How a Takeoff in Advanced Robotics Will Power the Next Productivity Surge

The Shifting Economics of Global Manufacturing
How a Takeoff in Advanced Robotics Will
Power the Next Productivity Surge
February 2015 – Selected highlights

1
Copyright©2015byTheBostonConsultingGroup,Inc.Allrightsreserved.
Executive summary of the findings
A takeoff in advanced robotics
will lead to +/– changes of up to 5
percentage points in the cost
competitiveness of the leading
export nations relative to the US
Advanced industrial robots will
boost productivity and lower labor
costs significantly over the
coming decade
Robotics are quickly approaching
an inflection point in usage and
are being adopted in new
industries
Four industries will deploy the
majority of advanced robots
through 2025
A combination of wage rates and
labor flexibility will determine the
rate of adoption
• Countries that have shown the ability to drive consistent productivity gains have led
BCG's global manufacturing cost-competitiveness rankings
• Advanced industrial robots will power the next surge of productivity improvements
• S. Korea, China, the US, Japan, and Germany are likely to benefit disproportionately;
much of the rest of W. Europe is expected to lag in adoption due to their labor laws
• Robots will boost productivity by 10%–30% in many industries and lower labor costs by
18% or more in certain countries in 2025, after inflationary increases over the next
decade and net of traditional productivity measures
• They could also push labor savings at least 30% higher than they would be otherwise
• Prices should drop ~20% and performance should rise ~5% p.a. over the next decade
• Recent introduction of robots <$40K (e.g., Baxter, UR5) working alongside humans is
eliminating cost, safety, and programming barriers; robots are now affordable for SMEs
• Programming, advanced vision, and gripping systems continue to expand the
boundaries of use, eliminating technical barriers for some key sectors
• Computer, electrical, transportation, and machinery will buy ~75% of robots through
2025
• Industry adoption will be primarily driven by economics (relative wages vs. robotics
costs)
• Industry task makeup will influence robot costs and likelihood of automation
• Four patterns will emerge—with the fastest growth in SE Asia, slowest in W. Europe
• Labor laws, capital availability, and growth will drive speed of country uptake
• Estimate ~80% of purchases to come from China, US, Japan, Germany, and S. Korea

2
Key takeaways
Robotics will change the calculus of manufacturing. The era of moving factories to capitalize on low-cost labor is
coming to an end
• Not for every product but for many. This can already be seen in the transportation, computer, and electrical equipment
sectors
The size of the manufacturing plant will be far less important as an economic driver than it is today
• Robotics will economically produce products in smaller lots and can be flexibly programmed and reprogrammed to create
different configurations
• Manufacturers, in some industries, will no longer need traditional, permanent production lines
Factories will be smaller and will be able to serve local markets with tailored products
• Once manufacturers set up a facility, they will be able to replicate production by sending the programming to similar robots
anywhere
Even small and medium-sized enterprises (SMEs) can participate as new robots cost as little as $25,000 with attractive
economics
The workforce will require very different skills (e.g., programming and higher-end mechanical engineering)
• Workers will need new training for the tasks they will do
Manufacturers must stay vigilant
• They must understand industry and country dynamics to know when rivals may adopt robotics
• They should also develop long-term transition, technology-development, and retraining plans

3
Productivity is a key driver of manufacturing competitiveness
Labor typically represents ~15%–40%
of production costs
Productivity plays a major role
in offsetting wage growth
151516
222323
27282829292932363636383942
0
20
40
60
80
100
Nonmetallicmineral
Labor as % of 2014 industry costs
Chemicals
Petroleumandcoal
2
Primarymetals
15
Food
Beverageandtobacco
Transportationequipment
Papermanufacturing
Leatherproducts
Textilemills
Plasticsandrubber
Electricalequipment
Woodproducts
Machinery
Textileproductmills
Furniture
Fabricatedmetal
Apparel
Computerandelectronic
Miscellaneous
Printing
Max
Average across top 25
export economies
882
29
77
0
50
100
150
2004 Other
cost
increases
2014Productivity
gains
Wage
growth
-20
Example: Mfg Cost-Competitiveness Index,
Computers / Electronics in China – YRD1
1Changes in the index from 2004-2014 are rounded to the nearest percentage point. YRD stands for Yangtze River Delta region in China.
Sources: US Economic Census, US Bureau of Labor Statistics, US Bureau of Economic Analysis, International Labor Organization, Euromonitor, Economist Intelligence Unit, BCG analysis

