Prof. Dr. Steffen Kinkel 1
Industry 4.0 application and
reshoring of manufacturing –
evidence, limitations & policy implications
Prof. Dr. Steffen Kinkel
Karlsruhe University of Applied Sciences
Institute for Learning and Innovation in Networks (ILIN)
MAKERS Workshop “Industry 4.0 – Implications for an
EU industrial policy”, Brussels, January 25th 2018
MAKERS - Smart Manufacturing for EU growth and
prosperity is a project funded by the Horizon 2020-
MSCA- RISE - Grant agreement number 691192.
Prof. Dr. Steffen Kinkel 2
Content
Industry 4.0 and local value chains
Trends in manufacturing backshoring
Industry 4.0 enabling technologies and correlation with backshoring
Key competences for Industry 4.0
Conclusions for Industrial and Innovation Policy
Prof. Dr. Steffen Kinkel 3
Rise of local value chains and
Industry 4.0?
Transnationally highly fragmented value chains are typical for today's global
economy, in particular for high-tech products (Brennan et al., 2015).
E.g. iPhone: Designed and commercialised in the US
Assembled in China, “Made in the world”
But also disadvantages and risks of global supply chains show up:
(e.g. Handfield, 1994; Holweg at al., 2011; Nassimbeni, 2006)
Long lead-times, low flexibility, instability in supply chains
Unsatisfactory quality standards of foreign suppliers
Cultural differences and communication problems
Rising labour costs
Increasing awareness for the back-/reshoring of manufacturing
Industry 4.0 / Smart Factory enables efficient and agile production systems
Potentials to support back-/reshoring?
Potentials to restore manufacturing and local value chains in EU countries?
Prof. Dr. Steffen Kinkel 4
Offshoring stays on
lowest level since
mid 90s
Backshoring stable
(slightly upwards);
for every 3rd
offshoring company
there is one
backshoring
Around 500 German
manufacturing
companies per year
perform backshoring
German evidence: Manufacturing
offshoring and backshoring over time
17%
26%
27%
19%
25%
19%
12%11% 11%
15%
9%
8% 9%4%
6% 6%
4%3% 3%
2%3%
2% 3%2%
3%
1995(n = 1.305)
1997(n = 1.329)
1999(n = 1.442)
2001(n = 1.258)
2003(n = 1.134)
2006(n = 1.011,n = 1.663)
2009(n = 817,
n = 1.484)
2012(n = 820,
(n = 1.594)
2015(n = 571,
(n = 1.282)
Share
of com
panie
s (
in %
)
Jahr
German Manufacturing Survey 1995-2015, Fraunhofer ISI
Metal and electrical industry
Whole manufacturing industry
Offshoring in the two years before ...
Reshoring in the two years before ...
Prof. Dr. Steffen Kinkel 5
Issues: Different points in time, different economic conditions,
different phases in the „offshoring and backshoring lifecycle”
“Adjusted” shares of backshoring
companies in European countries
CountryShare of companies
active in reshoring
Time-frame
(years covered)
“Adjusted” share of companies active
in reshoring over a 2 years period
Sweden 27,0% 6 9,0%
Ireland 13,0% 3 8,7%
Belgium 9,5% 3 6,3%
Slovakia 9,0% 3 6,0%
France 14,0% 5 5,6%
Denmark 13,0% 6 4,3%
Finland 13,0% 6 4,3%
DACH 4,0% 2 4,0%
Portugal 6,0% 3 4,0%
Netherlands 6,0% 3 4,0%
Selected European countries
(EMS survey)4,0% 2 4,0%
UK 13,0% 8 3,3%
Germany 3,0% 2 3,0%
Estonia 3,5% 3 2,3%
Lithuania 2,0% 3 1,3%
Bulgaria 2,0% 3 1,3%
Romania 1,0% 3 0,7%
Source: Kinkel et al. (2017): Measuring reshoring
trends in the EU and the US, Deliverable 4.1 of the
MAKERS project, Karlsruhe
Prof. Dr. Steffen Kinkel 6
56%59%
43%
52%53%
68%
33%28%
31%25%
32%
27%21%
20%
15%13%
11%6%
33%
6%11%
5%
5%0%2%
0%13%
19%
0% 10% 20% 30% 40% 50% 60% 70%
Flexibility, Ability to deliver (2015)(2012)(2009)
Quality (2015)(2012)(2009)
Capacity utilisation (2015)(2012)(2009)
Transport costs (2015)(2012)(2009)
Coordination (2015)(2012)(2009)
Infrastructure (2015)(2012)(2009)
Labour costs (2015)(2012)(2009)
Loss of know-how (2015)(2012)(2009)
Proximity to R&D at home (2015)(2012)(2009)
Availability of skilled workers (2015)(2012)(2009)
Source: German Manufacturing Survey 2015, Fraunhofer ISI
Main motives for backshoring of
manufacturing activities (German evidence)
Flexibility and coordination have
become more important
Quality abroad still an issue
Labour costs and availability of
skilled personnel abroad have lost
in importance
Additional important reasons from
other research: “Made in” reputation
effect, total costs of sourcing
Prof. Dr. Steffen Kinkel 7
Industry 4.0 enabling technologies
application levels – long ways to go
37%
15%
5%
23%
26%
19%
6%
20%
21%
37%
34%
30%
16%
29%
55%
27%
0% 10% 20% 30% 40% 50% 60%
1-49 employees
