GE’s Jeff Immelt on digitizing in the industrial space McKinsey Company
Summary
TLDRThe transcript discusses the digital transformation of industrial companies, using the example of a jet engine with sensors generating massive data. The company's decision to embrace analytics as core to its future is highlighted, akin to material science's importance in the past. The speaker emphasizes the need for internal change, including hiring data scientists and altering business models to compete in the industrial internet space, aiming to capture value from digitization and drive productivity.
Takeaways
- 🌐 **Evolutionary Digitization**: The company's shift to digital was not a sudden decision but an evolution driven by the industries and technologies they serve.
- 🚀 **Data-Driven Industry**: Modern industrial equipment, like jet engines and locomotives, generate vast amounts of data, making industrial companies part of the information business.
- 📈 **Analytics as Core**: The company views analytics as a core competency, just as material science has been over the past 50 years, and plans to integrate it deeply into their operations.
- 💡 **Business Model Transformation**: The company is considering changing its business model to better leverage the data and analytics, similar to how IT companies operate.
- 🔄 **Decision to Go 'All In'**: They have decided to fully embrace analytics rather than outsourcing, aiming to be at the forefront of the industrial internet space.
- 🛠️ **Building In-House Capabilities**: Instead of acquiring or partnering, the company chose to build its own analytics capabilities, starting with a center in California.
- 🚆 **Impact on Customers**: For instance, increasing the velocity of locomotives by just one mile per hour can significantly impact profits for rail companies.
- 💼 **Internal Changes**: The company is focusing on internal changes, including hiring new talent, altering business models, and embracing a digital culture.
- 📊 **Revenue from Software**: They have seen revenue growth from software applications, aiming for a digital thread from engineering to the installed base.
- 🌟 **Dual Strategy**: The company is pursuing being both a platform and an application company, offering a platform for customers to build their own applications.
- 👥 **Cultural and Talent Shift**: Recognizing the need for a different type of talent, including product managers and salespeople, and the importance of blending new hires with the existing team.
Q & A
What is the significance of digitization in the industrial world according to the speaker?
-The speaker emphasizes that digitization in the industrial world is not a choice but an evolutionary necessity driven by the technology and industries they serve. It's about leveraging data from sensors in machines like jet engines or locomotives to optimize performance and efficiency.
How much data can a single flight between New York City and Chicago produce?
-A single flight between New York City and Chicago can produce a terabyte of data, highlighting the vast amount of information generated by modern industrial machinery.
What is the company's stance on handling the data and analytics in-house?
-The company has decided to be 'all in' on analytics, treating it as core to the company's future as material science has been in the past. They aim to evolve their business model and service agreements to share outcomes with customers, similar to how IT companies operate.
What was the company's approach to building its analytics capabilities?
-The company chose to build its analytics capabilities internally rather than through acquisition or partnership. They brought in talent from outside, built a center in California, and started developing applications with customers.
How does the company plan to integrate digital technology into its service business?
-The company is integrating digital technology into its service business by building applications that can improve efficiency and productivity. They aim to push these applications back into the company to improve internal operations as well.
What is the potential impact of improving locomotive velocity by one mile per hour for a company like Norfolk Southern?
-Improving the velocity of a locomotive by just one mile per hour, from 22 to 23 mph, could be worth $250 million in annual profit for a company like Norfolk Southern, demonstrating the significant financial impact of analytics in industrial operations.
What is the company's strategy regarding its digital platform and applications?
-The company is pursuing a dual strategy of being both a platform and an application company. They have developed a platform called Predix and are building applications on top of it. They are also opening up their platform to customers to encourage them to develop their own applications.
How has the company's approach to hiring and talent acquisition changed due to digitization?
-The company has significantly increased its hiring of data scientists and other technology professionals. They are also changing their product managers, salespeople, and on-site support to align with the new digital focus, and are recruiting differently, including looking for different skills when hiring from college campuses.
What internal changes is the company undergoing to adapt to the digital age?
-The company is undergoing a cultural simplification, reducing layers, processes, and decision points. They are embracing Silicon Valley tools like fast works, and are democratizing information within the company with contemporary IT tools and a mobile-first approach.
How does the company view the importance of digitization in the current era for industrial CEOs?
-The company views digitization as the most critical issue for CEOs in the current era, suggesting that failing to embrace it could lead to significant competitive disadvantages and missed opportunities for value creation.
Outlines
🔧 Industrial Digitization and Data Analytics
The speaker discusses the transformative impact of digitization on the industrial sector, emphasizing that it's not a sudden shift but an evolutionary process. They highlight the example of a jet engine equipped with sensors that generate a terabyte of data per flight, illustrating the scale of data industrial companies now handle. The company's decision to embrace analytics as a core competency is outlined, with a commitment to treat it with the same importance as material science has been in the past. The speaker also addresses the strategic decision to develop in-house analytics capabilities rather than outsourcing, leading to the establishment of a technology center and the integration of analytics into service agreements. The potential for industrial companies to capture significant value from the industrial internet is also discussed, with a warning against complacency in the face of this opportunity.
