An Empirical Analysis of Manufacturing Re-shoring
and Supply Chain Risk
By
loannis M. Kyratzoglou
Master of Science & Mechanical Engineering Degree, Mechanical Engineering
Massachusetts Institute of Technology, Cambridge, 1986
Submitted to System Design and Management Program
In Partial Fulfillment of the Requirements for the Degree of
Master of Science in Engineering and Management
at the
Massachusetts Institute of Technology
June 2013
MASSACHUSETTS INSTME
OF TECHNOLOGY
JUN 2 6 20
LIBRARIES
C 2013 Massachusetts Institute of Technology. All rights reserved.
Signature of Author
Signature redacted
(I
V
V
loannis M. Kyratzoglou
Fellow, System Design and Management Program
May 25, 2013
Signature redacted
Certified by
David Simchi-Levi
Professor of Engineering Systems
C_
Accepted by
f"
(rhsil
Supervisor
Signature redacted,
Patrick Hale
Director, System Design and Management Program
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An Empirical Analysis of Manufacturing Re-shoring and
Supply Chain Risk
by
loannis M. Kyratzoglou
Submitted to the System Design and Management Program
on May 25, 2013 in Partial Fulfillment of the
Requirements for the Degree of Master of Science in
Engineering and Management
Abstract
After an exodus ofjobs in the last few years, the U.S. is committed to improving its
manufacturing competiveness by investing in manufacturing innovation and increasing its labor
force productivity. With rising labor costs in China and the current economic recession in Europe
the timing could not be better for the U.S. to surge forward to gain back its competitive edge.
These advantages along with the expected U.S. shale oil energy boom create an attractive
opportunity for U.S. companies to re-shore their operations. This empirical manufacturing study
analyzes the survey responses from a large number of companies with global manufacturing
footprint and examines whether U.S. companies consider re-shoring their operations. The results
show that a significant proportion, 33.6 percent of the U.S. companies are "considering" bringing
manufacturing back to the U.S., while 15 percent of U.S companies are "definitely" planning to
re-shore to the U.S. This is a very insightful finding and it shows that the re-shoring trend is
picking up speed. We used the survey data to identify what drives this trend and whether this
trend has made an impact.
Competition in the manufacturing industry is instigating companies to reduce their supply chain
costs. To retain their competiveness, companies are responding by implementing strategies such
as lean manufacturing, outsourcing and offshoring. However, these strategies have significantly
increased the company's exposure to supply chain risks. For example, lean manufacturing means
lower inventory levels, and a high risk incident can cause a major disruption in operations.
Similarly, as outsourcing and offshoring operations grow, supply chains become geographically
dispersed and exposed to various types of risks. As a result, many companies are concerned
about their supply chain resilience but only a few are effectively managing risk. Therefore,
companies need to plan their supply chain strategy to effectively respond to various risks. This
empirical study develops a framework to characterize the supply chain risk maturity level of each
company. We then apply the maturity model to examine resiliency and operational effectiveness.
The results offer a number of important insights: For example, companies with mature supply
chain and risk management processes are more resilient than immature ones. The operational
3
insights gained by this research can help companies manage today's challenges and prepare for
tomorrow's opportunities.
Thesis Supervisor:
David Simchi-Levi
Professor of Engineering Systems
4
Acknowledgements
There are a lot of people that I would like to thank for making this Thesis work so successful.
Without their support the completion of the Thesis would not have been possible.
0
First, I am grateful to Professor David Simchi-Levi who accepted me in his group and
allowed me to pursue a thesis in an important topic. His remarkable supply chain
insights, thesis direction and thought leadership were essential to complete this research.
* I would like to thank my family, especially my wife Kathleen and my children loannis Jr.
and Anastasia. Without their support, patience and encouragement this work would not
have been possible.
* I would also like to thank my management at The MITRE Corporation, who fully
sponsored and supported my SDM studies and enable me to advance my professional
development.
0 I also appreciate the collaboration and important contributions of Dr. Constantine
Vassiliadis of PwC N.V. Dr. Vassiliadis was instrumental in designing the survey,
working with me on formulating the Insights from the Survey and, reviewing the
material.
0 Finally, I really appreciate the support of Ms. Janet Kerrigan. Her IT skills help me make
significant forward progress in critical stages of the project.
5
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6
Table of Contents
1.
An Empirical Analysis of Manufacturing Re-shoring .......................................................................
1.1
Intro d uctio n .................................................................................................................................
13
1.2
Survey Need Statem ent ..............................................................................................................
14
1.3
Survey Data Characterization Summ ary.................................................................................
15
1.3.1
Manufacturing Company Distribution by Industry Type.................................................15
1.3.2
Manufacturing Companies Distribution by Revenue Size ...............................................
1.3.3
US HQ Manufacturing Companies Distribution by Manufacturing Operations..............17
1.4
Survey Data A nalysis ...................................................................................................................
Distribution of Manufacturing Activities, by Company Size..........................................
1.4.1
2.
17
18
19
1.5
U.S. Manufacturing Companies Distribution by Market Demand (Sales)...............................20
1.6
Manufacturing Operations vs. Company Sales Correlation ...................................................
21
1.7
Manufacturing Operations vs. Sales Comparison for Different Regions ................................
22
Re-shoring Survey: Hypothesis............................................................................................................24
2.1
Hypothesis Testing ......................................................................................................................
24
2.1.1
Considering vs Definitively Planning to Moving Back Decision......................................24
2.1.2
2012-2015 Re-distribution of Manufacturing Operations ..............................................
26
2.1.3
Hypotheses Testing .............................................................................................................
30
2.2
3.
13
Drivers and Government Action to Support Re-shoring .......................................................
30
2.2.1
Decision Drivers to Consider Re-shoring .........................................................................
30
2.2.2
Suggested Government Actions to Incentivize Companies to Re-shore.........................32
2.2.3
Challenges in Bringing Production Back to US ................................................................
2.2.4
Supply Chain Strategies Used to Support Re-shoring Decision......................................34
2.2.5
Current Manufacturing Strategy Used by Companies ...................................................
33
35
2.3
Associations Between Operations, Sales, R&D and Product Development...........................36
2.4
Sum m ary .....................................................................................................................................
38
An Empirical Analysis of Supply Chain and Risk Management........................................................41
Intro d uctio n .................................................................................................................................
41
3.1.1
Backgro und ..........................................................................................................................
41
3.1.2
The Values of Mature Risk Management and Operational Resiliency...........................42
3.1.3
The Need for the Study ..................................................................................................
3.1
7
43
3.1.4
4.
5.
6.
Today's C hallenges ..............................................................................................................
43
Supply Chain and Risk Management: Survey Demographics..........................................................45
4.1
Survey Data Sum m ary ..................................................................................................
4.2
Globalization of the Supply Chain ...........................................................................................
47
4.3
Sources of Supply Chain Risk ..................................................................................................
48
4 .4
M easu ring R isk ............................................................................................................................
50
4.5
What Parameters are Companies Most Sensitive To............................................................
51
4.6
W hat Com panies Do to Address Risks.....................................................................................
52
...45
Supply Chain Risk: Capability M aturity Framework .......................................................................
54
5.1
Levels of M aturity along Two Dimensions ..............................................................................
54
5.2
The Seven Supply Chain Risk Enablers of Maturity ................................................................
54
5.3
The Four Levels of M aturity in Supply Chain Risk ..................................................................
56
5.4
Hypotheses and Survey Testing .............................................................................................
58
Supply Chain Risk: Key Insights ......................................................................................................
60
6.1
Key Insight #1: The Majority of the Companies Have Immature Supply Chain Operations And
Risk M anagem ent Processes In Place ................................................................................................
60
6.2
Key Insight #2: A Company May Be Mature In One Risk Reduction Enabler Area and Immature
In A no th e r ...............................................................................................................................................
62
6.3
Key Insight #3: Companies with Mature Capabilities In Supply Chain And Risk Management Do
Better Along All Dimensions Of Operational And Financial Performance ..........................................
63
6.4
Key Insight #4: Supply Chain Disruptions Have Significant Impact on a Company's Business and
Financial Pe rfo rm ance .............................................................................................................................
65
6.5
Key Insight #5: Companies with Mature Supply Chain and Risk Management Processes Are
More Resilient to Risk Disruptions than Companies with Immature Risk Management Processes.......66
6.6
Key Insight #6: Mature Companies Investing In Supply Chain Flexibility Are More Resilient To
Disruption than Those That Do Not Invest In Supply Chain Flexibility...............................................67
6.7
Key Insight #7: Mature Companies Investing in Risk Segmentation Are More Resilient To
Disruptions than Those That Are Not Investing In Risk Segmentation ..............................................
6.8
69
Key Insight #8: Mature Companies Applying Push-Pull Supply Chain Strategy Are More
Resilient To Risk Disruptions Compared To All Companies.................................................................73
6.9
Linking Supply Chain Risk with Operational and Financial Performance ...............................
7.
Supply Chain Risk: Summary and Recommendations.....................................................................77
8.
Appendix A - Operations and Financial Definitions........................................................................
8
75
79
9.
10.
Appendix B. Capability M aturity Classification M odel...................................................................
Bibliography.....................................................................................................................................83
9
82
Table of Figures
Figure 1. Pie Chart of Manufacturing only Companies by Industry .......................................................
16
Figure 2. Distribution of Manufacturing only Companies-by Revenue Size .......................................
17
Figure 3. Distribution of Manufacturing Companies by Consolidated Revenue Size ............................
17
Figure 4. US Manufacturing Companies--Distribution of Manufacturing Operations ...........................
18
Figure 5. Distribution of Manufacturing Activities, by Company Size ...................................................
19
Figure 6. US-Based Manufacturing Operations Trend vs US HQ Company Revenue Size..................20
Figure 7. Distribution of Sales by Company Size ..................................................................................
21
Figure 8. Distribution of Manufacturing and Sales vs. Company Size ...................................................
22
Figure 9. Percentage of Manufacturing and Sales Comparison for Different Regions ..........................
23
Figure 10. Comparison of Considering vs Definite Planning to Move Back to U.S. by Aggregate...........25
Figure 11. Comparison of Considering vs. Definite Planning to Move Back to US by Size..................26
Figure 12. Re-distribution of Mfg. Operations for Companies Considering to Re-shore ....................... 27
Figure 13. Distribution of Sales per Region for U.S. Companies Considering to Move ........................ 28
Figure 14. Changes in the Distribution of Manufacturing Operations 2012-2015.................................28
Figure 15. Industries Considering Moving Back ..................................................................................
29
Figure 16. Decision Drivers to Bring Manufacturing Back ...................................................................
32
Figure 17. Ranked Government Actions to Support Re-shoring ...........................................................
33
Figure 18. Challenges of Bringing Production Back to U.S. .................................................................
34
Figure 19. Strategies Used to Support Decision to Move Back ..............................................................
35
Figure 20. Current M anufacturing Strategy ...........................................................................................
35
Figure 21. Factors for Companies to Move Production outside of U.S. ...............................................
