big Data analytics capabilities are stronger in the areas of monitoring and connecting equipment than in
Figure 5:
predicting issues and optimizing operations
In my company, our current capabilities around Big Data analytics include the ability to: (Multiple responses.)
In my company, our current capabilities around Big Data analytics include the ability to (multiple responses):
Monitor equipment/assets to identify operating
65%
issues for more proactive maintenance
Connect equipment/assets and collect
58%
operating data
Analyze data to provide useful insights 58%
Gain operational insights that lead to better
57%
decisions
Consolidate and correlate data from various sources
to feed analytic insights 48%
Predict based on existing data 40%
Optimize (e.g., operations, workforce
36%
efficiencies, business decisions)
Other 0%
None of the above 2%
Source: GE Insights, September 2014 Base: Total sample; n=254
Q10
Figure 6: Companies’ Big Data capabilities are strongest in the area of analysis
Figure 6:
On averageOn average
across across where
the company, the company, where do
do your company's Bigyour
Datacompany’s big data
analytics capabilities fallanalytics capabilities
on the spectrum below? fall on the spectrum below?
35%
19%
18%
16%
13%
Connect Monitor Analyze Predict Optimize
Source: GE Insights, September 2014
Figure 5 13Moving However, when asked about future
plans, respondents stated their
from today’s priorities in more ambitious plans
for analytics: increasing profitability
implementation (60 percent), gaining a competitive
advantage (57 percent) and improving
to tomorrow’s environmental safety and emissions
(55 percent) represent more pervasive,
strategies cross-functional and sophisticated use
of analytics.
What does the roadmap of surveyed Breaking this out by business line,
companies look like in the next one individual strategies emerge for
to three years? Understandably, initial particular industries. As shown in
investments are focused in areas Figure 7, survey respondents were
representing the connection and asked what their top three priorities
monitoring of assets for improving the were for the next one to three years.
ability to react and repair and move The shaded areas indicate the
toward zero unplanned downtime. highest-ranked priorities, by industry.
Figure 7: Top business priorities, by industry
Highest-ranked priorities
Power Power
Priorities: 1-3 years Aviation Wind Generation Distribution Oil & Gas Rail Manufacturing Mining
Increase profitability 61% 71% 56% 59% 56% 67% 58% 55%
through improved resource
management
Gain a competitive edge 58% 55% 53% 69% 50% 50% 76% 48%
Improve environmental 39% 61% 50% 75% 59% 43% 52% 58%
safety and emissions
Gain insights into customer 58% 61% 47% 56% 38% 60% 70% 39%
behaviors, preferences and
trends
Gain insights into 55% 48% 34% 56% 47% 73% 67% 39%
equipment health for
improved maintenance
Drive operational 42% 48% 41% 72% 44% 53% 55% 64%
improvements and
workforce efficiencies
Create new business 45% 61% 34% 53% 47% 40% 52% 58%
opportunities with new
revenue streams
Meet or exceed regulatory 32% 39% 41% 63% 50% 33% 39% 39%
compliance
14“In the ’60s through the ’90s, railroads
focused on manpower reduction by
automating processes. But we have greatly
exhausted that. Now the focus is on better,
more informed and intelligent decisions. This
is coming from several directions, but top
down more so than bottom up.”
Fred Ehlers, Vice President - Information Technology,
Norfolk Southern Corporation
The impact of unplanned downtime on industrial
companies is real and significant. See how
unplanned downtime impacts industries from
Aviation, to Oil and Gas, to others. Learn more.
(gesoftware.com/the-power-of-ge-predictivity)
15Big Data analytics in
the healthcare industry:
A diagnosis
Among the healthcare organizations we surveyed as
part of our Industrial Internet research, an overwhelming
majority acknowledged the critical role of analytics
in driving improved clinical, financial and operational
outcomes. These organizations feel that analytics will
have the power to dramatically improve patient outcomes,
even in the next year. However, challenges around system
barriers between departments, budgetary constraints and
organizational obstacles are impeding implementation of
their analytics initiatives.