4
Canada
SouthKorea
By 2025, ~25% of all tasks will be automated through
robotics, driving ~16% in global labor-cost savings
1China figures based on YRD region. Sources: STAN Bilateral Trade Database, US Bureau of Labor Statistics, BCG analysis
Conservative
Aggressive
Scenarios
00
3
6777888999
1314
16
1818
20
21212222
24
25
33
0
10
20
30
40
Labor-cost savings from adoption of advanced industrial robots (%, 2025)
Average global labor-cost savings ~16%
Indonesia
Japan
UnitedStates
Taiwan
UnitedKingdom
Australia
Germany
CzechRepublic
China1
Globaltotal
Thailand
Switzerland
Poland
France
Italy
Belgium
Sweden
Netherlands
Brazil
Russia
Mexico
Austria
Spain
India
47 40 35 32 33 30 41 39 34 35 30 24 26 30 29 27 26 14 25 24 23 22 19 7 0 0
21 15 12 10 12 10 6 6 9 5 8 8 4 6 6 5 5 4 5 5 5 4 4 1 0 0

5
Advanced robots operate where traditional robots cannot
Able to apply logic to make decisions and/or operate in quasi- or unstructured environments
Develops logic
• Creative thinking required
• Involves problem solving
Applies logic
• Arrives at a decision about the object
• Involves quality control or feedback on
success of an operation
No logic needed
• No decision made about the object
• Includes image processing to determine
part orientation/feature detection
Rigid
• Environment or objects always in
predicable orientation/location
• Objects can be moving but at a
known speed
Quasi-structured
• Environment or objects have
some degree of variability
• Localization of objects requires
additional degree of sensing
(e.g., image processing)
Unstructured
• Environment or objects have no
predefined orientation and/or no
predefined structure
• Localization of objects requires
additional degree of sensing
(e.g., image processing)
Develops
logic
Applies
logic
No logic
needed
e
Rigid
Quasi-
structured
Unstructured
Taskcomplexity
Environment / Object structure
Traditional
robotics
Human labor
advantage
Advanced robotics

6
Project management
Has consistently been ~5%–10%
of total system costs; absolute
cost decline expected
Systems engineering (e.g.,
programming, installation)
Gains from offline programming
mostly obtained; decrease
expected to slow given the
minimum cost of installation
Peripherals (e.g., safety
barriers/systems, sensors)
Will see additional drop due to
removal of safety barriers
Robot (includes software)
Minimal declines expected given
pricing is close to material cost for
high-purchase-volume automotive
industry
Advanced industrial robots are increasing in performance
while costs continue to fall steadily
Future costs trends
55
43
33 30 28
33
40
45
40
36
81
62
46
39
33
13
11
9
0
50
100
150
200
2010
155
2005
182
103
7
2020
117
8
Present
(2014)
133
Example of total industrial robot system costs ($USD, thousands)
-22%
2025
1Average quality adjustment from 1990-2004 was ~5% on top of price change.
Note: Example costs are for a spot welder (largest current application) in the US automotive industry, numbers in nominal dollars.
Sources: ABB "Economic Justification for Industrial Robotic Systems" (2007), IFR "World Robotics-Industrial Robots 2013," expert interviews, BCG analysis
Projected
Meanwhile, robot performance is increasing at an estimated 5% per year1

7
Robotics already a rational alternative to human labor in
many industries based on pure economics
0
10
20
30
40
Price/performance-adjusted
nominal wages and operating cost ($/hour)
2030202520202015
1Robot system cost is for a typical spot welding application in the US automotive industry. 2Example is a general robotic system, such as the ABB IRB 2400. 3Includes other wood products
Note: Assumes 8% price and performance improvement rate. Gray lines represent high (thin lines) and low (thick lines) scenarios around baseline scenario. Labor hourly rates include benefits
and overhead (~50% increase over base hourly pay). All values shown in nominal 2014 US dollars.
Sources: US Bureau of Labor Statistics, Industrial Federation of Robotics, company websites, expert interviews, IFR "World Robotics - Industrial Robotics 2014," BCG analysis
Within the US automotive and electrical equipment industries, robotic
price/performance is better than or near parity with manual labor costs
In other industries,
robotic systems may surpass
manual labor in the next 10 years
0
10
20
30
40
2030202520202015
Robot (generic)2
Furniture wages
0
10
20
30
40
2030202520202015
2023
US automotive industry US furniture industryUS electrical equipment industry
Robot (generic)2
Electrical wagesSouthern US auto wages
Robot (automotive)1
2013 industrial robot
shipments (units)
10,320
shipments (units)
3,328
shipments3 (units)
23
2018