36
Figure 22. M atrix Correlation Graph ......................................................................................................
37
2
Figure 23. Linear Relations and R values for the variables ..................................................................
38
Figure 24. Distribution of Companies by Region ..................................................................................
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
45
25. Distribution of Company Participants by Industry ................................................................
46
26. Size of Companies Based on Sales Revenue .........................................................................
46
27. 2012 Sales vs Operations for the Manufacturing Industry...................................................
47
28. Percent of companies with global manufacturing presence...................................................48
29. Supply Chain Risks that a company is most exposed to.......................................................49
30. High and Low likelihood that these risk will materialize .....................................................
50
31. Risks with High and Low potential impact on performance.................................................51
32. Parameters that a company's supply chain operations are most sensitive to........................52
33. Company Actions to address supply chain risks...................................................................53
Figure 34. The 7 Supply Chain and Risk Reductions Enablers ..............................................................
55
Figure 35. The Supply Chain and Risk Management Capability Maturity Model.................................58
Figure
Figure
Figure
Figure
Figure
Figure
Figure
36.
37.
38.
39.
40.
41.
42.
Capability Maturity Profile of the Surveyed Companies.....................................................
61
Functional Area M anaging Risk ...........................................................................................
62
Mature capability companies performed operationally better than immature ones..............64
Mature capability companies performed financially better than immature ones .................. 65
Percentage of Companies that suffered 3% or higher impact on their performance.............66
Key Performance Indicator resilience to disruptions between mature and immaturity levels ...67
Key supply chain value driver to match customer value proposition...................................68
10
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
Figure
43. Performance of mature cost-efficient vs mature flexible-response companies......................69
44. The key value dimension of the leading customer value proposition of survey participants .... 70
45. Percentage of companies that perform risk strategy segmentation....................71
46. Key product differentiators for risk strategy segmentation....................................................71
72
47. Difference in performance impact based on risk strategy segmentation ...............................
73
...............................
48. Difference in performance impact based on risk strategy segmentation
74
49. Operational Strategy ..................................................................................................--------......
74
50. Companies with Push-Pull strategies are more resilient ........................................................
51. Link between Supply Chain Risk decisions and performance...............................................75
11
Table of Tables
Table 1. Survey Data Summary ..................................................................................................................
15
Table 2. Capability Classification per Risk Reduction Enabler per Company .......................................
63
Table 3. The Capability M aturity Classification M odel..........................................................................
82
12
1. An Empirical Analysis of Manufacturing Re-shoring
1.1
Introduction
In the 1970 and 1980's companies based their operations and sales in US or Western Europe to
serve home and neighboring countries. In the 90's and 00's rising labor costs and government
regulations forced a number of companies to start looking to outsource their manufacturing
operations elsewhere. Far East Asia nations, like China, India and Taiwan, were offering better
manufacturing operations opportunities with subsidies, low-wage labor, stable economic
environment, lax regulations and monetary rigging. Further, rapid growth in emerging and
untapped economies like China's was offering higher returns and benefits. With this strategy
they were successful in luring US companies to relocate their manufacturing operations there.
Large scale industrial manufacturing parks, such as the Tianjin Economic Development Area
(TEDA) and Shanghai Fengpu were built to host and attract foreign business. Shanghai Fengpu
is one of China's top cheap labor manufacturing centers. About an hour west of Sichuan's
capital Chengdu, is Foxconn Technology Group, one of Apple's biggest manufacturing partners.
Foxconn employs hundreds of thousands as they help build electronics products for Apple and
many other global brand names, such as Amazon's Kindle and Microsoft's Xbox. [1]
These parks were built with the sole purpose to attract foreign capital. Pretty soon, after
manufacturing, research and development (R&D) moved abroad and then, product development
(PD) followed course. TEDA is one China's top high-tech innovation centers attracting such
global R&D and product development investments. So this is not only about manufacturing. In
the meantime, over the past-ten years, millions of US jobs moved abroad. Manufacturing had
become the foundational cornerstone of China's economic growth and global market presence.
In 2013, rising Chinese labor costs, concerns over Intellectual Capital (IP) theft and, longer
supply chain lead times, high fuel costs are causing companies, with more than $1 B in sales
revenues, to consider regionalizing their manufacturing operations. Google recently announced
that its Nexus Q streaming media player would be manufactured in the US. Apple also
announced a limited manufacturing of their products in the US. General Electric and Ford start
moving some of their manufacturing back in the US. Caterpillar is moving assembly of its largest
excavators from Japan to Texas. The question that is being posed is: Based on this information,
13
is there a trend that US reached a turningpoint and has become an attractiveplacefor reshoringmanufacturing?"
The U.S. Bureau of Labor Statistics, in their Current Employment Statistics Highlights [2] states
that in the month of February 2013 +14,000 manufacturing jobs were added in the economy.
Fabricated metal products added 6,000 out of the 14,000 while employment in motor vehicles
and parts manufacturing was essentially unchanged. The manufacturing industry has recovered
178,000 since January 2010. US president Obama, in his 2013 State of the Union Address
mentioned that 500,000 jobs were added over the three years. The next question is: Is there a
real trend that manufacturingjobs are "coming back?"
U.S. manufacturing has been one of the pillars of American prosperity. Today, more than ever, it
is essential that the U.S. continues its leadership in manufacturing-to sustain the foundations of
the Nation's economic prosperity and national security and to meet new challenges in the
domains of technology innovation, energy, transportation, health care, and education. If U.S.
wants to maintain its technological innovation, scientific R&D, product development and
manufacturing leadership then these areas become central priorities of the US Government
policy makers. A few studies [3] address some of the policy questions, but "What are the
manufacturingpolicy initiatives and incentive actions that the US Governmentpolicy makers can
take to support bringing manufacturingback and create new jobs?" U.S. economic growth can
be based on rethinking about the next manufacturing shift.
1.2
Survey Need Statement
To receive responses to the questions posted in the previous section the Massachusetts Institute
of Technology (MIT) Forum for Supply Chain Innovation and Supply Chain Digest (SCDigest)
publication launched the "2012 Re-shoring Survey." The discussion above has given rise to
three manufacturing hypotheses:
1.
U.S. manufacturing reached a turning point and has become an attractive place for reshoring manufacturing operations.
2. Time has reached for U.S. companies to change their manufacturing strategy and move
back to U.S.
3. U.S. Government is applying the right government policies to bring manufacturing back
14
The survey was distributed to members of the MIT Forum for Supply Chain Innovation and
Supply Chain Digest. In total, 340 participants completed the survey, providing the input for this
thesis study and the Annual Re-shoring Report [4]
1.3
Survey Data Characterization Summary
Decision makers and executives from 340 companies across a wide range of primary industries
participated in the survey, which MIT Forum and SCDigest conducted in July and August of
2012. From the 340 participated industries, 198 were manufacturing industries. The list of
industry types and the selection of the subset of 19 manufacturing industries is based upon the
North American Industrial Classification [5], which is a United States Government Department
of Labor Bureau of Labor Statistics classification system. A U.S. headquarter company is
defined as the company that has their headquarters in the U.S. Table 1 below summarizes the
survey characteristics.
#
Description
Data
1
2
3
4
Survey Closure Date
No. of Participants
No. of Manufacturing Companies Only
No. of US companies (defined as HQ in US)
Table 1. Survey Data Summary
9 Sep 2012
340
198
156
1.3.1 Manufacturing Company Distribution by Industry Type
The distribution of manufacturing only companies by industry type is shown in Figure 1 and
Figure 2. Based on the company's businesses we have a good cross section of industries from 19
U.S. Government manufacturing categories.
15
AeupA
PodU
d
Other Mactinery
Parts ManLtactu r ng, 3.5%
Primary Metal M anUfactur ng,
0.
Apparel aid Texlle, 4,0%
Manufacturing Only Companies by Industry
Ind,,sgbia Machifievy
Marufacturing, '1%
Motor
Vchiclc
Srfther Marufacrtiring
PrudLLcb .hIC PJul6_
-Marufacturin& 5.65I
* Computer &Electronic )rocucts MFG
a Food & Beverage Product MEG
a Chemicals
v Electricci Equipnerit, App lance and Comporent MG
a Pharmacpuicals and Medicine
n Motur Vehide Pruduck intL Par Manifcltui ing
Electrical Eqcipment,
Appliance and
Comporert MFG,
alrdLstnal
Machirery Manufacturing
w Apparel and Textiie
7.6%
* Aerospace Procucts and Parts Manufacturing
s Other Machinery Manutacturing
W Pr imaI y Metal M;JILtJLLu ng
Figure 1. Pie Chart of Manufacturing only Companies by Industry
Based on the sample size of 198 manufacturing only companies, the top industries responding to
the survey were:
1.
Computer and Electronic Product Manufacturing, 19.2 percent
2. Food & Beverage Product Manufacturing, 10.6 percent
3. Chemicals, 8.1 percent
4. Electrical Equipment, Appliance and Component Manufacturing, 7.6 percent
5. Pharmaceutical and Medicine, 7.1 percent
There is a miscellaneous manufacturing category that includes all other manufacturing categories
that has received the largest share of 27.8 percent. Further decomposition of this category
reveals a list of assorted manufacturing industries such as:
1. Personal Care Products
2. Golf Equipment manufacturing
3. Other types of manufacturing industries represented by 1 percent by proportion
16
1.3.2 Manufacturing Companies Distribution by Revenue Size
The distribution of manufacturing only companies by revenue size is shown in Figure 2. The
largest category of companies is the $1B - $1OB range with 22.5 percent and the smallest
category is $20M - $50M with 2.2 percent.
Size of Companies Based on Sales Revenues
Company Size
25.0%
S20McRev<50M
5.1%
3-$z
5106<
S50M<Revc$10O N0
$A<Rev<$
/
I
M5.6%
5,C~~2Ql
t%
6%
(1
5.0%
525C*M<ReY<6500M
Rioe
121%
MI I.I
n Company 'An.
£o,.%%$108<ReY<$2SB
B.
\ 5$0evMS<O
M,61%
Rev<$25
.%
Figure 2. Distribution of Manufacturing only Companies-by Revenue Size
Figure 3 shows the segmentation and distribution of companies using only three size categories:
by proportion 52.5 percent of the companies are less than $1B in sales revenue, 22.2 percent are
between $1B and $1OB and 25.3 percent is greater than $25B.
Company Size
Figure 3. Distribution of Manufacturing Companies by Consolidated Revenue Size
1.3.3
US HQ Manufacturing Companies Distribution by Manufacturing Operations
The first question is: Where is your manufacturing operationsfootprint? The question
introduces one of the two interelated concepts that we will examine later - manufacturing
operations footprint and the revenue sales footprint. The distribution of manufacturing
operations for all US HQ manufacturing companies is shown in Figure 4. 119 out of the 156 US
17
manufacturing companies provided data on their current distribution of their manufacturing
operations. A U.S. manufacturing company is defined as the one that has its Headquarters in the
U.S. Thirty seven companies chose not to reveal any information about their distributions of
operations strategy. In terms of revenue size, we have a good representation of the
manufacturing companies that are operating globally.
