This IDC Spotlight paper emphasizes how continuous improvement methodologies, empowered by instrumentation, machine learning, and distributed intelligence, will help manufacturing companies become flexible, context-aware digital businesses.

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
The Robot Apocalypse?
In December 1980, the American news weekly Time Magazine had a cover story entitled The
Robot Revolution. The article talked about advances in robotics and the impact on global
employment and economic power. The piece captured much of the worker trepidation about
the coming automation and warned that Japan, then considered the low-cost manufacturing
challenger to the United States and Europe, was investing most aggressively in robotics
despite the perceived labor cost advantage.
In 1980, manufacturing represented approximately 20% of global GDP and 22% of
employment; today, these numbers are 16% and 14%, respectively. The growth of the service
sector has reduced the contribution manufacturing makes to the world economy, but the drop
in employment has been even more precipitous. Is this evidence that the Time article was
correct?
We would answer yes but with some extenuating circumstances. The impact has come more
from automation in general (including robots) than just robotics as the machines that run in
factories became more reliable, faster, and smarter. Automation extends to factory material
handling and warehouse and supply chain operations with automated guided vehicles and
storage and retrieval systems. Advances in workflow and planning software also contributed
to the productivity gains. However, continuous improvement programs like Lean and Six
Sigma had a huge impact on this economic data as the application of these methodologies
became widespread.
It is valuable to think about this history in the wake of all the conversation and hand-wringing
we see today around the impact of the next generation of automation, collectively referred to
as Industrie 4.0, or smart manufacturing. And the past is truly a prologue. By 2020, robotics
will have five times the capability at one-fifth the cost of what was available in 2015, and
China is the most aggressive investor, but like the last wave, it will be automation inclusive
of those robotics, not just robotics. Continuous improvement methodologies, empowered
Industrie 4.0 and the Economic,
Employment, and Enterprise Implications
Brought to you by:
Tech Mahindra
Powered by:
IDC
Author:
Robert Parker
January 2017

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
by instrumentation, machine learning, and distributed intelligence, will help manufacturing
companies become flexible, context-aware digital businesses moving to single-order
approaches that will allow them to individualize and personalize products at an unprecedented
level.
This white paper investigates this further by discussing three scenarios that will impact the
industry:
• There is an opportunity of $4.5 trillion for economic value-add across the manufacturing
value chain — $1.1 trillion in the factory itself.
• Up to 50 million jobs will be under pressure to be reskilled.
• Enterprises will invest in digital platforms to sustain operational excellence.
Scenario 1: There Is an Opportunity of $4.5 Trillion for
Economic Value-Add Across the Manufacturing Value
Chain — $1.1 Trillion in the Factory Itself
CEOs across all industries are embracing a digital-based business strategy to capture
growth opportunities and improve performance. They see the opportunity to fundamentally
change customer experiences through new investment in technology and understand that
their fundamental operating model must change to support the successful delivery of that
experience. This trend is particularly true in manufacturing as the management focus pivots
from one on managing capacity and resources to one that creates capabilities from an
ecosystem.
IDC conducted an analysis to determine the digital transformation (DX) opportunity by industry
segment. The manufacturing industry has the potential to create $4.5 trillion of economic
value over the next five years, and this is what those CEOs are targeting for improvement. The
sheer size of this number can be formidable to understand, so we endeavored to evaluate the
opportunity across the basic value chain (see Figure 1).
The factory itself represents 25%, or $1.125 trillion, of the opportunity, and it is the focus of
this white paper. Figure 1 further breaks this down into three broad categories:
• Asset utilization: Digital technologies can be applied to improve the availability of assets
and, in turn, the utilization rate. The $394 billion will flow from lower maintenance costs,
higher revenue levels, and avoidance of new capital expenditures.

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
• Throughput/efficiency: New machine, energy, labor, and materials efficiencies will be
realized through digital technologies, amounting to $506 billion in economic value-add.
• Quality assurance: Digital technologies can be used to catch defects sooner and error
proof processes to sustain improvements. The estimated potential is $225 billion.
Future factory initiatives will be financially justified along these same lines. While all of the
elements are important, different segments may emphasize one over another. For example,
in asset-intensive manufacturing segments like chemicals, the returns will flow largely from
asset utilization, while fast-moving consumer goods are likely to begin with throughput and
engineering-oriented value chains like automotive or aerospace with quality.
While the factory represents $1.1 trillion of the opportunity, the impact of digitalization has
similar implications for the upstream supply chain ($1.3 trillion) and downstream sales
channels ($2 trillion). However, the factory will be the central pivot for capturing the value.
Supply and materials movement will be calibrated to the pace of the factory. Similarly, a
manufacturer’s ability to satisfy the promises made on both the initial sale and the aftermarket
will be dependent on product design and manufacturability.
FIGURE 1 Dissecting the DX Opportunity in Manufacturing
Source: IDC, 2016
Digital
transformation
$4.5T
MAKE
Smart manufacturing
$1.125T
Asset utilization
$394B
Quality assurance
$225B
Through put/
efficiency
$506B
SOURCE
Upstream SC
$1.350T
DELIVER
Downstream SC
$2.025T