8
Inexpensive robots with integrated low-cost systems have
broadened their customer base beyond large companies
New emerging platforms are low-cost…
Universal Robotics
Universal UR5: $34K
(~$70K total with setup costs)
• Sample applications:
material handling,
assembly, machine
tending
Rethink Robotics
Baxter: $25K
(~$38K with setup costs)
• Sample applications:
packaging, kitting,
material handling
…And are safe to operate alongside
humans and easy to train or reprogram
Source: Company websites
Human-directed
teachingSafety
No safety barricades or
equipment required
Can work safely in
proximity to humans
(e.g., a collaborative robot)
Manually moving the robot
through the required
motions eliminates the
need for specialized
technicians and expertise

9
Technological advances also continue to create opportunity
for robotics to be used in new industries
Fabricated
metal
Solution examples
Jabez Technologies'
Robotmaster1
1Winner of Robotics Business Review's Game Change Award for motion control technologies. 2Cruse Leppelmann Kognitionstechnik GmbH.
Sources: Robotics.org, company websites, BCG analysis
Industry
Food and
beverage
CLK2 3D visual inspection
systems for trimming and
cutting
Electrical/
electronics
Challenge
• Translate CAD drawing to
robot path
• Inadequate programming
tools for complex
robot trajectories
• Inconsistent product
dimensions
• High variability
between animals
• Small parts need a higher
degree of accuracy
(e.g., connectors)
• Require quick
movements to
maximize throughput
FANUC delta-style and high-
speed six-axis articulated robots
Application
examples
Debur a gear
Process beef
• Trim
• Cut
Assemble auto
battery cells

10
Certain industries are more likely to see the economic
benefit of robotics due to high wages and automatable tasks
-40 -20 0 20 40
% deviation from global average manufacturing wage2
Computer and electronic products
Miscellaneous
Furniture
Transportation equipmentElectrical equipment, appliance, and component
Apparel
Textile product mills
Machinery
Fabricated metal Primary metal
Nonmetallic mineral products
Plastics and rubber products
Chemicals
Printing and support activities
PaperWood products
Leather
Textile mills
Beverage and tobacco products
Food
Most likely to lead global adoption
Laggards Technologically limited
Highly
automatable1
Limited
ability to
automate
Adoption in high-wage countries only
Ability to
automate
based on
currently
available
technology
1Corresponding to occupational tasks that have the future potential to be replaced with advanced robotics. 2Average industry-specific wage premium derived from BLS International Labor
Comparison of Hourly Compensation Costs in Manufacturing Industries, 2012.
Note: Petroleum and coal manufacturing not pictured due to high and variable wage premium, consistent with immovable, resource-intensive industries.
Sources: US Bureau of Labor Statistics, BCG analysis

11
Robotics
adoption
by year
0% 1% 3% 4% 7% 10%
Robotics
adoption
by year
0% 0% 0% 0% 1% 1%
Robotics reduces productivity-adjusted labor costs
Examples: German chemical industry on cusp of adoption; US later, sees limited 2025 savings
2014 2016 2018 2020 2022 2024
50
100
200
150
250
Effective cost, weighted average of robotics cost and wage rate
Average chemical robotics amoritized hourly cost
German chemical industry productivity-adjusted wage index
Robotics investment triggered in
2014, 15% price gap
Robotics investment results in
~8% lower costs in 2025
German chemical industry labor costs
(indexed to US) will be effectively reduced by
enabling more output or fewer workers
US chemical industry sees limited robotics
investment, but still competitive
Minimal 2025
savings realized due
to low adoption rate
Productivity-adjusted
wages (US = 100 in 2014)
Robotics investment
not triggered until 2021
Note: All wages in nominal productivity-adjusted values.
Sources: US Bureau of Labor Statistics, Economist Intelligence Unit, International Labor Organization, International Federation of Robotics, BCG analysis
Productivity-adjusted
wages (US = 100 in 2014)
2014 2016 2018 2020 2022 2024
200
50
100
150
250
Effective cost, weighted average of robotics cost and wage rate
Average chemical robotics amoritized hourly cost
US chemical industry productivity-adjusted wage index