South America
1.6%_
Mexico/Central
Amnerica, /%istribution
Midcle East/Africa,
0.5%
of Manufacturing
Operations for US Companies
other Asia, /.1%
Japan, 05%
* Canada
n Western Europe
* Eastern Europe
* China
m Japan
Other Asia
Mexico/Central America
South America
Eastern Europe, 2.0%
Western Europe, 5.6% ~-
Middle East/Africa
Canada, 17%
Figure 4. US Manufacturing Companies--Distribution of Manufacturing Operations
The survey responses reveal that about 52.6 percent of the U.S. Companies have their
manufacturing operations in the U.S. and 21.1 percent in China. We also note, 61.8 percent of
the manufacturing operations are based in North America, 7.6 percent in Europe, and 28.6
percent in SouthEast Asia. Hence, despite the common preception that most of U.S.
manufacturing has moved overseas, the survey data show that U.S. companies have their main
manufacturing thrust in the U.S. and North America region, closer to the market demand.
1.4
Survey Data Analysis
In the following sections we perform an analysis of the static and dynamic characteristics of
manufacturing sector and examine any emerging trends or shifts in the landscape. From Figure
4, the analysis provides results at the agregate level and does not distinguish the footprint of the
18
companies in terms of industry type or revenue size. This type of revenue size segmentation
analysis is performed in the next section.
1.4.1 Distribution of Manufacturing Activities, by Company Size
To facilitate analysis of the survey results we will segment the Revenue (Sales) Size into three
categories (see Figure 3):
Small size companies with revenue less than $1 billion (Rev < $1 B)
1.
2. Mid size companies with revenue between $1 billion and $10 billion ($lB <Rev < $10B)
3. Large size companies with revenue greater that $10 Billion (Rev > $1 OB)
Let us focus in the blue-colored section of the pie chart for each of the A, B and C graphs of
Figure 5. The blue area sector indicates the portion of the manufacturing operations performed
in the US. We note that as the company's revenue increases,the proportionof U.S.
manufacturingoperations in the U.S. decreases.The percentage values decline from 60 percent
for small companies, to 50.4 percent for mid-size and, to 35.3 percent for large size companies.
mexicoAxentrai-
Soith Ame-ca,
Middl
"ast"Afr"a.0.0%
Amer,6.5%
Rvnue1
r~xo/et
$.2%
<e
R
Mi~idle
South America,
2.0%
n
E
$BcRvne$
$1B < Revenue< $10
* US
0 Canada
aULS
Other Asia, 67%
Japan, 0 3
0 Canada
Othet Asia,
a Weter
Japan, 0.8%
a Western Europe
aEastern
5.6%
UCiina
a China
n Japan
a Japan
wOther Asia
0.6%
Fwnppe
Mexica/Central Arnerca
Soilt Arerica
Eastern Europe,
349%
a Middle East/Africa
2 39(
F r np
Otner Asia
a Mexiro/Central America
South America
Eastern
Europe,
n
UEastern Eiuope
Europe
w Middle East/Africia
Canad
Canada, 0.9%
srxattrArrera,
A
Mexku/Centtra
America, 8.5%
%
MiddleEast/Ahue,
19%
Rev > $106
* us
a Canada
aWestern Europe
As Company's Revenue Increass,
Proportion of Manufacturing i the US
* Eastern Europe
IkawEsenErp
0 China
05%
*apan
Decrenea
aOther Asia
, Mexi
Canada,
3.%
urope,
Eastern Europe,-9.
Fg 2%
Figure 5. Distribution of Manufacturing Activities, by Company Size
19
/Certial
Amieta
Scuth America
Middle E ast/Afr Ia
The downward trend in the U.S.-based manufacturing operations vs. US company size is also
illustrated in Figure 6 below. Figure 6 shows a bar chart with a polynomial trend-line of the 6050-35 percentage values shown in Figure 5. The survey data for China-based manufacturing
operations vs. US company size is also shown in the same graph. Based on the data trends with
respect to China, we cannot draw any conclusion.
Proportion of MFG Activities in US vs
70.0% T
Company Revenue Size
60.0%
0.4%
50.0%
4 40.0%
--
--
-us
.30.0%---
Chn
China
V
5
20.0%
Poly. (US)
10.0%
0.0%
Rev<$18
$13<cev<$10B
Rev>$10B
Company Revenue Size
Figure 6. US-Based Manufacturing Operations Trend vs US HQ Company Revenue Size
1.5
U.S. Manufacturing Companies Distribution by Market Demand (Sales)
The second question is: From what region is most ofyou market demand and revenue sales
comingfrom? The answer to this question is important. In the previous section we addressed
regional distribution of manufacturing operations by company size. In this section we will
address regional distribution of sales by company size. Only 83 companies provided information
about their Sales Strategy.
20
WexkojCe'traL_S uihAler ca, 1. 1
mwiae
, 5%
sa 39 6
fastorn Etrope,
1.4t
.WiddeEaws/affkAl
Proprion of Sale
Proportion of Sales
Coming from Different Regions
< Rev < $108
Mesicc/Cenlral S3uth America
Coming from Different Regions
Rev< $1B
meria, 2.%
O
Middle East/Africa,
30
i$18
aUS
aus
a C;nada
a Wsnada
* WStVI: EUf ipe
a Eastern Europe
a China
Eastern
A Werterf
Canad,.0A
r turope
Europe,
a Eastern Europe
R
*China
2,1%
a Jpan
aOthei Asia
0 MexicoiEertral America
Siitltnera
Japan
*
a Other Asia
e aexkio/Centrl America
Canada, 44%
South America
d
South Anerica,
Mexico/Central
3.1%
ast/A'rica,
Middle
F
2
America, 2.5%
0 her Asia,
Middie East/Africa
Proportion of Sales
Coming from Different Regions
Rev > $10B
Japa~t, 2.615
As Company's Revenue Increases, US
Sales Propo
AtWesternEure
Eastern Euroipe
n DecreasesChina
Eastern
a lapan
Earpe
3,1%
a 0tWr Asia
1erricoICentri America
~
Canaa,
Souts America
Middle East/Afica
Figure 7. Distribution of Sales by Company Size
Figure 7 shows the distribution of sales by company size. Let us again focus in the blue-colored
section of the three pie charts. The blue area sector indicates the portion of the sales revenues
coming from the U.S. vs. other regions. There is another important insight: as the company's
revenues size increases, US salesproportiondecreases. U.S. companies with revenues less than
$1B have 69.4 percent of their sales coming from U.S., while the ones with revenues sales
between $lB and $10B have 55.6% percent of their sales coming from the U.S. Large
companies with more than $1OB in revenues have 43.9 percent of their revenue come from U.S.
In summary, it is not surprisingwhy these large companies are moving their operations
outside the U.S. More than 56 percent of their sales revenues come outside of U.S. and from
emerging markets such as Latin America, Western Europe and Middle East. Thus a regional
supply chain operations strategy will be more suitable for this scenario.
1.6
Manufacturing Operations vs. Company Sales Correlation
Now that we understand the downward trend patterns of manufacturing operations vs. company
size and sales per region vs. company size the next interesting questions is: what is the
21
correlationof the manufacturingfootprint to salesper regionfootprintfor different company
sizes?
The response to this question is addressed in Figure 8. The insight is that manufacturing
footprint and sales footprint in the regions are highly correlated (with a coefficient of
correlation closer to -0.8) indicating a high linear relationship. This insight is intuitive:
companies like General Electric or Intel may have 70 percent of their revenue come from outside
the US so a lot of their manufacturing activities and sales are outside the U.S.
Distribution of manufacturing and Sales vs
Company Size
700%
55.6%
600%
504
43,9%
_%_
49
_5
MFG
SALES
300%
Poly. (MFG)
20.0%
Poly. (SALES)
10.0%
0.0%
Rev < $18
$1B < Rev < $108
Rev > $108
Company Revenue Size
Insight: As Revenue Size Increases the Proportion of Manufacturing
Activities and Sales in US Decreases
Figure 8. Distribution of Manufacturing and Sales vs. Company Size
1.7
Manufacturing Operations vs. Sales Comparison for Different Regions
If we examine the distribution of manufacturing operations by region in the upper-left corner of
Figure 9 we notice that for US companies:
1.
A large concentration of manufacturing operations is in the US
2. A large size of sales comes from US
If we look at the pair of manufacturing operations plus sales across regions, at the aggregate
level we observe the following important insights:
1.
Sales exceeds manufacturing operations for developed countries by 20 percent
22
2. Manufacturing operations exceeds sales revenue by proportion for emerging markets by
20 percent
The Emerging Model on the right side of Figure 9 provides an insight for U.S. companies on:
where the revenues are coming from and where their manufacturing operations are
located.
70.0%
60.0%
9C.0%
Percentage of Manufacturing Operations and Sales for
Different Regions (US companies)
Emerging Model
WX 0%
50.0%
W-O%
60,0%
40.0%
30.0%
0.0%
"
SALES
00%
* MNFG
200%
10.0%
" MNFG
4C.0%
Sao%
L 16 L,
A,
t~-
an--
0
oSLE
2C.0%
1110%
C.0%
Developed Cmfnt es
-4
sSs
DevelOpin
D~eveloped (:*untie%
Emerging Markets
us
China
Canada
Mexico'Central America
Japan
Other Asia Regions
W. Europe
SouthAmerica
Middle East /Africa
Figure 9. Percentage of Manufacturing and Sales Comparison for Different Regions
23
2. Re-shoring Survey: Hypothesis
2.1
Hypothesis Testing
For this survey research we will use the deductive approach to develop the hypotheses and then
test it through empirical survey observations. Now, based on the reasoning provided in Section 1
it is hypothesized that:
H. There is no trend that manufacturing is moving back (aka re-shoring) to US
HA: There is a positive trend that manufacturing is moving back to US
We will use the survey results to qualitatively and quantitatively test the hypothesis.
2.1.1
Considering vs Definitively Planning to Moving Back Decision
In the survey we have asked the companies "whether they are consideringbringing
manufacturingback to the U.S. in the next three years (2012-2015)." In order to explore their
realistic intentions we have asked a second back-to-back reinforcing question:
Is Your Company Definitively Planning To Bring Manufacturing Back to
The U.S. In The Next Three Years (2012-2015)?
As addressed in Figure 10 in our Survey, about 33.6 percent of the companies reported that they
are considering moving manufacturing operations back in the U.S. (left chart). But when we ask
them whether they are definitively planning to get back (right chart) we get a much smaller
number, 15.3 percent. This is a comparison between Consideration vs Definitively Planning to
move manufacturing back to the U.S. at the aggregate. We observe the following:
I. Vt
1 Observation: There is a big difference between those that are discussing and those that
have made the decision to move back in the US. But even 15.6 percent it is an enormous
number. That is a change in manufacturing operations footprint.
2.