🚀 Embracing Digital Transformation Internally
The speaker outlines the company's efforts to internalize digital transformation, aiming to apply the same digital tools and platforms used in customer-facing applications within their own operations. They describe the company's dual strategy of being both a platform and an application company, with the development of a platform called 'predicts' and the construction of applications on top of it. The decision to open this platform to customers for application development is highlighted, along with the hiring of thousands of data scientists and the need for a cultural shift within the company. The speaker acknowledges the need for new product managers, salespeople, and on-site support staff, indicating a significant change in the company's approach to talent and training. They also discuss the broader impact of digitalization on the company's IT and manufacturing operations, framing it as a positive and necessary evolution.
🌐 Culture Shift and Continuous Improvement
The speaker delves into the company's approach to culture simplification, aiming to reduce complexity and improve efficiency. They describe the move away from annual reviews and planning to a more continuous and real-time feedback system, embracing a 'Silicon Valley' approach to fast works. The company is adopting lean tools and digitalization to streamline processes and decision-making, with an emphasis on commercial intensity and risk reduction through execution. The speaker also touches on the company's global footprint and the challenges of operating in a highly regulated environment, highlighting the need for a culture that can adapt to a permanently complex world. They conclude by stressing the importance of democratizing information and adopting contemporary IT tools to foster a culture of simplification.
Mindmap
Keywords
💡Digitization
💡Industrial Internet
💡Analytics
💡Business Model
💡Data Scientists
💡Productivity
💡Platform Company
💡Service Agreements
💡Cultural Simplification
💡Lean Tools
💡Global Operation
Highlights
Industrial companies are in the information business whether they want to be or not.
A flight between New York City and Chicago produces a terabyte of data from sensors on jet engines.
The decision was made to treat analytics as core to the company, as material science has been over the last 50 years.
GE wants to be both a platform company and an application company with a focus on analytics and data.
The velocity of a locomotive is crucial for profit; just a 1 mph improvement can generate $250 million in profit for companies like Norfolk Southern.
GE's revenue from software and applications is about $5 billion, with an annual productivity of $500 million.
The 'digital thread' is aimed at connecting engineering all the way through the installed base for enhanced internal operations.
GE has hired a couple thousand data scientists and is continuing to expand that workforce.
The company has had to rethink its hiring, focusing on product managers, commercial people, and new types of skills.
The digital initiative started about five or six years ago to handle the complex challenges of a global operation.
GE's footprint has shifted from 70% inside the U.S. to 70% outside the U.S., adding to the complexity of operations.
The company's culture was too complicated, and simplifying the culture has become a major focus.
GE has adopted 'fast works'—a Silicon Valley approach to lean tools, adapting quickly and embracing market risk.
In the digital age, the idea of annual reviews or planning is outdated; GE has shifted to continuous feedback and planning cycles.
Internal democratization of information, with contemporary IT tools, is driving GE's move toward a simplified and modern organization.
Transcripts
you
we think about this digitization of the
industrial world we as a company didn't
you know go to bed one night and and say
god we can't be an industrial company
anymore
we need to be more like Oracle we need
to be more like Microsoft they what
happened was it happened more on an
evolutionary basis really based on the
industries were in and in the technology
we serve you think about a jet engine
today or a locomotive or a mr scanner
it's maybe a new jet engine might have a
hundred sensors on it
these sensors have the capability to
take continuous data about the heat of
the engine the fuel consumption the
where are the blades the environment
that they're taking off and a series of
things
and a one flight between New York City
and Chicago produces a terabyte of data
so industrial companies are in the
information business whether they want
to be or not this is going to happen in
the industrial space now you add to that
a series of decisions every company
needs to make about do I do i outsource
all that do I do it myself do I change
my business model accordingly and the
decision we've made is that we just want
to be all in we want to treat analytics
like it's as core to the company over
the next 20 years as material science
has been over the last 50 years we can
hire the talent you know we can evolve
our business model accordingly we need
to treat our service agreements to share
outcomes with our customers the same way
an IT company might approach that in the
future so in order to do that we have to
add technology we have to add people we
have to change our business models we
have to be willing to do all those
things but the point I make to to people
is if you think about today 15 or 20
percent of the S&P 500 valuation our
consumer internet stocks that didn't
exist 15 or 20 years ago the consumer
companies got none of that right when
you look at retailers bang
consumer product companies they got none
of that now if you look about 10 or 15
years and say that same value is going
to be created in the industrial internet
do you as an industrial company want to
sit there and say I don't want any of
that I'm gonna let a new co or some
other company get all that is that is
that really what you've relegated
yourself to so I think all these things
led us to say let's build it let's see
if we can be good at it we may be wrong
we don't think so but we may be wrong
but let's not sit back and just say look
that's somebody else's job or we're not
good enough to do it or we can't change
we're unwilling to take that as a fait
accompli
we went through a process of kind of
make versus buy in versus out so we
basically said look do we want to make a
big acquisition in analytics right T and
we analyzed a bunch of different cases
and basically said look we haven't
really we don't have the foundation
inside the company to do a big
acquisition
let's make do we want a partner or do we
want to do it ourselves we we have lots