“In the past, decision-making was more
straightforward—doctors simply made a decision based
on knowledge of the domain, personal experience, and
evaluation of the patient's physical signs and symptoms
plus relevant diagnostic laboratory data. Now there is
much more data available to the clinician that requires
additional expertise and having the right people with
the right skills to interpret the data—biostatistics,
epidemiology, health informaticists, other health
professional clinicians, and so forth. Caring for patients
is now a team activity, and learning to work in teams is
an important skill for physicians to acquire.”
Christopher C. Colenda, MD, MPH
President and Chief Executive Officer,
West Virginia United Health System
16Big Data analytics in the healthcare industry: A diagnosis
Positive outcomes profitability as an important business
impact of analytics.
focused respondents (compared
with 25 percent of clinical-focused
More than half of the healthcare respondents) looked to the outcome
In the next one to three years, these of predictive analytics that provides
executives surveyed believe that
healthcare organizations see Big actionable insights into opportunities for
analytics can drive a variety of positive
Data analytics driving several kinds operational improvements.
outcomes for their organizations,
of positive results in particular. The
including improved diagnostic speed
top outcome named (by 44 percent Asked to name their best current
and confidence (named by 54 percent
of respondents) was the ability capabilities around analytics, top
of respondents); reduction in patient
of analytics to integrate a view of answers focused on improving
wait times and length of stay (56
clinical, financial and operational patient flow (56 percent); tracking and
percent); and better clinical outcomes
data—data that is currently spread monitoring the utilization of healthcare
and patient satisfaction scores (59
across multiple disparate systems. equipment (49 percent); tracking
percent). Fifty-seven percent of
The second outcome cited was clinical, financial and operational
respondents overall—and 66 percent
the ability to provide unified patient measures (46 percent); and managing
of operations-focused respondents
records (38 percent). Perhaps not workforce productivity and engagement
—named improved healthcare system
surprisingly, 34 percent of operations- (46 percent). (See Figure 8.)
Figure 8: Healthcare companies’ strongest capabilities in Big Data analytics
In my organization, our current capabilities around analytics include the ability to:
(Multiple responses)
56%
59%
Improve patient flow 58%
49%
Track and monitor the utilization and location of 51%
healthcare equipment 46%
46%
View/track clinical, financial, and/or operational 43%
performance measures 48%
46%
Manage workforce productivity and engagement 47%
50%
38%
Streamline workflows 41%
36%
36%
Optimize clinical procedures to drive improved patient 31%
outcomes 40%
36%
Connect information across the care continuum 37%
40%
33%
Consolidate and correlate patient data for analytic 29%
insights 38%
31%
Proactively manage defined patient groups/populations 33%
32%
31%
Optimize reimbursement rates 31%
30%
31%
Benchmark performance against my peers across 27%
clinical, financial, and/or quality performance measures 34%
Overall (n=61)
26%
Minimize payment cycles 27% Clinical (n=51)
24%
Operations (n=50)
17Big Data analytics in the healthcare industry: A diagnosis
Shaking up the leveraging analytics as a key strategy
over the past two to three years.
Expectations are
healthcare space The threat of analytics-based high and driven
Big Data analytics is both a competition is on the minds of
healthcare executives, especially if
by the Board
promise and a threat to healthcare
organizations. Three-fourths of they are unable to integrate analytics Overwhelming percentages of
those surveyed believe that the use into clinical and operating processes healthcare respondents are already
of analytics has the power to drive in the coming years. Seventy-four seeing positive outcomes from their
a productivity transformation in percent of respondents named “losing analytics investments. Ninety percent
healthcare in the next year, and 87 qualified talent to competitors” as one or more of healthcare organizations
percent believe it will do so over the of their three greatest fears; another lay claim to having successfully
next three years. 70 percent were concerned that their implemented analytics related to
financial performance would cease improving patient outcomes and to
Eighty-four percent of respondents to be competitive in the marketplace; driving improvements in operational
agree that healthcare providers who two-thirds feared that other healthcare efficiency.
adopt an analytics strategy in the providers would make greater
next one to three years will outpace headway in providing the highest- Relative to their competitors,
their peers in the marketplace. And quality care. (See Figure 9.) about one-third of healthcare
74 percent have seen competitors organizations (31 percent) claim
that they are significantly ahead of
the game in the area of analytics,
with another 39 percent saying they
are at least somewhat ahead of the
Figure 9: Top concerns of companies if they are unable to effectively integrate competition. Only 2 percent of those
analytics capabilities surveyed claim to be lagging behind
competitors in this area.