2 "d Observation:
If we look closely at the green sector of the pie-chart - about 1/3 of the
companies refused to discuss their strategy. This is one part of the survey: the companies
are willing to tell us everything else but in this question they were not willing to tell us.
24
All US Companies: Definitively
All US Companies:
Consider to Bring MFG Back
Plan to Bring MFG Back
"Consider to Brineg MIG Back
SNo
" Delfotiveiy Planning
" No Definitively Planning
Consde ation
Ia
k No Response
No Response
Figure 10. Comparison of Considering vs Definite Planning to Move Back to U.S. by Aggregate
This second observation is an important observation to a sensitive question even though we said
at the survey that we are not going to disclose any information (the survey data are kept
confidential). A set of companies considered that this may too sensitive to report and they have
not responded. The green color sector consists primarily of large size companies.
In Figure 11 we segmented the Consideringvs. Definitive Planningto Move Back decision by
size in order to understand the breakdown:
1.
Small size companies go down from 34%+12%
2. Mid-size goes down from 32+20%
3. Larger size does down from 27% - 8%
The largest drop is observed in small size companies but the biggest manufacturing operations
impact is from large size companies.
25
Consider to Bring MNFG Back
Rev < $1B
Definitively Plan to Bring
MNFG Back: Rev < $1B
L
" Cons der to Sting M1,F6 8ack
" Definitivey Pann
" No Conidefation
" No DefiritivelyPlaniing
a No Rewpur i
m No Fesponse
Consider to Bring MNFG Back
$1B<Rev<$1OB
W Ccmidef to Birg MNFGi
Definitively Plan to Bring
NFG Back: $1B< Rev a$10B
3k
U
m No Cwoi~i at kita
De kfinifely
planning
efililivety 'iin
WNo *VWoIW
No flepoe
Definitively Plan to Bring
Consider to Bring MFG
Rev > $10B
* Consider
ng
MFG Rev > $10B
a Definitively Planning
to Bring MNr G 3ack
0No Definitively Plaining
* No Consideration
a No Responsc
No Response
Figure 11. Comparison of Considering vs. Definite Planning to Move Back to US by Size
2.1.2 2012-2015 Re-distribution of Manufacturing Operations
Two more interesting questions arise. The first question is: "From the U.S. companies that are
considering to re-shore what is the re-distributionof their manufacturingoperationsfrom 2012
to 2015?" Figure 12 provides an illustrative answer. U.S. and Mexico are gaining +4.5 and
+1.8 percent respectively. This data may indicate a shift into a more regional strategy as Mexico
is emerging as the new North America manufacturing alternative due its proximity to the U.S.
markets. Note also from where the shifts are coming from: China and Western Europe are losing
-4.8 and -1.8 percent of their manufacturing capacity.
26
US Companies Considering to Reshore: Distribution of MFG
Operations 2012-2015
6,0%
4.5%
4.0%
m us
2.0%
S0.0%
0.0%
0.0%
0S
f
8
I
-2.0%
a Canada
0%
N Western Europe
-0.2%
8 Eastern Europe
N China
a Japan
-4.0%
* Other Asia
4.8%
60
z.,
N Meico/Central Ameri:a
lb
X
(Y
14$
b
ESouti
America
a*Midtdle East/Atrica
Figure 12. Re-distribution of Mfg. Operations for Companies Considering to Re-shore
The 2 nd question is: From the U.S. companies that are consideringto re-shorewhat is their
distributionof their sales?" Figure 13 indicates that the companies that are considering moving
back their manufacturing operations back to US have the bulk of their sales, 62 percent, in the
U.S. Now wonder why they want they change to regional strategy: the shift in demand is
expected to pull manufacturing operations and supply chains back to U.S. to move closer to their
primary market. The main drivers cited in the survey are better control, faster time-to market
and higher quality.
But what are the 2012-2015 manufacturing operation trends of all U.S. companies? In the
previous paragraphs we examined only the U.S. companies that are considering re-shoring.
What are expected globalmanufacturing operationshifts in the period 2012-2015?
27
70.0%
US Companies Considering to Reshore:
Distribution of Sales Per Region (2012)
62O%
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
0 Sales
12.0%
4.%6.3%
*.1.9%
.
0
0~R
2.0%
iwii
3.6%
2.8%
2.4%
-
-
l
fq
2.0%
Il
Figure 13. Distribution of Sales per Region for U.S. Companies Considering to Move
Changes in Distribution of Manufacturing Operations
2012-2015
1.5%
1.0%1.0%
.0%
0.0%
-0.5%
"US
0.3%
0.2%
0.5%
0.%
5-0.1%
f
-1.0%
" Canada
E Western
-01%
-0.8%
" China
-1.5%
-2.0%
Europe
" Eastern Europe
" Japan
-1-8
" Other Asia
-2.5%
b
oe
o#
.
sp
.0
.c0
?
" Mexico/Central America
" South America
.
we'
i Middle East/Africa
Figure 14. Changes in the Distribution of Manufacturing Operations 2012-2015
28
Figure 14 (blue indicate gain and red indicate loss) answers that question. U.S. and China, by
proportion, are experiencing a reduction in manufacturing operations at -1.8 percent and -0.8
percent respectively while Mexico and Other Asia Regions are gaining +1.0. We can also
observe the flows from where the changes are coming from. For example, U.S. manufacturing
operations are shifting to Mexico while China operations are shifting primarily to other Asia
regions. China is not gaining but the numbers on U.S. are important. The results are indicative of
a trend. Business analysts may have thought that China would develop its market internally.
That maybe the case but the data are only about U.S. companies strategic decisions. We also see
a low cost to low cost movements (there is a movement from within developing countries) from
China to Vietnam, Malaysia and Myanmar. Note that this is the delta for 3-years differences.
We do not expect a big change in the three years.
When we asked the questions on "what are the leadingindustries that are moving their
manufacturingoperationsback to the US.?" Figure 15 shows that the top industries are:
1. Food and Beverage Products manufacturing (75 percent)
2. Motor Vehicle Products and Parts Manufacturing (60 percent)
3. Electrical Equipment, Appliances and Component Manufacturing (57.1 percent)
4. Aerospace Products and Parts Manufacturing (50 percent)
5. Pharmaceutical and Medicine (42.9 percent)
6. Chemicals (37.5 percent)
Industries Considering Moving Back
710%
rod & no-wrage Prorm Mr(*
Products and Parts Manufacturing
60.0,
E ectrical Eculpmcnt, Applianco anc Componcnt -manufacturing
1%
Motor Vehidce
$
Aerospace Products and Parts Manuftcturkng
aharmaceutcals and Meoicne
.0%
ndstrIos
14 9
7.5%
Chem cals
3-1
OUts Milsuracusing
3/
Computer and Electronic Product -anufacturing
33.3
lndstr al Mac-inery Ma ufacti rins
00%
%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
Figure 15. Industries Considering Moving Back
29
70.0%
800%
What type of Consumer Packaged Goods (CPGs) companies are moving back? Some of them
are pretty big companies that are either planning or moving manufacturing closer to US market
demand.
2.1.3 Hypotheses Testing
Analyzing the data we observe a positive trend from 2012-2015, that a good percentage, +4.5
percent (Figure 12), is considering to move operations back into the U.S. and an even stronger
+6.5 percent from those that are definitively planning to move operations back. Further, as we
mentioned earlier, 31.0 percent of the companies with greater than $1 OB are considering moving
back but only 11.9 percent are definitively planning. This is a big difference! But we cannot
draw conclusions analyzing one side of the story. By referencing Figure 14, the aggregate
empirical results of all companies for the period 2012-2015, indicate -1.8 percent reduction, by
proportion, in moving manufacturing operations back in the U.S. This antithesis in how
company executives are really thinking vs. 2015 sales and operations trends leads to a stipulation
that companies that have invested heavily ashore are considering reshowing in a longer than 3year horizon. We do not have a strong evidence of a positive relation between manufacturing
operations re-shoring to U.S. Therefore we cannot say that there is a strong trend that
manufacturing is definitely moving back to US in the near future. There is a good percentage of
companies that are considering moving back to US, thus creating an opportunity for re-shoring.
In the next section we will analyze the drivers that lead to the decision for re-shoring.
2.2
Drivers and Government Action to Support Re-shoring
2.2.1 Decision Drivers to Consider Re-shoring
We asked the companies if they are consideringmoving manufacturingback to the US then what
the main decision drivers? The answers to this survey question are shown in Figure 16. The
companies identified the following reasons:
1. Time to market (73.7 percent) - this driver motivates a regional manufacturing strategy.
For companies with a customer value proposition such as Zara's "High fashion content at
a reasonable price" then "time-to-market" is the key operations driver.
2. Cost Reductions/Total Landed Cost Calculations (63.9 percent). The total landed costs
includes the total costs of purchasing and delivering the product to its final retail
destination.
30
3. Product Quality (62.2 percent). There have been concerns about product quality from
low - wage labor countries due to low-quality of supplier components made overseas,
longer waiting times, lack of quality specifications and consumer safety issues.
4. More Control (56.8 percent). A number of companies want to have control over
materials, labor costs, intellectual property rights, and technology partners and
component suppliers. For these companies control is an important driver.
5.
Hidden Supply Chain Costs (51.4 percent) - At the beginning when companies moved
manufacturing facilities into Asia it was about labor costs and unit costs. Then, it was
financial incentives provided by the local government. However, hidden logistics,
materials and local contract costs added into the cost equations can increase the total cost
of ownership by a significant number of percentage points.
6. Protect Intellectual Capital (48.6 percent). This is an important driver. For example,
there is anecdotal evidence from U.S. companies with complex supply chain operations
in Far East Asia where IP theft and lax laws is a serious concern.
Note the Hidden Costs of Supply Chain item: what this is telling us is that as we start operating a
global manufacturing strategy, we realized that there are other costs that we did not take into
account when we did the initial analysis to justify the move to Asia. These are the costs of
moving or outsourcing the manufacturing operations to Asia.
31
Considering to Bring Back MFG Decision Drivers Ranking
Time to Market
Cost Reductions/total landed cost calculatiors
Product Quality
-
63.%
~
-.-
More Control
Hidden supply chain costs
Protect IP
Less Risk/volatility
-
I
-
I
-
I
-
I
48.b%
45.7%
Quality Concerrs
Speed of Productions
Ant cipation of US Gov ncentives, Tax Breaks etc.
5.8%
'1.49
I 41.7%
40.0%
18.2%
Brand Perception
Currency Fluctuations/ Margin Erosion
Counterfeiting
Pr essure to iic edse US Jobs
Energy Costs
Public Relations ssues
Other (please specify)
62.2$
E Rank
7.1%
M 33.
30.3%
2! .7%
2! .7%
5.%
0.0%
0.0%
10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0%
80.0%
Figure 16. Decision Drivers to Bring Manufacturing Back
2.2.2 Suggested Government Actions to Incentivize Companies to Re-shore
Realizing that most of the companies may have already heavy infrastructure footprint and large
investments overseas we have asked the companies: What Government actions are requiredto
incentivize companies to move back? Figure 17 shows the top six actions, the U.S. Government
can take to incentivize re-shoring of U.S. Companies:
1.