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
Business Implications
The database of IDC MaturityScape Benchmark for digital transformation shows that the
manufacturing industry is well under way on its journey but still relatively immature (see Figure
2). Winners in the digital economy will have to move fast to effect transformation and capture
the economic value.
FIGURE 2 Digital Transformation Maturity in the Manufacturing Industry
In 1980, operational priorities revolved around creating scale — the ability to produce a
standard product at the lowest possible cost. As we reached the turn of the century, the
emphasis, largely due to globalization, turned to scope — finding an optimal cost to serve
specific markets. As we move toward 2020, the emphasis is shifted to operational speed —
the ability to use technology to quickly adapt to market needs. Creating reliable velocity will
allow manufacturing companies to capture their share of the $4.5 trillion opportunity. This
requires the ability to manage new ecosystems at speed and scale based upon an Industrie
4.0 platform that embeds smart factory and IoT capabilities, industry collaborative clouds (for
both open and proprietary ecosystems), and industrial information technology (IT) systems
fully enabling IT and operations technology (OT) convergence.
Digital ExplorerDigital Resister Digital Transformer Digital DisruptorDigital Player
16.2%
41.1%
22.1%
14.7%
5.8%
Ad Hoc
Opportunistic
Repeatable
Managed
Optimized
Business is a
laggard, providing
weak customer
experiences and
using digital
technology only to
counter threats.
Digitally enabled
customer experience
and products are
inconsistent and
poorly integrated.
Business provides
consistent but not
truly innovative
products, services,
and experiences.
Business remakes
existing markets and
creates new ones to
its own advantage
and is a fast-moving
target for competition.
Business is a leader
in its markets,
providing world-class
digital products,
services, and
experiences.
Source: IDC, 2016

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
The French energy management and automation specialist Schneider Electric is a great
example of productivity benefits enabled by the new platform approach. Schneider Electric
developed the EcoStruxure platform to improve asset management and maintenance. In an
application of the platform, the connected solar power plant, consumers reported productivity
increases of up to 10%. In other applications, across power management, process and
machine management, and IT room, building, and security management, Schneider Electric
reported up to 30% energy savings on capex and opex.
Scenario 2: Up to 50 Million Jobs Will Be Under Pressure
to Be Reskilled
One of the great motivations of political and industry bodies around the world is to create
new manufacturing jobs. This can be seen in not only the Industrie 4.0 efforts in Europe but
also China 2025, Made in India, and the Smart Manufacturing Coalition (the United States).
Combine this with the prevailing political winds of increased protection of home markets as
seen recently in both Great Britain and the United States, and you have a political environment
that is very friendly to manufacturing and supportive of new investment.
However, this enthusiasm must be tempered with the reality that a return of manufacturing
to a mature economy does not necessarily translate to new factory jobs. In fact, estimates
run as high as 50 million jobs lost worldwide because of the investment in new automation
capabilities. That doesn’t mean that governments are wrong to support manufacturing; having
a strong manufacturing base is critical to economic security, but the promise of new factory
employment is misguided.
It is useful to frame the nature of factory work in the future in the context of digital
transformation. IDC has maintained for some time that the traditional thinking of
manufacturing being labor centric — men operating machines — is shifting to a proposition
that manufacturing is becoming people centric — people optimizing processes. Advances in
robotics are more than just capabilities and cost; they are becoming more collaborative with
an ability to be programmed on the fly and work with humans rather than sitting behind a
fence doing a single task programmed for it. In fact, IDC estimates that by 2020, nearly two-
thirds of all work in factories will be completed by one of these “cobots.”
Add to this the impact of additive manufacturing. Today, the use of 3D printing and other
additive methods is largely confined to product prototypes, but there are an increasing
number of examples of the technology being used for production components and
aftermarket parts. The digitally disruptive automotive company Local Motors has built a car
with 97% of the parts created with additive methods. IDC forecasts that by 2020, nearly 20%
of components in complex products like aircraft and automobiles will be produced on demand
with additive manufacturing technologies.

