GE’s Jeff Immelt on digitizing in the industrial space McKinsey Company

Summary

The 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

00:00

🔧 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.

05:00

🚀 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.

10:01

🌐 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.

Keywords

💡Digitization

Digitization refers to the process of converting information into a digital format. In the context of the video, it is about transforming industrial operations into data-driven processes. The speaker discusses how industrial companies are becoming information businesses due to the vast amount of data generated by their products, such as jet engines with sensors that collect data on heat, fuel consumption, and more. This data is crucial for making informed decisions and improving efficiency.

💡Industrial Internet

The Industrial Internet is a term used to describe the integration of complex machines, sensors, and software into industrial processes to optimize efficiency and productivity. The video highlights how the Industrial Internet is creating new opportunities for industrial companies to generate value by harnessing the data from their machines, similar to how consumer internet companies have done.

💡Analytics

Analytics is the process of examining data to draw conclusions and support decision-making. The speaker emphasizes the importance of analytics in the future of industrial companies, comparing its significance to that of material science in the past. The company's decision to treat analytics as a core competency reflects the belief that data analysis will drive innovation and competitive advantage.

💡Business Model

A business model outlines how a company creates, delivers, and captures value. The video discusses the need for industrial companies to reconsider their business models in light of digitization. This includes decisions about whether to outsource data analysis or handle it in-house, and how to incorporate data-driven insights into their service agreements with customers.

💡Data Scientists

Data scientists are professionals skilled in analyzing and interpreting complex digital data. The speaker mentions hiring thousands of data scientists as part of the company's digitization efforts. This highlights the growing importance of data expertise in driving business strategy and innovation within industrial companies.

💡Productivity

Productivity refers to the efficiency of production, or the output of goods and services per unit of input. In the video, the speaker discusses how the company's investment in analytics and digital tools has led to significant productivity gains, such as saving millions of dollars by optimizing the velocity of locomotives.

💡Platform Company

A platform company provides a foundational technology or service that others can build upon. The video describes the company's ambition to become both a platform and an application company. They have developed a platform called 'predicts' and are encouraging customers to build applications on top of it, showcasing their commitment to open innovation and collaboration.

💡Service Agreements

Service agreements are contractual arrangements that define the services to be provided by one party to another. The speaker mentions the need to evolve service agreements to share outcomes with customers, similar to how IT companies operate. This reflects a shift towards outcome-based services, where the value is in the results achieved rather than just the services provided.

💡Cultural Simplification

Cultural simplification refers to the process of streamlining and simplifying organizational culture to improve efficiency and adaptability. The video discusses the company's efforts to reduce complexity, such as cutting down on layers of management and processes, to better align with the fast-paced demands of the digital age.

💡Lean Tools

Lean tools are methods and practices aimed at maximizing value while minimizing waste. The speaker mentions the adoption of lean tools and a 'Silicon Valley approach' to improve the company's operations. This includes practices like 'fast works', which emphasizes speed, flexibility, and continuous improvement in product development and service delivery.

💡Global Operation

A global operation refers to a business that operates across multiple countries and markets. The video notes the company's shift from being 70% U.S.-based to 70% outside the U.S., highlighting the complexity of managing a global footprint. This change underscores the need for digital tools and strategies to effectively coordinate and optimize operations on a worldwide scale.

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