Tax credit
2. R&D Incentives
3. Corporate tax reductions and
4. Provide Better Education/Training for Required Skills
5. Better Infrastructure
6. Raise Duties / Tariffs
In Figure 17b we are distinguishing between the companies' that are Considering Moving Back.
But the answers are more or less the same.
32
All US Companies: Government Actions
OCrporate Tax Reductions
68.9%
Iax Lredits
BMW
ProvIde R&D IrcentIves
1
Provide Better Educalion/Training for Required k Its
Pruvi~de
R
4n
Setter Irifrastruc te
37.1%
R.ai* Duteft'Trik
32.5
ation
30.4%
Rapid Deprec
%
0.0
1OD%
20M% 300%
400% 50.0%
W0.0%
70.0%
W.0%
All US Companies Considering to Move Back: Government ActionsTa
6.1%
Tax Credits
Provide
ef
R T1WXIi
51.8%
R&DineiIves
Cor ptn dte Tax Reduuiurts
57.1%
Pirjvide Betle Educatiun/Trainig fua Re.urnred Skildk
51.4%
Provide Betet Infrast ucture
42.9%
Raise Duties/ariffs
34.4%
Rapid Depreciation
00D%
294%
10.3%
20.0%
303%
40.0%
50.0%
60.0%
70.0%
Figure 17. Ranked Government Actions to Support Re-shoring
2.2.3 Challenges in Bringing Production Back to US
So, what are the criticaldrivers of where manufacturingis going to be? What are the challenges
of re-shoring? For example, a company may look at what is the impact of tax rate in different
countries. And then, based on this information they decide what their manufacturing footprint is.
Certain companies, e.g., motor vehicle products, may have a large heavy infrastructure in Asia
and it is difficult to move that infrastructure for heavy products back to U.S. But for Consumer
Packaged Goods (CPG) companies the situation may be different. The CPG industry
infrastructure is not as immobile as the motor vehicle and chemicals ones. The incentive to
come back may be a lower tax rate. Figure 18 shows what the companies consider the top
challenges are of bringing production / manufacturing back to the U.S. The top challenges are:
1.
Labor Cost
(84.4 percent)
2. Tax Rate
(75.6 percent)
3. Facilities Costs
(68.5 percent)
4. Supplier availability
(67.1 percent)
5. Environmental Regulations
(65.5 percent)
33
We also performed the same computations for companies are that are considering coming back
and the results are identical. Hence, the U.S. policy makers may consider policies and plans that
will lower tax rates to further incentivize re-shoring.
Challenges of Bringing Production/Assembly
Back To The U.S. (All Companies)
84.6%
LabuL CUsI
Tax Rate
7 .6%
Facilities Costs
68.5
Sipphler availability
7 1%
Environ-nental Reglations
b 5.5%
Labor Rules, Safety anc Other Regulations
'
Labor laws
56,0%
Access to Skilled Labor
535%
Financial reportirg recuirernents
395
Access to Capital
34.6%
-0.0%
7.1%
100%D 20.0% 40.0% 400(%,90,0% 60 0%7ft0% ROoQ.0%qf0
Figure 18. Challenges of Bringing Production Back to U.S.
2.2.4 Supply Chain Strategies Used to Support Re-shoring Decision
We asked the companies that are considering moving production/assemble operations back to
U.S. "What Strategies are they using to support their decision to move back? " What the
companies told us is that their potential re-shoring strategy decision is based on "Total Landed
Costs." This strategy makes sense for products with high forecast accuracy, low supply chain
risk, slow innovation speed and high financial impact. The top three strategies are shown in
Figure 19:
1.
Total Cost to Serve (e.g., Total Landed Costs)
60 percent
2. Improve Supply Chain Flexibility
57 percent
3. Supply Chain Risk Analysis and Mitigation Strategies
56 percent
34
Strategies used to support decision to move
Production/Assembly To The U.S.
II
Total Cost to Serve Modeling (e.g.,total landed
cost)
I
i
I
______
60%
7%
Improve Supply Chain Flexibility
Supply Chain Risk Analysis and Mitigation
Strategies
5
*
Supply Chain Segmentation
Advanced Technology/Business
intelligence,
8%
28 %
etc.
Other (please specify)
13
0%
10%
20%
40%
30%
50%
60%
70%
Figure 19. Strategies Used to Support Decision to Move Back
2.2.5 Current Manufacturing Strategy Used by Companies
In order to obtain information on each company's manufacturing strategies we ask "What
ManufacturingStrategy Are You Using,Regional or Non-Regional?" In a regional strategy,
manufacturing in Asia is for Asia; manufacturing in North America and Latin America is for
North America; and manufacturing in Europe is for Europe). Fifty (50) percent of the companies
told us that they are using regional manufacturing strategy (see Figure 20). This explains the
presence of a large manufacturing footprint in certain regions.
Manufacturing Strategy
Currently~UI a ReinlMnuatrn
Currently Use a Regional Manufacturing
Strategy
77 50.0%
1
3 i.9%
Chose not to Reveal their Strategy
Do Not Use A Regional Manufacturing
Strategy
Actively Planning To Move To a Regional
Manufacturing Strategy
310,
-
Considering To Move To a Regional
Manufacturing Strategy
9.0%
6 0%
0.0%
10.0% 20.1% 30.0% 40.0% 50.0% 60.0%
Figure 20. Current Manufacturing Strategy
35
But what are the primary drivers that caused US companies to adapt a regional manufacturing
strategy and trigger them to move production outside the U.S? The responses are shown in
Figure 21. The key drivers are cost reduction to serve the regional demand (sales) and revenue
growth from emerging markets. For example, U.S companies moved to China and Far East due
to low labor costs and to service the local markets. These insights obtain here also confirm the
insights in Sections 2.4 and 2.5.
Factors for Companies to Move Production Outside the US
I nwpr Costs
53.0%
Move closer to demand
41.0%
lcvcnuc growth is going to comc from outside the US
40.0%
Lack of U.S.-basec raw materials and/or components
19.0%
'rod ittryualwty
16
Speed o, production Cyc e Times
15.0
Foreign expertise
b.0%
Lack of U.S.-based skill sets
Other (please specify)
%
.0%
00%
00%
10.0%
70.0%
30.0%
40.0%
Sn.0%
60.0%
Figure 21. Factors for Companies to Move Production outside of U.S.
2.3
Associations Between Operations, Sales, R&D and Product Development
In this section we are investigating potential correlations between manufacturing, sales,
employee force, R&D and product development locations. By performing correlation analysis
we are looking at relationships between these variables. The question we are asking is: "Is there
a relation between product development and R&D locations?" For example, if the product
development is performed ashore is R&D also located ashore too? Similarly, we are examining
whether there is there a relation between manufacturing and sales locations. To answer these
questions we analyze the correlation graph in Figure 22. We observe only following relations:
1.
A relation between Sales and Employees locations
2. A relation between R&D and Product Development locations
Figure 23 shows that R&D and PD variables are highly correlated with an R2 value of 0.832. It
shows that R&D and PD locations are dependent. A change in PD location will cause a change
in the R&D location. This is an association that needs to be kept in mind. For example, if
product development moves ashore it will cause R&D to also move ashore. What it means is
36
that re-shoring product development is not only about recovering the lost US jobs. It is also
about r-'hnrino R kT
A -imi1nr denndiner
Most C.-
PYitQ hetween qnle mnd
-
emninios Inontinnq
-
y
Fi,
Figure 22. Matrix Correlation Graph
37
R&D vs PD
Employees vs Sales
120
120
100
y
0.05x+ 3.871
R 2 0.832
100
0
so
80
60
60
40
40
20
20
0
0
20
40
0
80
60
100
120
0
20
40
Ops vs Sales
60
+
80
100
120
Ops vs R&D
120
120
4
100
-
--
-
-
-
1OD
-+4
-
S04572
.
80
604
4
4
40
20
2
0
20
40
60
80
100
120
0
20
40
60
so
100
120
Figure 23. Linear Relations and R2 values for the variables
2.4
Summary
Our survey study shows that a significant proportion (33.6 %) of the U.S. companies state that
they are "considering" moving manufacturing operations back to U.S. The study also shows that
15.3% of the U.S. companies are "definite" planning to move back. The data also show that
there is a change from a global manufacturing strategy, where the focus is on low labor cost, to a
more regional strategy, where U.S. and Mexico is for the North America markets and Europe is
for European markets. These changes indicate the start of a regional strategy trend over the last
few years. We used the survey data to identify what drives this trend and whether this trend has
made an impact. The companies have cited the following reasons for the re-shoring:
1.
Time-to-market - For companies that have a value proposition that is focused on time-to
market then their integrated supply chain is dedicated on responsiveness. For these
companies their operations strategy is focusing on speed and a regional strategy can serve
that purpose.
2. Product Quality - there are multiple reports of product quality issues as a result of
outsourcing. U.S. companies received cheaper quotes from China so they contacted a
factory to launch their product there. Very soon these companies realized that the inferior
38
quality of the products triggered a need for better control of product quality. A number
of companies fed up of having low quality products made in China are considering
moving production back home.
3. Cost Reduction / Total Landed Costs - Over the years the labor costs in China have
increased significantly in comparison to U.S. and Mexico labor costs. Hence, production
sourcing decisions may need to be revisited based on the future wages and labor costs.
4. More control over raw materials -Control and distribution of raw materials is essential
for production. Raw material scarcity can adversely affect operating conditions. Hence,
strategies on how to gain access from overseas to raw materials sources and, lead-times
required to obtain sufficient quantities is another decision area to be revisited.
5. Hidden Supply Chain Costs - When moved ashore, a number of companies did not take
into consideration hidden logistics, materials and local contract costs added into the cost
equations. It generated an increase to the total cost of ownership by a significant
percentage points causing companies to re-think their past re-shoring decision.
6. Energy costs - Energy costs have increased over the years impacting logistics and
transportation costs. The projected energy boom from new technologies to extract shale
oil can cause a reduction in future energy costs thus further motivate re-shoring.
The survey responders also indicated what actions the policy makers can take to incentivize
companies to move back. The objectives of these incentives are to change business behavior and
motivate to re-shore their business. The top three suggested actions for policy makers to support
the re-shoring decisions are to provide:
1.
Tax Credits
2. R&D Incentives
3.
Corporate Tax Reductions
4. Better Education/Training for Required Skills
The companies will use a number of strategies to support their decision to move production and
assembly back to the U.S. The strategies are:
1.
Total Landed Costs - Most of the companies told us that their potential re-shoring
decision is based on this strategy. This strategy makes sense for products with high
39
forecast accuracy, low supply chain risk, slow innovation speed and high financial
impact.
2. Improve Supply Chain Flexibility - Ensuring that goods are always available requires
that companies build flexibility into their supply chain so they can respond to change in
supply and demand as it arises. This drives companies to re-assess the global
manufacturing strategies in order to reduce risk.