of good software partners but we
basically said look we need to do this
ourself
probably let's err on the side of seeing
if we could approach it in that way so
that was 2010 so we we brought people in
from the outside we built a Center in
California we started populating our
businesses so so roll forward we started
doing applications with customers we
started building into our service
business things like that I can give you
a bunch of different analogies but in
the case of our locomotive customers
they have a phrase called velocity every
CEO of a railroad could tell you their
velocity the velocity tends to be let's
say between 20 and 25 miles per hour
this tends to be the average miles per
hour that a locomotive travels in a day
22 miles doesn't seem very good the
difference between 23 and 22 for like to
say Norfolk Southern that's worth 250
million dollars of annual profit that's
huge for a company like that
that's one mile so that's all about
scheduling better it's all about less
downtime it's all about not having
broken wheels being able to get through
Chicago faster that's all analytics
I'd say inside the company we're about
five billion dollars in revenue so this
is from software in little applications
things like that so we build up let's
say a population of applications we get
about let's say we're approaching 500
million dollars of productivity a year
and now kind of what we're trying to do
is we're trying to push that back inside
the company as well so you know we're
selling it but we want to get our own
internal company on the same basis on
the same platform using the same skills
what we call the digital threat we want
the digital thread to go from
engineering all the way through our
installed base and and you know we've
made the decision that we're gonna try
to be both a platform company in an
application company so we have a
platform called predicts and then we're
building applications on top of that
we're probably the only industrial
company that's actually trying to do its
own plan and we're opening up our
platform to our customers we're saying
to our customers look if you want to
write apps applications on prediction
you're free to do it I always think risk
first like most like most CEOs I
basically say our investors look if all
we did is we got more productivity
higher service sales applications you
guys are gonna love this if we end up
having the platform that works it's a
whole new company you know so you get
that for free but that's why I circle
back and would say to any CEO industrial
or non industrial this is going to be
the most important thing that that
you're gonna work on at least in this
era where we are right now and you give
up your latitude you know at your own
peril on this
so we probably have hired since we
started this a couple thousand just data
scientists and things like that that's
going to continue to grow and multiply
what we found is we've got to hire new
product managers new difficult
commercial people there's it's going to
be in the thousands so so what you're
gonna do is you're gonna blend them with
the GE team and then we're gonna recruit
differently so when we go to college
campuses we're gonna look for different
skills we're gonna put them in different
training programs so it's a combination
of you've got you've got to bring our
culture along but that's not enough
we've got to bring thousands of people
in from the outside the that's the only
way that's the only way we're gonna get
there fast enough this is something I
got wrong I thought it was all about
technology I thought if we hired a
couple thousand technology people if we
if we upgraded our software things like
that that was it I was wrong product
managers have to be different
salespeople have to be different on-site
support has to be different we've we've
had a drill and change a lot about the
company and then I just think it's it's
it's infecting everything we do it's
infecting our own IT it's infecting our
own manufacturing plants it's it's
infected everything we're doing and and
I think in a positive way not a negative
way
when you think about internal change
culture people leadership development
again here's here's a time where
multiple things happen at the same time
I think we started digital initiative
maybe five or six years ago we've also
as a company now I don't think geez
unique through this you know live
through the financial crisis where an
old company we live in highly regulated
industries I think what we found was our
culture was too complicated to get the
work done the way we needed to get our
work done both in terms of how we were
trying to digitize how we're trying to
survive in terms of a more highly
regulated world and just just think
about our footprint even since I was CEO
when has gone from 70% inside the United
States to 70% outside the United States
just the complexity of running a global
operation so what we've trying to do
inside the companies really just drive
this what we call culture simplification
right fewer layers of fewer processes
fewer decision points we've adapted the
lean tools in a what I would call
Silicon Valley approach what we call
fast works so we've embraced some of the
some of the Silicon Valley tools in
terms of putting everything on the clock
bringing commercial intensity into the
company and and the way I describe that
is as most big companies we're willing
to take all kinds of market risk so that
we don't have to take in turnover right
we've tried and say look let's let's
let's actually be aggressive in the
markets and let's count on our own
execution to risk reduce inside the
company and then broadly getting to the
digitisation point just democratizing
information inside the company just
getting IT tools that were contemporary
in a mobile setting and we call these
things the culture of simplification so
you know my notion is we're in a
permanently complex world a permanent
complex world in this historical
organization chart with lots of
processes that's kind of a thing of the
past
we basically unplugged anything that was
annual so so the notion is in the
digital age sitting down once a year to
do anything is weird it's just bizarre
so we basically you know whether it's
doing business reviews or strategic
planning we're on a much more continuous
way we still give a lot of feedback we
still do a lot of how you're performing
but we make it much more contemporary
and much more 360 so somebody can get
interactions with their boss and a
monthly basis or a quarterly basis and
the data you get is being collected by
your peers the people that work for you
and a much more accurate and fluid way
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