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
The most impactful area, however, will be in the use of data for decision making. The Chinese
appliance manufacturer Haier has an initiative to automate decision making and eliminate
three to five levels of management, with an initial emphasis on operations. Investment in
deeper process instrumentation through IoT and better analysis of that data through machine
learning will produce faster, more adaptable processes. IDC predicts that by 2020, 20%
of operational processes will be self-healing, requiring no human intervention to correct
anomalies. Another 40% will be aided by intelligent agents that can present the decision
makers with vetted options for corrective action.
The job loss estimate of 50 million may be true, but like the last wave of automation, a greater
number of new jobs will be created, even if not directly tied to factory work. There will be a
shift away from mechanical skills and management layers to more educated experts that can
enable rapid process reorganizing and optimization to adjust to market needs. Industrie 4.0
will require a reskilling of the labor force, not a reduction.
Business Implications
Manufacturing companies should use these 2020 predictions as a set of planning
assumptions as they consider the composition of their own labor forces. This planning
exercise should entail an identification of jobs and their relative importance today and in the
future. The resulting mapping of those jobs will determine the approach to take (see Figure 3).
FIGURE 3 Skills Analysis
CURRENT
FUTURE
SKILL
ANALYSIS
Retrain
Outsource Develop
Elevate
High importance
High importance
Low importance
Low importance
Source: IDC, 2016

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
Another best practice identified by IDC is to encourage greater coordination between
those groups responsible for operations technology and those in the IT organization
— perhaps even setting up an independent department made up of personnel from
both sides. Educate the OT personnel on IT concepts like TCP/IP networking, process
management, and analytics while doing the same for IT people on factory networking,
supervisory control systems, and Lean Six Sigma decision frameworks.
Key consulting partners with deep manufacturing experience can be invaluable in
this process as they bring expertise on advanced technologies and a broad set of
experiences. Time is of the essence, so companies should be working on these long-
term skill plans today.
Scenario 3: Enterprises Will Invest in Digital Platforms to
Sustain Operational Excellence
One of the elements that is lost in the typical analysis of the productivity gains the
industry enjoyed in the latter half of the past century is the impact of continuous
improvement methodologies such as Lean and Six Sigma. Most will point to the
increased use of automation or the labor arbitrage of low-cost manufacturing countries,
but a substantial portion can also be attributed to the enhanced discipline of these
approaches to operational excellence.
One of the interesting areas of debate relative to Industrie 4.0 is the question as to
how relevant these methodologies will be. The sheer number of end item products
and associated services being offered combined with the increasing flexibility of the
technology on the factory floor and in the supply chain creates a level of complexity
that is beyond the capabilities of these approaches. At least, that is how the argument
goes. IDC finds that integrating the operational discipline into investment plans actually
enhances both the effectiveness of the methodologies and the technology investment.
A renewed commitment to continuous improvement provides a starting point for thinking
about the technology that must be put in place to guide decision making and process
automation, what IDC refers to as the digital platform.
The digital platform is an architectural construct that marries an analytic model for
decision making, the digital twin, with the instrumentation and activation of the
operational processes (robotic process automation), the digital thread (see Figure 4).

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
FIGURE 4 Digital Platform Components
The digital twin is an analytic environment that creates a closed-loop decision making model
for any domain in the value chain (see Figure 5). The model is built to connect the decisions
made at the most strategic level to those being made in real time at the operational level.
FIGURE 5 The Digital Twin
In an interesting piece of academic research, more than two-thirds of companies reported
not meeting their stretch goals for profitable goals, yet more than 95% of those firms had
detailed strategic plans. The message to executives is clear — having a brilliant strategic plan
may be necessary, but it is not sufficient in achieving goals. In a separate piece of research
investigating companies with Lean Six Sigma programs in place, the number 1 impediment to
success was the lack of strategic direction to set priorities.
Digital Twin
Digital Thread
Improve decision making
Robotic process automation
Product
Portfolio
Scenario
Value
Situational
Sales AftermarketSupply Production
Allocate resources
Mitigate risks
Optimize outcomes
Next best action
Source: IDC, 2016
Source: IDC, 2016

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
The digital twin serves to bridge the strategy-to-execution gap. There are four types of
analysis that are done for every domain within a manufacturing enterprise:
• Portfolio analysis: This is done at the highest level of the organization determining the
right mix of products, customers, suppliers, assets, people, and so forth. The purpose of
this analysis is to allocate resources.
• Scenario analysis: This is done at a senior level in the organization looking at situational
possibilities to identify where the organization is vulnerable with the goal of mitigating
risks.
• Value analysis: This is normal near-term planning where different countervailing
outcomes (e.g., inventory levels versus order fulfillment rates) are evaluated to optimize
outcomes.
• Situational analysis: This is real-time evaluation that determines the next best action.
In this model, business policies or rules flow down, while information flows up. The premise is
to create a complete closed-loop decision making process, essential to achieving the promise
of Industrie 4.0.
The digital thread is realized at the process level and is often at the center of plans for
incorporating IoT technology. There are essentially three layers. At the foundation are devices
and associated connectivity. The next level is the data ingestion and activation layer. This
tier serves to both aggregate and organize the data coming from the devices and send
instructions back down to those devices. At the top level is process orchestration, which puts
the data and action into a process context.
The digital twin and digital thread come together when the next best action coming from the
situational analysis directly communicates with the process orchestration to instantiate the
action (see Figure 6).