3. Supply Chain Risk Analysis and Mitigation Strategies - Global companies have realized
the outsourcing and offshoring have increased risk as the supply chain partner / supplier
base have become more complex. This drives companies to rethink their network
relations in order to reduce risk and improve their business performance.
4. Advanced Technology - Faster computing, robotics and new sensor technology improves
productivity and reduces the importance of low labor costs. The latest applications of
software technologies allow faster and reliable information sharing across multiple
suppliers/partners enabling upstream and downstream data visibility.
These insightful findings show that the re-shoring trend is picking up speed. It shows that an
attractive opportunity exists for policy makers and U.S. companies to help accelerate this trend
and contribute to the U.S. manufacturing growth.
40
3. An Empirical Analysis of Supply Chain and Risk Management
3.1
Introduction
3.1.1 Background
In the mid 70's and early 80's most of the companies were basing their operations and sales in
US or Western Europe to serve home and neighboring countries. Uncertainty and risk, due to
disruption incidences, were present but not in the same scale as it exists today. The company
usually provided a stable environment but success on risk management was mostly attributed to
the competence and heroics of the staff within the company and not in the use of established and
mature risk mitigation processes.
In the 80s the companies established new supply chain and manufacturing technologies strategies
that allowed them to reduce costs, increase time to market and better compete beyond the nearby
geographical boundaries. In the 80's companies start learning how to manage risk and
uncertainty within local geographical boundaries. Risk reduction was facilitated by the fact that
most of the partners/suppliers were within regional boundaries. At that time companies were
considering how to strategically position their inventory, start controlling their capacity, and
establish a level of visibility within the supply chain. The work products and services satisfied
their specified requirements, standards, and company objectives. Uncertainty and risk were
measured and contained but not effectively mitigated yet. Robust strategies for mitigating
supply chain disruptions [6] have been mentioned in the literature, but there was a still
unnecessary cost due to either redundant stock piles or inefficient transportation and logistics
strategies. Executive were making decisions considering only the benefits or impacts around
their own company.
In the late 1990s and 2000, companies start expanding their business on the global market. Web
1.0 and 2.x Internet technologies and e-business models (e.g., eBay) involved business processes
spanning the entire value chain. Order processing, products and services were coming or
delivered from all over the world. Rising labor costs at home forced manufacturing to be
outsourced in Asia. Now, the logistics supply chain had become increasingly complex.
Uncertainty and risk has increased significantly. Companies that did well in that period were
well-integrated internally, performed proactive risk management, had product and process
standards and had established business continuity plans. Business models were flexible,
41
allowing the company to adapt easier to changes. The supply chain costs were acceptable but
not optimized across all links in the supply chain; new global enterprise supply chain
optimization concepts start emerging.
Today, we have a highly competitive global operations and sales environment. Product life
cycles have become shorter, time-to-market and technology speeds have become faster, cost
reductions are always sought and demands for higher product quality have increased. Global
trade introduced new market uncertainties and new types of risks [7]. Now, companies need new
business models and agile adaptation to changes. The must invest and use sophisticated
techniques and business models to address changing markets environments while maintaining
continuity of operations.
3.1.2 The Values of Mature Risk Management and Operational Resiliency
On March 11, 20111, Nissan Motor Company Ltd and its suppliers experienced a 9.0-magnitide
earthquake as it struck-of the coast of Japan. The quake was among the 5 most powerful
earthquakes on record. Tsunami waves in excess of 40 meters traveled up to 10km inland
causing a Level 7 meltdown at 3 nuclear reactors at Fukushima Daiichi. The impact of this
combined disaster was devastating with 25,000 people dead, missing or injured, 125,000
buildings damages and an estimated economic damage of $200B.
In the weeks following the devastating March 2011 earthquake in Japan, 80 percent of the
automotive plants in the country suspended production. Nissan's production capacity was
perceived to be the most impacted by the disaster when compared to its competitors Toyota and
Honda: six production facilities and fifty of the firm's critical suppliers suffered severe damage
resulting in a loss of production capacity equivalent to approximately 270,000 automobiles.
Despite this devastation, Nissan's recovery was remarkable. During the next six months, Nissan
production in Japan decreased by 3.8 compared to an industry wide total of 24.8 percent. Nissan
ended 2011 with an increase in production of 9.3 percent compared to a reduction of 9.3 percent
industry wide.
How was Nissan able to successfully manage a disruption of this magnitude?
Case Study: Nissan Motor Company Ltd: Building Operational Resiliency: William Schmidt, David Simchi-Levi,
MIT Sloan Management: Aug 2012
42
Nissan responded to the disaster by adhering to the principles of its risk management philosophy.
It focused on identifying risks as early as possible, actively analyzing these risks, planning
countermeasures and rapidly implementing them. Nissan had prepared a continuous readiness
plan spread among its suppliers: an earthquake emergency response plan, a business continuity
plan and disaster simulation training. Nissan deployed these advanced capabilities both along
the supply chain as well as the risk management dimension. First, management was empowered
to make decisions in the field without lengthy analysis. The flexibility of its supply chain model
structure - decentralization coupled with strong central control when required - was combined
with simplified product lines. There was visibility across the extended enterprise and good
coordination between internal and external business functions. These supply chain capabilities
allowed the company to share information globally, to allocate component part supplies on
higher margin products and to adjust production in a cost-efficient way.
3.1.3 The Need for the Study
The Nissan story is at the heart of this study. Without question, it illustrates that companies,
such as Nissan, with highly mature capabilities along the two dimensions - supply chain
management and risk management -will be able to effectively address risks, outperform the
competition and even gain a competitive advantage.
Having the capability to connect the customer value proposition, sound supply chain operations
and risk management strategy with principles,frameworksand processes allow companies to
address most of today's and tomorrow's business challenges. The MIT Forum for Supply Chain
Innovation and PwC launched a Supply Chain Risk Maturity Survey for Global Organizations in
order to assess these challenges and their impact on business operations.
The survey was distributed to members of the MIT Forum for Supply Chain Innovation and
world-wide customers of PWC. In total, 209 companies have completed the survey, providing
their input to this report.
3.1.4 Today's Challenges
When a company expands from the regional scene to a global one, it is cause for change in the
operations strategy. Suddenly, transportation and logistics become a challenge; lead times are
longer, costs have increased and end-customer services are impacted. For example, the
economic debt crisis in Europe lowers expectations for future demand for products in the
43
continent, causing companies to change strategies and to seek alternate global markets to sell
their products and maintain their ability to compete. A research report into global supply chains
[8] identifies many operations strategies, e.g., flexible-response, but it is unclear which one is
more resilient to disruptions.
Now that companies have established a global footprint, similar products have dissimilar
customers and different distribution channels, which require different supply chains. The first
challenge to address is "What are the supply chain complexity driversfor a company with global
operations?"and, "What are the sources of risk?" The second challenge poses the questions
"How can vulnerability and exposure to high impact supply chain disruptions be properly
assessedand managed?" and "How can supply chain resiliencebe improved?" The third
challenge arises as the executives strive for a better understanding of "What supply chain
operationsand riskprinciples will guide the improvement of the company's bottom line: the
operationsandfinancialperformance?"
44
4. Supply Chain and Risk Management: Survey Demographics
4.1
Survey Data Summary
In total, 209 companies participated and completed the survey of which 65% were manufacturing
companies and 35% were non-manufacturing companies. From the 209 companies, 181 of them
fully completed all 39 questions. Most of the responses (53%) were originated from companies
headquarter in Western Europe, followed by United States (19.1%), Mexico/Central America
(11.5%) and Japan (6.2%), see Figure 24. By continent, most of the responses (53.1%) came
from Europe, followed by North America (30.6%) and Asia (11%). Since most of our survey
data responses came from Western European companies, our results are biased towards
European views rather than representing a uniform cross-sectional views across North America,
Europe and Asia.
Company HQ by Region
60.0%
S1.7%
50.0%
40.0%~-30.0%
191%
20.0%
10.0%
11.5%
0.5%
0.5%
1.4%
2.4%
1.9%
4%
Figure 24. Distribution of Companies by Region
Participating companies came from all spectrum of industries including Pharmaceuticals and
Medicines (9%), Food and Beverage Product Manufacturing, (9%), Retail Trade (8%),
Chemicals (7%), Computer and Electronics Product Manufacturing (6%), Transportation and
Warehousing (9%) and Industrial Machinery Manufacturing (6%), Healthcare and Social
Assistance (3%) and Electrical Equipment Manufacturing (6%), as illustrated in Figure 25.
There is an almost even distribution of industry participants making the industry distribution in
our survey uniform.
45
Count
1o
Petroleum and Coal Products
Accommodation and Food
Services
itt
Agriculture,
Miningand
%,
uction
Aerospace C
achinery
and
Wood, Paper, Printing
2%
Industry Participation
Apparel and Textile
a Aerospace and Defense
Telecommunications
mAgriculture, Mining and Construction Machinery
a Apparel and Textile
1%%
o Chemicals
* Computer and Electronic Product manufacturing
Public Administration
0%
a Construction
onic Product
a
ction
a
Professional, Scien\ca
,
Electrical Equipment, Appliance and Component Manufacturing
N Food & Beverage Product MFG
* Foundries, Forgings, Other Metal Products
* Glass, Cement and Concrete Products
a Healthcare and Social Assistance
Primary Metal Manu
0%
* Industrial Machinery Manufacturing
-
a Information
a Mining, Quarrying, and O0 and Gas Extraction
v Motor Vehide Products and Parts Manufacturing
a Newspapers, Books, Motion Pictures,
a Other Manufacturing
Television & Cable Broadcasting
i Pharmaceuticals and Medicine
ries, Forgings, Other Metal ProdPmary Metal Manufacturing
w Professional, Scientific and Television Services
Public Administration
Glass, Cement and Concrete Products
2%
P Retail Trade
---. Healthcare and Social Assistance
.Telecommunications
3%
Transportation and Warehousing
Newspapers, Books, Motion Pictures,
Television & Cable Broadcasting
2%
Motor Vehicle Products and PartsManufacturing
3%
Mining Quarrying, and Oil and Gas
Extraction
1%
-
_In
ormation
2%
Figure 25. Distribution of Company Participants by Industry
Figure 26 depicts the distribution of all participating companies by yearly revenue size. Of the
210 companies, 47.8 percent have revenue less than $500M USD, 12.9 percent have revenues
between $500 and $1B, 23.4 percent have revenues between $1B and $1OB USD, 7.2 percent
have revenues between $1 OB and $15B and, 8.6 percent have annual revenue sales greater than
$25B. Finally, the proportion of companies with revenue sales greater than $1B is 40 percent.
I
--
Size of Companies Based on Sales Revenue
-
60.0%
50.0%
47.8%
400/o
30.0%
23.4%
20.00%
12.9%
8.6%
7.2%
10.00/0
0.0%
0 - $500M USD $500M - $1B
$IB - $IOB
$10B - $25B
USD
USD
USD
Greater than
$25B USD
Figure 26. Size of Companies Based on Sales Revenue
46
1
The demographic data will support our research initiative to segment the responses within
categories, identify the risk factors and examine how risk maturity behaviors vary among
industry or sales revenue size subgroups.