50-249 employees
250+ employees
All companies
Level 3 Level 2 Level 1 Level 0
Based on three
technology fields:
(1) Digital management
systems, (2) Wireless
human-machine comm.,
(3) CPS-based operations
Levels = number of fields
in which companies have
implementations
Large firms much more
active than small firms
Source: Kinkel, S. and Jäger, A. (2017): Auslandsverlagerungen, Rückverlagerungen
und Digitalisierungsverhalten in der deutschen Industrie. Trends und Auswirkungen
für den Produktionsstandort Deutschland, Karlsruhe
Prof. Dr. Steffen Kinkel 8
Correlations of Industry 4.0
and backshoring
Significant positive correlation between the use
of Industry 4.0 enabling technologies and the
backshoring propensity of German
(also Austrian and Swiss) manufacturing companies
“Advanced users” (level 3) of Industry 4.0 enabling
technologies display on average a 10-times higher
backshoring propensity than "non-users" (level 0)
Two arguments:
Use of I4.0 enabling technologies facilitate increased
automation and productivity of the German factory
site, making labour arbitrage of low-cost countries (LCC)
less appealing and economies of scale more important
Even more important: Use of I4.0 enabling technologies
facilitate increased flexibility and efficient production
of individualized solutions, providing incentives for
firms to keep/reshore production close to their European
customers ( local value chains).
Cox & Snell: 0,055 Nagelkerkes: 0,230Regression
coefficient B Sig.
Step 1 Ln #employees ,072 ,673
sec99_other manufacturing -,038 ,974
sec24_metal & metal components -,093 ,938
sec26_Data processing equipment,
electronic and optical products
,691 ,561
sec27_electrical equipment ,439 ,724
sec28_machinery & equipment -1,023 ,415
medium batch size ,329 ,593
large batch size -,152 ,850
medium complex products -,383 ,532
complex products -,248 ,730
supplier company -1,485 ,004
main competition factor: price/cost ,574 ,310
Ln import quota of inputs -,143 ,468
Ln export quota of inputs 1,101 ,004
Ln share of unskilled workers ,137 ,439
I40-enabling-use-til-2013_level1 1,884 ,095
I40-enabling-use-til-2013_level2 1,932 ,076
I40-enabling-use-til-2013_level2 2,618 ,016
Constant -8,946 ,000
Source: Kinkel, S. and Jäger, A. (2017): Auslandsverlagerungen, Rückverlagerungen
und Digitalisierungsverhalten in der deutschen Industrie. Trends und Auswirkungen
für den Produktionsstandort Deutschland, Karlsruhe
Prof. Dr. Steffen Kinkel 9
Technical key competences:
Software development of modular applications (apps) and IT-based platforms
Integration with the programming of machine and plant controls
IT security and user-oriented IT design
Non-technical competences:
Comprehensive understanding of customer problems and business models
Analysis of complex data and making sense as “smart data”
Interdisciplinary cooperation, particularly between engineers and IT specialists
Agile development approach, early experimentation and testing, positive culture of
error: "be brave and fail fast“
Key competences for the
digital integration
Source: Kinkel et al. (2016): Digital-vernetztes Denken in der Produktion.
Studie für die IMPULS-Stiftung des VDMA, Karlsruhe, November 2016
Prof. Dr. Steffen Kinkel 10
Conclusions for Industrial and
Innovation Policy
The advantages of cost-based offshoring to LCC have clearly diminished, however
offshoring intensity is still higher than backshoring intensity
Positive correlation between the adoption of I4.0 enabling technologies and backshoring
limited with respect to jobs directly created at the home base, as “new production” is
more automated
Indirect effects through local purchase of equipment and infrastructure as well as
local sourcing of inputs and services
What policy can do
Support regional clusters and local value chains
Support local demand for innovative and more sustainable solutions (e.g. public
procurement, “Made in” local value chains)
Support development and adoption (!) of smart and agile production systems (e.g.
Industry 4.0, flexible and individualized manufacturing, additive manufacturing)
Support development of smart, data-driven services and business models for B2B
Support education, qualification and competence development of skilled personnel,
limit bottlenecks
Prof. Dr. Steffen Kinkel 11
Prof. Dr. Steffen Kinkel
ILIN Institute for Learning and Innovation in Networks
(www.ilin.eu)
Karlsruhe University of Applied Sciences
Questions?