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
FIGURE 6 Connecting the Digital Twin to the Digital Thread
Having this platform in place will help deliver the self-healing processes that are at the center
of Industrie 4.0. As the model is trained, this could be further expanded to the model being
capable of self-optimizing plans and self-organizing resources.
The real-time digital twin for continuous optimization will benefit from artificial intelligence
techniques such as machine learning throughout the process, from PLM design and
simulation to actual feedback coming from MES/SCADA systems. The digital thread is
increasingly implemented by business processes modeled and continuously optimized using
modular microservices on cloud platforms.
The Japanese manufacturer DENSO is a great example of a company that is on this journey.
It is making major investments in IoT in its 130 manufacturing factories around the world to
improve quality and increase throughput. These efforts are supplemented by the application of
advanced analytic approaches to ensure that results are optimized across the whole network
of factories.
Business Implications
Creating the digital platform is a truly ambitious endeavor that extends beyond just IoT or
machine learning. However, those companies that look to take this long-term view will be able
to more easily capitalize on the economic potential of the digital future. A significant challenge
Product
Portfolio
Scenario
Value
Situational
Sales AftermarketSupply Production
Allocate resources
Mitigate risks
Optimize outcomes
Next best action
Orchestration
Connectivity
Data ingestation/activation
Self-organizing
Self-optimizing
Self-healing
Source: IDC, 2016

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
remains in putting the technology together — there are no digital platform vendors per se.
There are valuable components that can be assembled but should be done with the services
partner that can ensure the integration is seamless and the cost of ownership is minimized.
About Tech Mahindra
Tech Mahindra is an IT services and outsourcing company, with approximately 113,000
employees in 90 countries and $4.2 billion in revenue in the fiscal year ending in March 2016.
Manufacturing is the second largest vertical within Tech Mahindra, contributing to nearly 20%
of the company’s global revenue. Tech Mahindra’s work in the manufacturing vertical includes
IT and engineering services in areas such as production and quality, manufacturing execution,
fleet management, mobility, and warranty. Specific industry segments that Tech Mahindra
works with include automotive, discrete, aerospace and defense, process and mining and
metals.
Challenges and Considerations
Implementing new IT investments and IT projects come with challenges, many of which can
be addressed with advance planning. The two most notable issues we have seen in the past
include:
• Projects without clear business cases and endpoints and insufficient executive support
• Delays caused by ineffective change management
Furthermore, many of the changes necessary to successfully adopt Industrie 4.0 and execute
digital business transformation require integration of critical business systems and data
sources, as well as data governance or even data quality enhancements. Manufacturers may
also need help in managing across a number of IT vendors and suppliers to achieve their
business objectives.
For Tech Mahindra specifically, the challenges are to differentiate its offerings and its ability to
execute in the manufacturing industry, where Tech Mahindra also faces competition from very
large global players. Tech Mahindra must also demonstrate how its services are relevant not
just for IT but also in the context of the business, and as such contribute to digital business
transformation.

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IDC White Paper | Industrie 4.0 and the Economic, Employment, and Enterprise Implications
Essential Guidance
The three scenarios discussed in this white paper should serve as long-term planning
assumptions that guide your thinking as to how to best capture the opportunity. However,
immediate action is required so that the plan must be devised quickly and investment started.
Given the skills and fractured technology landscape, manufacturers would be well advised
to seek a services partner that brings the requisite project skills, technology skills and, most
importantly, a deep understanding of the manufacturing industry — from both the operational
and the information technology perspective.
The societal pressure will be on improving education as the manufacturing employee of the
future will have to have engineering-level understanding of how things are made. Government
leaders often tout manufacturing as a source of new jobs, but the reality is that those jobs
are unlikely to come with the factories, and the focus should be on the important economic
security that manufacturing brings to a nation.
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About IDC
International Data Corporation (IDC) is the premier global provider of market intelligence,
advisory services, and events for the information technology, telecommunications and
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investment community make fact-based decisions on technology purchases and business
strategy. More than 1,100 IDC analysts provide global, regional, and local expertise on
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