If we are unable to integrate analytics into our clinical and operating
process in the next one to three years, my top three fears are: A look at investment levels reveals
that healthcare companies are
We will start to lose qualified
74% not investing to the same level as
75% industrial companies, but percentage
talent to competitors 74%
of budget is still significant. About
70%
half of all healthcare organizations
Our financial performance
69% surveyed (clinical, 53 percent;
will cease to be competitive
in the marketplace
74% operations, 50 percent) are investing
from 11 to 20 percent of their
66% overall technology budget on Big
Other healthcare providers will 65%
make greater headway in providing 68%
Data analytics. About one-third are
the highest-quality care investing more than 20 percent; by
contrast, 73 percent of industrial
61%
We will not be able to effectively 63% companies are investing at that level.
integrate our operations across 60% (See Figure 10.) Asked to name their
the continuum of care
top three challenges in implementing
2% analytics solutions, the number one
I don't believe there will 2%
be any impact response was “budget constraints
are slowing our analytics initiatives.”
2%
We have already implemented 2%
our analytics strategy 2%
Overall (n=61)
7% Clinical (n=51)
None of the above 6%
6% Operations (n=50)
18Big Data analytics in the healthcare industry: A diagnosis
Even if investment is not at the Figure 10: Percentage of technology spend on analytics initiatives
same levels as industrial companies,
executive commitment is strong: Big What portion of your overall technology expenditure is made in
Data analytics strategies are being analytics initiatives?
driven from the very top of these
organizations. Eighty-two percent
of respondents said their Board of Overall (n=61) 34% 49% 13% 3%
Directors is either a primary or strong
influencer of the analytics adoption
strategy at their company. Almost as Clinical (n=51) 31% 53% 14% 2%
many (77 percent) named the CEO as
a driving force. By contrast, just 43
percent named the CIO as the strong Operations (n=50) 34% 50% 12% 4%
or primary influencer and 52 percent
named the COO.
More than 20% 11%-20% 5%-10% Less than 5%
An urgency to
deliver improved
patient outcomes
Healthcare organizations, unlike
Figure 11: Perceptions of competitors’ analytics capabilities
their industrial counterparts, have a
greater focus on how analytics can My understanding of other healthcare providers with analytics capabilities is
drive better patient care rather than that they: (Multiple responses)
as a means to achieve competitive
advantage. For example, the
perceived threat level posed by 54%
Are gaining analytic
analytics-based competition appears 59%
insights in at least one
to be lower than among the industrial area of their operations 58%
companies surveyed. There, recall,
74 percent said that their main 52%
View analytics as a
competitors are leveraging Big Data strategy to drive improved 51%
analytics proficiencies to differentiate patient outcomes 56%
their capabilities. Only 30 percent of
Have made significant 46%
healthcare executives had that fear.
progress in the ability to
49%
capture and store data
Instead, the power of analytics to
for analytic purposes 48%
improve patient outcomes was a
greater concern for respondents. Have publicly stated 44%
Over half (54 percent) stated that their their intent to optimize 45%
competitors were already gaining their operations by
leveraging analytics 48%
analytic insights in operations and
52 percent thought their competitors Are leveraging their 30%
viewed analytics as a strategy to drive analytics proficiencies
to differentiate 25%
patient outcomes. (See Figure 11.)
figure 10
their capabilities 36%
7%
Have no visible plans to Overall (n=61)
leverage analytics 4%
Clinical (n=51)
6%
Operations (n=50)
19Big Data analytics in the healthcare industry: A diagnosis
The top three capabilities targeted for
development in the next three years
Talent issues shortfalls. Asked to rank their top three
challenges, only 23 percent named
indicate that healthcare organizations What kinds of talent and “Talent acquisition is impacting our
are planning on building out the competencies will be needed in the ability to understand and realize the
infrastructure required for leveraging analytics area in the coming years potential from our collected data.”