Prof. Dr. Steffen Kinkel 12
Target and source countries of
manuf. offshoring and backshoring10%
49%51%
13%14%
16%
23%27%
7%
32%17%
9%
16%4%
14%
0%0%
9%
0%0%0%
13%0%
54%55%
40%
31%30%
27%
21%25%
16%
8%11%
10%
7%8%9%
2%2%
12%
2%2%3%
1%0%
-60% -50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 50% 60%
EU 13 (2015)(2012)(2009)
China (2015)(2012)(2009)
Rest of Asia (2015)(2012)(2009)
EU 15 (2015)(2012)(2009)
North America (2015)(2012)(2009)
Rest of Eastern Europe (2015)(2012)(2009)
Latin America (2015)(2012)(2009)
Rest of World (2015)(2012)(2009)
Source countries of Reshoring(n = 36 (2015) | 32 (2012) | 46 (2009))
Target countries for Offshoring(n = 128 (2015) | 154 (2012) | 161 (2009))
Source: European Manufacturing Survey 2015, Fraunhofer ISI
Prof. Dr. Steffen Kinkel 13
Main motives for offshoring of
production activities
Main motives for
manufacturing relocations
Manufacturing
relocation mid
2004 to mid 2006
Manufacturing
relocation 2007 to
mid 2009
Manufacturing
relocation 2010 to
mid 2012
Manufacturing
relocation 2013 to
mid 2015
Trend
Labour costs 80 % 77 % 71 % 75%
Access to new markets 27 % 28 % 28 % 27%
Vicinity to key customers 21 % 29 % 26 % 29%
Vicinity to to relocated
production capacities n.a. 16 % 23 % 20%
Access to raw materials n.a. n.a. 15 % 12%
Import restrictions n.a. n.a. 11 % 9%
Lack of skilled workers n.a. 8 % 9 % 13% ()
Taxes, levies, subsidies 11% 12% 5% 11%
Following competition n.a. n.a. n.a. 10% n.a.
Prof. Dr. Steffen Kinkel 14
Use of Industry 4.0 enabling technologies
in German manufacturing industry
67%
11%
33%
19%
31%
30%
27%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Enterprise Resource Planning Systems (ERP)
Product Lifecycle Management Systems (PLM)
Digital visualization
Mobile devices for programming / operation of machines
Digital exchange of disposition data (SCM)
Techniques for automation and control of internal logistics
Real-time manufacturing execution system (MES)
Source: German Manufacturing Survey 2015, Fraunhofer ISI
Digital Management Systems
Wireless human-machine communication
CPS-related operations
Prof. Dr. Steffen Kinkel 15
Cox & Snell: 0,077 Nagelkerkes: 0,168Regression
coefficient B Sig.
Step 1 Ln #employees ,449 ,000
sec99_other manufacturing -,435 ,475
sec24_metal & metal components -,325 ,617
sec26_Data processing equipment,
electronic and optical products
-,291 ,706
sec27_electrical equipment 1,094 ,097
sec28_machinery & equipment ,159 ,808
medium batch size ,377 ,255
large batch size -,349 ,472
medium complex products ,039 ,917
complex products ,321 ,451
supplier company ,153 ,573
main competition factor: price/cost ,788 ,012
Ln import quota of inputs ,153 ,213
Ln export quota of inputs ,215 ,107
Ln share of unskilled workers ,121 ,271
I40-readyness-til-2013_level1 ,323 ,430
I40-readyness-til-2013_level2 ,463 ,223
I40-readyness-til-2013_level2 ,250 ,538
Constant -6,437 ,000
Logit model for offshoring
propensity of companies
Large firms are
more active in
offshoring
Companies with a
focused price/cost
leadership
strategy are more
active in offshoring
No effects of
Industry 4.0
readiness on
offshoring
propensity
Prof. Dr. Steffen Kinkel 16
Cox & Snell: 0,055 Nagelkerkes: 0,230Regression
coefficient B Sig.
Step 1 Ln #employees ,072 ,673
sec99_other manufacturing -,038 ,974
sec24_metal & metal components -,093 ,938
sec26_Data processing equipment,
electronic and optical products
,691 ,561
sec27_electrical equipment ,439 ,724
sec28_machinery & equipment -1,023 ,415
medium batch size ,329 ,593
large batch size -,152 ,850
medium complex products -,383 ,532
complex products -,248 ,730
supplier company -1,485 ,004
main competition factor: price/cost ,574 ,310
Ln import quota of inputs -,143 ,468
Ln export quota of inputs 1,101 ,004
Ln share of unskilled workers ,137 ,439
I40-enabling-use-til-2013_level1 1,884 ,095
I40-enabling-use-til-2013_level2 1,932 ,076
I40-enabling-use-til-2013_level2 2,618 ,016
Constant -8,946 ,000
Logit model for backshoring
propensity of companies
Company size no
factor for backsho-
ring propensity
Supplier companies
are more reluctant
to backshoring
Export-intensive
firms are more
active in back-
shoring, to shorten
their upstream
value chains
Positive effects of
use of Industry 4.0
enabling
technologies on
backshoring
propensity