One of the key questions is that given the geographic location of the company's headquarters
what percentage of their operations, in terms of volume, and sales are done in all global regions?
The results reveal an important insight: A large number of US and Western European
Headquarter companies have outsourced their operations in China (see Figure 27). However,
while 10.1 percent of their operations are done in China only 4.5 percent of sales (by proportion)
is done in China. We see this model increasingly in similar low-cost manufacturing labor and
emerging market countries. A similar model is observed with Mexico / Central America.
However in our survey, Mexico has a lot of companies headquartered in that region. The insight
here is that Mexico is progressively becoming a regional operations and sales center. On the
other hand, for the US we observe that sales exceed operations by proportions). U.S. and Europe
are considered prime consumer markets.
368%
35.0%
Sales vs Operations for the
Manufacturing Industry
30.0%
25,0%
1 r-7)4
3%qI
15.0%
100%
68%5.8%
5.7%
4.5%
56A%
58.6%
50%
42
38yo
5%
3.3
2.1%
4.3j
%
2.7
0.4%0
MlOPS OSALES
Figure 27. 2012 Sales vs Operations for the Manufacturing Industry
4.2
Globalization of the Supply Chain
From the survey, (see Figure 28), we also obtain another key insight that gives an opportunity to
think about today's global supply chain scale of manufacturing operations. Only 16% of the
companies surveyed had 100 percent of their manufacturing operations in one location. The
remaining, 84% percent, have their operations dispersed in more than 3 locations spanning
47
across multiple regions. Thus, supply chain risks due to global scale of product flow from
manufacturer to distributor to retailer and finally to customer has grown in complexity [9].
Many companies are outsourcing their product development and manufacturing in low-wage
labor markets, such as China and India. This is great from a company's savings perspective, but
has increased the complexity of the supply chain. It has introduced a number of operational
inefficiencies such as: increased lead times, increased inventory levels (to maintain lead times) or
lower service levels. It has also introduced risks due economic instability in these regions, such
as, currency fluctuations, labor unrests or even risk due to natural disasters.
900%
Ragional vs Global
Manufacturing Presense
80.0%
70.0%
60.0%
50.0%
40.0%
30.0%
16.8%
20.0%
10.0%
0.0%
%of Companies with operations
across regions
%of Companies with 100%
operations in one region
Figure 28. Percent of companies with global manufacturing presence
4.3
Sources of Supply Chain Risk
Global supply chains are exposed to many risks from multiple sources. Those risks are
associated with known-unknowns and controllable, to unknown-unknowns and uncontrollable
ones [10]. For example, in the Nissan Case, the devastating natural disasters were unknownunknowns (difficult to quantify the likelihood of occurrence) and uncontrollable (you cannot
manage the expected risk and its impact).
Our scope definition of risk covers the wide area between devastating supply chain disruptions
caused by natural catastrophes to rapid or slow structural market shifts to which the value chain
needs to adapt due to changes in the business, socioeconomic, geopolitical or technological
environment. To uncover the level of exposure to such diverse sources of risk we asked survey
participants to present their view with respect to which incidents can potentially have the biggest
impact on their supply chain. Figure 29 shows the top six risks: raw material price fluctuation
48
(53%), currency fluctuations (47%), market changes (41%), energy /fuel prices volatility (38%)
environmental catastrophes (31%) and raw materials scarcity (28%).
All these risks with the exception of environmental catastrophes are known-unknowns and
controllable to some degree. A number of these risks have a high likelihood that will materialize,
e.g., market changes, while others, like the recent April 2013 American Airlines 24-hour
unplanned computer outage, have low likelihood that will materialize. For selected types of risks
we can be better prepared for, such as energy / fuel prices changes. But there are some risks that
we cannot anticipate, such as natural disasters / environmental catastrophes that have low
likelihood but a great impact. Not all risks have the same likelihood of materializing.
Exposure to Supply Chain Risks
53.1%
Raw material price fluctuation
4 .9%
Currency fluctuations
41.1%
Market charges
38.3%
Energy /fuel prices volatifity
34.0%
Natural disasters / environmental catastrophes
Raw material scarcity
7.8%
26 35A
Rising labor costs
Geopolitical nstability
22.5%
Supplier/ Partner bankruptcy
22.5%
20.15A
Change in technology
12.4%
Unplanned IT disruptions (e.g., outage or downtime)
Counterfeit'ng
10.5%
Other
517
Telecommunications outages
5.3
Cyber attacks
0.0%
2.4%
10.0%
20.0%
30.0%
40.0%
SO.0%
60.0%
Figure 29. Supply Chain Risks that a company is most exposed to
We have asked our survey participants to grade the likelihood that these disruptions will
materialize. Their responses are shown in Figure 30. The participants are telling us that the risks
with highest likelihood to be materialized are: raw materials price fluctuations (34.9%), currency
fluctuations (27.8%), energy/fuel volatility (24.4%) market changes (23.9%), rising labor costs
(15.8%) and raw materials scarcity (13.9%).
49
Similarly, the survey participants ranked what they considered the low likelihood risks: 58% of
the participants told us that natural disasters / environmental catastrophes is low likelihood,
geopolitical instability (53.9%), telecommunications outages (49%), unplanned IT disruptions
(43.5%), and cyber-attacks (43%).
High Uikelihood That These Risks Will Materiaze
Raw
mnaterial
prie fluctuation
Low Ukelihood That These Risks Will Materiaze
Energy / fuel prices volatiity
Rising labor costs
Raw material scarcity
Change In technnlogy
Naturaldisasters /environrmental catastrophes
Unplanned iTdisruptions (e.g. outage, downtime}
Supplier / Partner bankruptcy
Counterfeiting
278%
23.9%
'24.4
15.8%
,
W
5.4%
Naturaldisasters/enironmentalcatstrophes
Geopoliticalinstability
Tekwnurnkiat is ouIt1gs
Unplanned If disruptions (e.g. outage, downt ime)
Cyber attacks
Supplier / Partner bankruptcy
349%
Currency fluctuations
Market changes
1 9%
195%
53.9%
483%
43.5%
4419%
438%
Counterfeiting
'
67%
O
5.3%
t
43%
$
3W3%
Geopulhitlitistability M
3.3%
Other M 2.4%
(yber attacks 01.9%
Telecommunications outages m 1 9
3.7%
Change intechnology
Raw material scarcity
Rising labor costs
[nergy /fuel prices volatiity
Market changes
Currencyloctuatios
Raw materlA price fluctuation
Other
0.0% 5.0% 100% 15.0% 20.0% 25,0% 30.0% 350% 400%
325%
28 6%
24.7%
20.8%
19.5%
16.Z%
110%
10.4%
00%
100% 20.0% 30.0% 40.0% 500% 600%
70.0%
Figure 30. High and Low likelihood that these risk will materialize
4.4
Measuring Risk
These risks have an Expected Impact when they materialize. The Expected Impact, Efx disruption],
is measured as the product of (a) the risk likelihood, Pr(x disruption), that this event will be
materialized, times (b) the direct consequence (effect) on business operations (e.g., on lead
times) or financial performance (e.g., revenue) values given that the risk event is realized. In
mathematical terms:
Efx
disruptionl =
Pr(x disruption) *
Value
(1)
For example, the probability of occurrence of a 7.0 Richter scale earthquake event (x disruption) is
low but the consequences are high which drives the expected impact value to be high.
Using the concept from equation (1), the complementary question to "High or Low Likelihood
Risk" is "which supply chain risks have the highest potentialconsequence (or effect) on your
company's operation orfinancialperformance?"Figure 31 shows what our survey participants
told us are the top five supply chain risks with high potential impact are: raw material price
fluctuation (41%), market changes (30.6%), currency fluctuations (29%), raw material scarcity
(27%), and energy/ fuel prices volatility (24%). Similarly the ones with low potential impact are:
50
cyber-attacks (33.5%), telecommunications outages (30%), Counterfeiting (28%), unplanned IT
disruptions (26%), supplier / partner bankruptcy (25%) and geopolitical instability (25%).
Risks with Low Potential Impact on Performance
Risks with High Potential Impact on Performance
30.
Market duanfes
Curreny lucaaIm
Raw rnaterial stardty
En2ergy4fuel ikeavastily
Natur
a~l
ds
te's endrlrierta:
4.7%
16.3%
-6
Uprvanced
244%
2dA%
(aUtar4"i
technology
1? %
163%
RAiin labmn ro-t
IrpcnnedIT
NippIer i Partner bankruptcy
6eopoliticalinftaaity
I srupfii (P g , rtage %, cmntine)
naikat Ows utafg4
5~bne *ttdui
,rtert2A
s. doMstile)
Ufoer Partner bankr7ip6 V
Gecpfita instabifly
NOaNrOliusseWs/enirem
Ereray /fael
90%
P
"DW
S.0% 100% 151 13.0%2S"
25.8%
2%0%
225%
It9.IE
ten
Cat09kC1
prrwrlatirty
12%
16&3
15,3%
1
Varke, cAngc
material prke fluctuaticn
7.%
O eaw
/10
A9
110%
o.3%AD% 450%
!X0%
4
11.5%
Other
2.9%
Ot~her
25.8%
25.A%
A sing larm coes
aln
(OeDn
lw atinrilshai utIV
139%
10.0%
Counterfeiting
Terwk
11
i dirmuptrs Jeg "a
(lnge
(ha%
Changr in
335%
Cybet attacks
is WasUtA
i i%
R.wmatetialprkefuctuation
50% 10.0% 15.0% 20.(% 250% 3011% 35.09 403%
Figure 31. Risks with High and Low potential impact on performance
4.5
What Parameters are Companies Most Sensitive To
The next question is "What are the parameters that a company's supply chain operations are
most sensitive to?" Figure 32 addresses the question and shows that the supply chain operations
are most sensitive to: skill set and expertise (31%), price of commodities (29%), energy and oil
(28%) among others. These parameters affect supply chain operations (skill set), transportation
(energy and oil) and IT service as a commodity. For example, according to the Department of
Energy Information Administration U.S. diesel prices rose 9.5 cents per gallon in February 2012.
Shippers are cognizant of the sensitivity and impact diesel prices can have on their financial
bottom line and, adjust their budgets in order to offset the increased costs higher fuel prices
produce.
51
High Sensitivity Variables
Reliance on skill-sets and expertise
31.19%
Controlled price of commodities
29.2%
Reliance on energy /oil
28.2%
Regional concentration of manufacturing operations
26.8%
Regional concentration of supply base
24.9%
Reliance on a small supply base
22
Regional concentration of customers
21.5%
Reliance on unique technology
16.7 X
Reliance on a small outsourcing base (e.g., transportation...