12
Labor-cost reduction and productivity gains due to robotics
could have a big impact on countries' cost competitiveness
Potential change in manufacturing cost-competitiveness index1 due to robotics, 2014 – 2025
1BCG's Global Manufacturing Cost-Competitiveness Index shows how competitive the top 25 export economies are in manufacturing. BCG measures each economy relative to the US. Above,
a one-point gain vs. the US means that the direct manufacturing costs of the country in question will become one percentage point cheaper relative to the US by 2025. For further background,
see BCG's August 2014 report, The Shifting Economics of Global Manufacturing. Sources: STAN Bilateral Trade Database, US Bureau of Labor Statistics, BCG analysis
Conservative
Aggressive
Scenarios
4444
333222
2222
1110
-1-1-1
-2
-4
-6
-10
0
10 SouthKorea
Indonesia
Japan
UnitedStates
Taiwan
Canada
United
Kingdom
Australia
Germany
Czech
Republic
China
Thailand
Switzerland
Poland
France
Russia
Belgium
Sweden
Netherlands
Brazil
Italy
Mexico
Austria
Spain
India
Gain ground
vs. the US
Lose ground
vs. the US
(11) (12) (3) (5) (4) (2) 0 0 (6) 1 (5) 1 1 (2) (2) 2 (0) 0 0 1 2 6 6 7 7
(4) (0) (1) (0) 0 (1) 0 (0) (0) (0) (0) 1 1 0 0 1 0 0 1 1 1 1 1 2 2
Dependent on wage growth,
labor productivity gains and
robot adoption, China may
gain ground vs. the US
Robotics offer an opportunity for both high- and low-wage
countries to make competitiveness gains

13
Management implications: Manufacturers worldwide must
remain vigilant
An understanding of global costs and
robot usage within your industry...
Survey the global landscape and keep a
pulse on industry-specific robotics trends
• Price/performance trends in your industry
and country
• Know drivers of robotics adoption in your
industry
• Robotics are not out of reach for SMEs
Keep abreast of technology and likely
competitor adoption
• Be aware of when technical challenges
(e.g., vision systems) are solved
• Knowledge of competitive robotics adoption
supports accurate costing, pricing,
investment, and strategic decision-making
...Is key to building a long-term
network and workforce strategy
Basis of competition is likely to shift away
from low-cost labor arbitrage
• Manufacturers can no longer simply "chase"
cheap labor
• Workers' tasks may shift to more complex
tasks where humans maintain advantages
• Consider locating where skilled
programming/automation labor is available,
not just traditional low-cost, low-skill labor
Prepare a network strategy for the robotics
revolution to maintain long-term
competitiveness
• Consider network flexibility in order to
realize the benefits of robotics as costs fall
• Develop a plan for robotics adoption as:
– New technology comes online
– Costs continue to decline
– Robot productivity accelerates

14
This research is part of BCG’s series on the shifting
economics of global manufacturing
Authors of this research
Selected publications and
research in the series
The Shifting Economics of Global Manufacturing: How Cost
Competitiveness Is Changing Worldwide
A report by The Boston Consulting Group
August 2014
The Rise of Robotics
An article by The Boston Consulting Group
August 2014
3D Printing Will Change the Game: Prepare for Impact
An article by The Boston Consulting Group
September 2013
Majority of Large Manufacturers Are Now Planning or
Considering 'Reshoring' from China to the U.S.
(press release)
Survey findings by The Boston Consulting Group
September 2013
Behind the American Export Surge: The U.S. as One of the
Developed World’s Lowest-Cost Manufacturers
August 2013
U.S. Manufacturing Nears the Tipping Point: Which
Industries, Why, and How Much?
March 2012
Note: Publications are available on BCG’s thought leadership portal, www.bcgperspectives.com, or at www.bcg.com.
Harold L. Sirkin
Senior partner and coauthor of The U.S. Manufacturing
Renaissance: How Shifting Global Economics Are Creating an
American Comeback (Knowledge@Wharton, November 2012)
BCG Chicago
Michael Zinser
Partner, coleader of the Manufacturing practice, and coauthor of
The U.S. Manufacturing Renaissance: How Shifting Global
Economics Are Creating an American Comeback
BCG Chicago
Justin Rose
Partner, leader of green energy in the Americas, and coauthor of
The U.S. Manufacturing Renaissance: How Shifting Global
Economics Are Creating an American Comeback
BCG Chicago
To request a media interview, please contact Eric
Gregoire at gregoire.eric@bcg.com.
To discuss the findings with a BCG expert, please
contact Payal Sheth at sheth.payal@bcg.com.
To read other publications in this series, please go
to www.bcgperspectives.com.

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