analytics. Forty-four percent said they to help healthcare organizations
are planning to build an integrated Perhaps related to this last point is
succeed? Two-thirds of respondents
data source for patient information; the fact that healthcare executives are
named patient-care analytics as the
43 percent noted plans to create an more open than their industrial peers
most important competency; 51
analytics platform for managing large to using external analytics providers.
percent cited software development/
volumes of data; and 41 percent Sixty-one percent intend to pursue
engineering. Far fewer (38 percent)
claimed to be developing analytics relationships with providers who are
cited the need for data scientists.
capabilities that drive improvements in experts in their industry and who
clinical performance. (See Figure 12.) The surveyed executives seemed can quickly translate their needs into
relatively unconcerned about talent analytics solutions.
Figure 12: Top analytics capabilities targeted for development
Which of the following are you planning to build or grow over the next three years? (Multiple responses)
Integrated data source for 44%
patient information 45%
48%
Analytics platform for managing 43%
large volumes of data 39%
48%
Analytics capabilities that drive improvements 41%
in clinical performance 41%
44%
Automated tracking of patient 38%
and staff flow 35%
40%
Mobile capabilities for improved staff 34%
productivity/patient care 35%
36%
Adoption of cloud-hosted model 34%
for analytics solutions 31%
36%
Automated external reporting 31%
(e.g., CMS, Joint Commission, MU) 29%
30%
31%
Tracking and reporting compliance 33%
34%
Monitoring healthcare equipment 28%
to ensure greater availability 27%
32%
Analytics capabilities that drive improvements 25%
in financial performance 24%
28%
Analytics capabilities that drive improvements 25%
in operational performance 25%
22%
21%
Enterprise data warehouse 22%
20% Overall (n=61)
18% Clinical (n=51)
Automating manual workflows 16%
18% Operations (n=50)
20Big Data analytics in the healthcare industry: A diagnosis
Driving better patient to realize their vision? With outcomes
such as better clinical results,
“Being successful at Big
outcomes improved profitability and improved Data requires putting the
diagnostic confidence (see Figure
Healthcare organizations clearly 13), it is unlikely that any provider will foundational elements
understand the potential of analytics
to drive better patient outcomes
wish to lag in realizing the wide range in place—allocation of
of benefits that analytics can deliver.
and operational efficiencies. With strategy, capital and
board-level support, will they be
able to translate that commitment
mindshare.”
to budgetary support to build the David Hefner, CEO (retired), Georgia
right infrastructure, overcome system
Regents Medical Center
barriers and attract the talent needed
Figure 13: Likely outcomes delivered by analytics capabilities
Outcomes most likely to be impacted by analytics in our organization include: (Multiple responses)
Better clinical outcomes and patient 59%
satisfaction/HCAHPS scores 61%
62%
57%
Improved healthcare system profitability 55%
66%
56%
Reduction in patient wait
55%
times and/or length of stay
54%
54%
Improved diagnostic speed and confidence 57%
54%
51%
Increased clinician and
53%
workforce productivity
54%
Reduction in operating costs through 49%
improved asset management 51%
54%
Improved coordination across 48%
the care continuum 47%
48%
38%
Reduction in cost of treating 39%
chronic disease
38%
Reduction in preventable 33% Overall (n=61)
adverse events (e.g., HAIs) 31% Clinical (n=51)
34%
Operations (n=50)
21Becoming an
Industrial Internet
value creator
What can companies do today to start
advancing their Industrial Internet capabilities
on the maturity curve to more value-
creating activities? Based on our research
and experience, here are several actions to
consider.
22Invest in end-to- have end-to-end security in place
against cyber-attacks and data leaks.
• Enforce security throughout
the supply chain. Incorporate
end security This has enterprise-wide implications.
The tools and technologies
robustness testing, and require
security certifications in the
The value of the Industrial Internet leveraged to protect company- procurement process to ensure
is being brought to bear due to wide assets would be appropriate vendor alignment.
the confluence of a multitude in the operational technology (OT)
environment as well. IT and OT leaders • Utilize mitigation devices
of technology enablers such as designed specifically for
cloud, mobility, Big Data and responsible for security policies
related to the Industrial Internet should Industrial Control Systems
analytics. These technologies, (ICS). Use the same effort given to
while innovative and even game- consider the following best practices:
the IT side to ensure ICS-specific
changing, nevertheless can expose • Assess the risks and consequences. protections against industrial
a company to security risks. Indeed, Use experts to evaluate and fully vulnerabilities and exploits on the
the survey found that one of the top understand vulnerabilities and OT side.
three challenges to deliver on the regulations to prioritize the security
promise of the Industrial Internet budget and plan. • Establish strong corporate buy-
is security (35 percent). Security in and governance. Gather internal
is of special concern in the Power • Develop objectives and goals. champions, technical experts,
Generation sector. (See Figure 14.) Set the plan to address the most decision-makers and C-level
important systems with the biggest, executives to ensure funding and
Although these results are not most impactful and immediate risks. execution of industrial security best
surprising, what is concerning is that practices.
less than half (44 percent) feel they
Figure 14: Percentage of companies, by industry, that named security as a top three challenge
Security concerns are impacting our ability to implement a wide-scale Big Data initiative
Aviation 32%
Wind 39%
Power Generation 31%
Power Distribution 44%
Oil & Gas 34%
Rail 37%
Manufacturing 27%
Mining 39%
Security concerns are impacting our ability to implement a wide-scale big data initiative
23Break down the enterprise. More prevalent are initiatives
in a single operations area (16 percent)
Data management itself will be a core
skill set. Industrial companies report
barriers to data or in multiple but disparate areas (47
percent).
that a vast amount of the time is
consumed by accessing, cleansing,
integration The lack of an enterprise-wide analytics
manipulating and consolidating
machine data before data scientists
vision and operating model often can examine the resulting datasets
Asked to name the top three results in pockets of unconnected
challenges faced in implementing Big to create predictive models. Breaking
analytics capabilities, redundant down organizational, data and system
Data analytics initiatives, the answer initiatives and, perhaps most important,
most frequently appearing (36 percent) silos will be both a requirement and an
limited returns on analytics investments. outcome of companies implementing
was “System barriers between New technologies such as data lakes,
departments prevent collection and their Big Data strategies—at least
combined with Industrial Internet the ones that hope to generate the
correlation of data for maximum capabilities, enable operators to funnel
impact.” In addition, for 29 percent of greatest benefits from their efforts.
sensor data from various networked
executives, a top-three challenge was machines onto a single platform. From Given these findings about data silos,
in the consolidation of disparate data there, massively parallel processing it is not surprising that our survey data
and being able to use the resulting data capabilities analyze the data as a shows a move toward centralization
store. (See Figure 15.) unified whole rather than as a billion of the analytics function in one
All in all, only about one-third of separate bits of information, each with way or another. For 50 percent of
companies (36 percent) have adopted its own individual file path.11 executives surveyed, their companies
Big Data analytics across the are moving toward either an overall
Figure 15: Top challenges in implementing Big Data initiatives, overall
Please rank the top three challenges your organization faces in implementing Big Data initiatives:
Security concerns are impacting our ability to implement 14%
a wide-scale Big Data initiative 35%
Consolidation of disparate data and being able to 13%
use the resulting data store are difficult 29%
System barriers between departments prevent collection and 12%
correlation of data for maximum impact 36%
9%
Quality and cost of collecting machine data are a barrier
23%
The integrity of the network for transmission of 9%
massive amounts of data is not reliable enough 28%
Talent acquisition is impacting our ability to understand and 8%
realize the potential from our collected data 26%
Organizational barriers prevent effective 7%
cross-departmental use of analytics 22%
6%
Poor data quality or lack of confidence in the data
26%
Budget constraints are slowing our Big Data 6%
analytic initiatives 26%
5%
Reliance on multiple vendors–no integrated solutions
20%
Other 0%
We are not experiencing any challenges 10% Top
with our Big Data initiatives 10% Top 3
11. Ideas Lab, “Trawling for Big Insight in the ‘Industrial Data Lake,’”
GE Ideas Lab Staff, August 15, 2014.
24“We aren’t planning to just aggregate Big Data.
We are gearing up to re-engineer the business
around this capability.”
Matt Fahnestock, Vice President, IT Service Delivery, NiSource Inc.,
Columbia Pipeline Group
“The biggest challenge was the data itself—
to get it to the right system and to the right
person. It seems so easy for data to be
transferred, but it’s not—it’s much more
difficult than people realize.”
Jonathan Sanjay, Regional Fuel Efficiency Manager, Air Asia
25“We had more data centralized group to manage Big Data
analytics initiatives or a coordinating Focus on talent
than we could actually group within the IT function. Half of
acquisition and
these companies (49 percent) also
use; it was good to
have this information,
intend to appoint a Chief Analytics
Officer responsible for business and development
implementation strategies concerning
but you need resources analytics. (See Figure 16.)
Executives surveyed are aware of their
own talent shortfalls in the area of Big
to analyze the data, Bringing the OT and IT divisions Data analytics and the critical nature
of sourcing and developing the talent
derive best practices together to deliver on the value of the
Industrial Internet will be key to driving needed to succeed in these areas.
and generate new maximum benefits. Only 26 percent About half of those surveyed note
that they have talent gaps in several
are considering merging the IT and
flight plans. There were OT organizations to deliver analytic critical areas including analyzing data,
interpreting results, and gathering and
not enough resources solutions. IT/OT convergence is an
important objective because: consolidating disparate data. (See
to interpret the data.” Figure 17.)
• Two of the top three challenges as
Jonathan Sanjay, Regional Fuel discovered in the survey—system Hiring talent with the expertise
barriers between departments needed is the most obvious remedy
Efficiency Manager, Air Asia
(36 percent) and disparate data to the talent gap issue, named by 63
(29 percent)—would be greatly percent of survey respondents. Yet
mitigated by being addressed by the fact is that there won’t be enough
“Once standards jointly held OT/IT responsibility. The experienced talent to go around in this
and practices are OT executives would have clear burgeoning area of Big Data analytics.
Indeed, shortages in the number of
visibility of operational processes,
established, it data stores and usage, while the data scientists are projected, as well
as the number of managers capable of
becomes easier and IT executives would have the
line of sight to new technologies using Big Data analyses to make good
more manageable that would help mitigate the data decisions. Another option favored by
55 percent of executives is to partner
integration issues.
to carry out higher with organizations such as universities
• As other organizations leverage to groom the talent needed. This is
and higher levels of asset data outside of the Operations an option being used at one of the
IT/OT integration that arena, such as in Finance for capital aviation companies surveyed.
management purposes, the need for
go beyond time and consolidation and business-focused The use of skilled external talent—
experts in an industry who can quickly
costs savings to value analytics to derive valuable insights
will drive the OT/IT convergence. translate business needs into analytics
creation via data solutions—is also an option favored
by more than half of respondents (54
visibility and agile percent). (See Figure 18.)
availability of data.” When it comes to retaining talent for
augmenting internal skills, industry
IT and Operational Technology knowledge is key to success (30
Alignment Innovation Key percent), exceeding analytics talent
Initiative Overview, alone (24 percent). However, it is those
Kristian Steenstrup, who hold both industry knowledge
and analytics skills who would be
Vice President and Gartner Fellow,
preferred by most industrial companies
Gartner Research, 26 March 2014 (43 percent). (See Figure 19.)
26Figure 16: Anticipated organizational changes to implement Big Data analytics
Which of the following organizational changes have occurred or do you expect will occur to support your company’s
use of analytics? (Multiple responses)
A centralized group will be formed that manages all Big
Data analytic initiatives 50%
A group within our IT organization will lead all
analytic initiatives 50%
A Chief Analytics Officer will be appointed,
responsible for our business and implementation 49%
strategy around analytics
A group within our OT (operations technology)
organization will lead analytics initiatives 29%
Our IT and OT organizations will either merge or
26%
jointly lead analytics activities
None of the above 3%
Figure 17: Talent gaps in the area of Big Data analytics
In which of the following areas do you have gaps in your talent? (Multiple responses)
Analyzing data 56%
Interpreting results 48%
Gathering and consolidating disparate data 48%
"Bridge" roles (people with ability to analyze data,
42%
interpret and tell the story)
Storytelling 28%
Other 0%
We have no talent gaps 9%
figure 16
27Figure 18: Strategies to fill talent gaps in Big Data analytics
Which of the following will your company pursue to ensure you have the talent needed to fulfill
your Big Data analytics strategy?
Hire new talent with the expertise we need 63%
Partner with organizations that have the talent we
need (e.g., universities, specialty companies, 55%
technology vendors)
Work with Big Data analytics providers who are
experts in our industry that can quickly translate 54%
our needs to analytic solutions
Use existing in-house resources (provide training
as needed) 46%
Acquire companies with Big Data analytics
expertise 39%
Work with Big Data analytics providers who have deep
expertise in the field of Big Data analytics and Big Data 33%
processing (but not necessarily in my industry)
Other 0%
When choosing an outside consultant for a Big Data Analytics initiative, I would choose
Figure 19: Desired qualities in outside consultants in Big Data analytics
someone with:
When choosing an outside consultant for a Big Data analytics initiative, I would choose someone with:
24%
30%
Deep industry knowledge
73%
3% Both industry knowledge and analytics
43% experience
Analytics cross-industry experience N/A, we do not hire outside consultants
for Big Data analytics initiatives
figure 18
28“Talent acquisition is difficult in the
maintenance-engineering world. Experience
is a good thing, but Qantas has a relationship
with universities where we recruit double
degree majors: aero engineering and
computer programming. Personally, I feel
that this is the best combination of skills.”
Bertrand Masson, Manager Aircraft Performance
and Fleet, Qantas Airways Ltd.
29“When it comes to incident response, our
regulators are requesting that we review
and plan with so much more information
than before. It’s now in one data mart; all
of the information is available and will
play a large role in saving us time and
money in the whole regulatory process.”
Matt Fahnestock, Vice President, IT Service Delivery,
NiSource Inc., Columbia Pipeline Group
30Consider new Begin by asking: “What product-
service hybrids beyond remote
It is also important to think about
tomorrow’s partner ecosystem.
business models monitoring and predictive asset
maintenance resonate with our
Companies will work with partners
and suppliers to create and deliver
needed to be customers and our customers’
customers? What product, service and
services as well as reach potential new
customers. Think of the partnering
successful with the value can we deliver to clients? How
prepared are we to accelerate our
taking place among farm equipment,
fertilizer and seed companies, and
Industrial Internet move toward a services-and-solutions
business model? How do we develop
weather services, and the suppliers
needed to provide IT, telecom,
and add the talent we need to be sensors, analytics and other products
To begin moving up the maturity curve
successful?” and services. Ask: “Which companies
of Industrial Internet solutions, it is
are also trying to reach my customers
important to think boldly about the Focus on rapidly progressing to and my customers’ customers? What
new business models needed. As predictive analytics and optimization other products and services will talk to
noted earlier, digital services based capabilities to derive the greatest value mine, and who will make, operate and
on Big Data analytics capabilities from operational insights. service them? What capabilities and
represent an important evolution of the Asset Performance Management information does my company have
Industrial Internet. Some companies (APM), at its baseline level, delivers that they need? How can we use this
are already converting products into value to industrial companies by ecosystem to extend the reach and
product-service hybrids—intelligent monitoring availability and performance scope of our products and services
physical goods capable of producing of assets across the entire enterprise. through the Industrial Internet?”
data for use in digital services. These However, predicting equipment
services enable companies to create outages for proactive action, before a
hybrid business models, combining catastrophic event can occur, results
the benefits of operational efficiency in significantly greater value with
with recurring income streams from increased overall productivity. Taking it
digital services. These digital services to the next level–optimization–will allow
will also enable firms in resource- for greater insights that can be used
extracting and process industries to for business trade-offs. For example,
make better decisions, enjoy better with complete visibility into output from
visibility along the value chain and a fleet of power generation plants, an
improve productivity in other ways. energy trader can execute optimal
transactions in the market, leading to
greater profitability.
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