15.8%
Reliance on favorable exchange rates
14.8%
1
Reliance on external assets and resources
0.0%
5.0%
10.0%
.9%
15.0%
20.0%
25.0%
30.0%
35.0%
Figure 32. Parameters that a company's supply chain operations are most sensitive to
4.6
What Companies Do to Address Risks
Figure 31 and Figure 32 are tightly coupled as they represent the factors that have direct effect
on the right hand side of (1). Putting both high likelihood and high potential impact events
together create a powerful outcome. This outcome is derived from equation (1): for example, IF
a company has designated raw materials as a critical strategic importance item, THEN without a
risk protection plan the expected impact of raw materials price fluctuation on performance is
high. The reason for this is that raw materials prices rank high on both the High Likelihood and
High Potential impact choices. The insight here is a risk mature company will prepare risk
protection plans on critical items.
Given these risks one of our objectives is to understand what the companies do in the face of the
expected risk impact on their business performance. The fundamental question is: "Given these
risk disruptionsand their dimensionalcharacteristicswhat strategic management decisions and
actions these companies consider to address them?" Failure to prepare and act accordingly may
cause loss of revenue and potentially significant loss of market share. Rapid recovery with
minimal impact on sales revenue and market share speaks about a mature risk company with
52
good resilience characteristics. Figure 33 addresses what the companies are telling us about their
strategies on how they manage supply chain risk disruption. The top 6 strategies are:
1.
Use both regional and global strategy (72.5%)
2. Implement dual sourcing (70.7%)
3. Create and implement a business continuity plan (70.5%)
4. Pursue a I't and 2 "dtier supplier collaboration (61.2%)
5. Apply forward buying / hedging strategy (57.1%)
6. Increase inventory levels and safety stock (55.7%)
For example, in the Nissan's case, Nissan had in place a well-thought out and exercised business
continuity plan ready to kick into place to facilitate a quick recovery. The responses and their
ranking make sense and, there are no surprises. We notice that the top three choices are ranked
very close. One can consider these are the top-strategies to address supply chain risk. Important
information is also revealed through this analysis. A number of companies are in the process of
establishing a risk mitigation strategy right now. These companies are very vulnerable to
disruptions and potentially "carry" high risk exposure potential.
Actions to Address Risks in the Supply Chain
*72.5%
Use both regional and global strategy
70.7%
Create and implement a business continuity plan
M05%
Implement dual sourcing strategy
Pursue (1st and 2nd tier) supplier collaboration (e.g, share experience, track performance)
61,2%
Applyforward buying/hedging strategy
57.1%
55.7%
increase inventory levels and safety stock
Establish distribution centers in multiple regions
53.0%
Pursue demand collaboration with your customers (e.g., share forecasts)
523%
46;4%
Pursue near-shoring manufacturing strategy (closer to the market demand)
42.6%
Use component substitution strategy
Use regional strategy only (e.g., Asia for Asia, Europe for Europe)
39 1%
8.3%
Use postponement or delayed differentiation strategy
other actions (please specify below)
24.2
0.0%
10.0%
20.0%
30.0%
40.0%
inAction is Established
Figure 33. Company Actions to address supply chain risks
53
50.0%
60.0%
70.C%
$0.0%
5. Supply Chain Risk: Capability Maturity Framework
5.1
Levels of Maturity along Two Dimensions
As illustrated in the Nissan case, to succeed in a complex, dynamic and fast-changing
environment companies need to deploy advanced capabilities along two sets of dimensions:
supply chain management and risk management. We developed an empirical framework that
applies set questions across seven supply chains/ risk management enablers to characterize the
maturity level of the supply chain processes and to characterize the maturity level of risk
management processes. The supply chain / risk management maturity model is used to match
each company to their appropriate maturity level based on their responses to questions.
5.2
The Seven Supply Chain Risk Enablers of Maturity
We selected seven supply chain / risk management enablers to provide the underlying foundation
to designate the maturity levels. For each of the seven enabling areas, we asked participating
companies to answer a set of questions concerning the practices they apply in the area. The
extent to which the companies have implemented these gradually advancing practices allows us
to assess which depth each enabler has been put in place. Scrutinizing this information for each
one of the enabling areas we derived the overall maturity level of the company. Companies that
have developed these enabling areas in sufficient depth are regarded within our framework to be
equipped with advanced capabilities. The seven supply chain / risk management enablers are:
1.
Risk Governance - involves the presence of appropriate risk management structures,
processes and culture.
2. Flexibility andRedundancy in Product,Network and ProcessArchitectures - involves
the ability to position the right levels of flexibility and redundancy across the value chain
in order to absorb disruptions and adapt to change.
3. Alignment between partnersin the supply chain - involves the strategic alignment on key
value dimensions, the identification of emerging patterns and the advancement towards
higher value propositions.
4. Upstream and downstream supply chain integration- involves information sharing,
visibility and collaboration with upstream and downstream supply chain partners.
54
5. Alignment between internalbusinessfunctions - involves the alignment and the
integration of activities between company value chain functions on a strategic, tactical
and operational level.
6. Complexity Management / Rationalization- involves the ability to standardize and
simplify networks and processes, interfaces, product architectures and product portfolios
and operating models.
7. Data, Models andAnalytics - involves the development and use of intelligence and
analytical capabilities to support supply chain and risk management functions.
The study reveals which one of these enablers companies consider the most important for
providing key capabilities to deal with supply chain disruptions. Figure 34, indicates companies
are considering alignment between partners in the supply chain as the highest risk reduction
enabler factor (60%). Internal and external process integration is also very important as
companies indicate that by considering both integration between internal business functions
(49%) and upstream and downstream process integration (47%). Risk Governance (44%) and,
network flexibility and redundancy (37%) are also being included in the mix. Interesting to note
data and analytics (28%) and complexity management (26%) are very low on the priority list.
Top-4 Important Risk Reduction Enablers
60%
Alignment between Partners in the Supply Chain
49%
Integration between Internal Business Functions
Upstream and Downstream Process Integration
and Information Sharing
44o
Risk Govemance
Flexibility and Redundancy in Network and
Product Architectures
7%
8%
Data, Models and Analytics
26%
Complexity Management
0%
10%
20%
30%
40%
50%
Figure 34. The 7 Supply Chain and Risk Reductions Enablers
55
60%
70%
5.3
The Four Levels of Maturity in Supply Chain Risk
The two dimensions, supply chain operations and risk management processes, go hand-in-hand
and complement one another. At lower maturity levels the processes are decoupled and
standalone but at high maturity levels they are fully intertwined. For developing and deploying
capabilities to manage supply chain risk effectively a high level of supply chain sophistication is
an absolute pre-requisite. There are four levels of supply chain and risk management processes
used to classify the maturity level of the participating companies:
Level I: Functionalsupply chain management and ad-hoc management of risk. Supply chains at
Maturity Level I are organized functionally with a very low degree of integration. They are
characterized by high duplication of activities, internally and externally disconnected processes
and absence of coordinated efforts with suppliers and partners. Product design is performed
independently and there is lack of visibility into partners/suppliers operations. The supply chain
is characterized by unbalanced inventory and capacity levels, expediting, poor customer service
and high total costs. There is no risk governance structure and poor visibility into sources of
supply chain risk. Only very limited vulnerability or threat analysis is performed. Risk is
managed in an ad-hoc way with no prior anticipation or positioning of response mechanisms.
Level II: Internal supplv chain integrationandpositioning ofplanned buffers to absorb
disruptions. Supply chains at MaturityLevel II are cross-functionally organized. Internal
processes are integrated, information is shared and visibility is provided between functions in a
structured way. Resources are jointly managed and there is a higher level of alignment between
performance objectives. Integrated planning is performed at strategic, tactical and operational
level - that leads to a one company plan. Risk management processes are documented and
internally integrated. Basic threats and vulnerabilities are analyzed. Scenarios concerning the
base integrated plan are conducted to position targeted buffers of capacity and inventory to
absorb disruptions. Postponement or delayed differentiation product design principles are
explored to improve response to changing demand patterns. There is minimum visibility,
however, into emerging changes and patterns outside the company domain.
Level III: Externalsupply chain collaborationand proactive risk response. Supply chains at
Maturity Level III feature collaboration across the extended enterprise. Information sharing is
extensive and visibility is high. Key activities such as product design or inventory management
56
are integrated between supply chain partners. External input is incorporated into internal
planning activities. Interfaces are standardized and products and processes are rationalized to
reduce complexity. Information sharing and visibility outside the company domain is exploited
to set up sensors and predictors of change and variability to proactively position response
mechanisms. Formal quantitative methodologies for risk management are introduced and
sensitivity analysis is conducted. Suppliers and partners are monitored for resilience levels and
business continuity plans are created.
Level IV: Dynamic supply chain adaptationand fully flexible response to risk. Companies in
Maturity Level IV are fully aligned with their supply chain partners on the key value dimensions
across the extended enterprise. Their individual strategies and operations are guided by common
objectives and fitness schemas. Their supply chain is fully flexible to interact and adapt to
complex dynamic environments. Emerging value chain patterns resulting from this interaction
are probed and identified and higher value equilibrium points are achieved. At this level, the
supply chain is often segmented to match multiple customer value propositions. Risk sensors
and predictors are supported by real-time monitoring and analytics. Risk governance is formal
but flexible. Full flexibility in the supply chain product, network and process architecture and
short supply chain transformation lead-times allow quick response and adaptability. Supplier
segmentation is performed. Risk strategies are segmented based on supplier profiles and marketproduct combination characteristics.
A company has mature capabilities or processes if the maturity level of supply chain business
processes and risk management processes is at least Level III. Similarly, a company has
immature processes if the maturity level of supply chain management and risk management
processes is at most Level II. A Best-In-Class (BIC) company has a Level IV maturity
classification. Figure 35 below summarizes the criteria along the two process management
dimensions used to classify the maturity level of each company. Appendix A defines the
operational and financial key performance parameter and Appendix B has a detailed description
of the Capability Maturity Classification Model. The content within each Capability Level box
represents a lower level decomposition of the questions for each of the seven risk reduction
enablers.
57
Figure 35. The Supply Chain and Risk Management Capability Maturity Model
5.4
Hypotheses and Survey Testing
In this section we state the hypotheses and then we test it through empirical observations. Seven
hypotheses statements are prepared and tested. The hypotheses are listed below:
Hypothesis #1: A Significant (majority) of the Companies Have Immature Supply Chain and
Risk Management Processes in Place
HO: All Companies have similaroperations and risk managementprocesses in place
HA: A significantmajority of the companies have immature supply chain operations and
risk managementprocesses in place
Hypothesis #2: Companies with mature capabilities in supply chain and risk management do
better along all dimensions of operational and financial performance
HO: Mature risk processes have no significant effect business operationsandfinancial
performance compared to companies with immature riskprocesses
58
Mature riskprocesses have significant effect on business operationsandfinancial
performance
HA:
Hypothesis #3: Supply Chain Disruptions Have Significant Impact on a Company's Business and
Financial Performance
Ho: Supply Chain DisruptionsHave no Significant Effect on a Company's Business and
FinancialPerformance
Supply Chain DisruptionsHave a Significant Effect on a Company 's Business and
FinancialPerformance
HA:
Hypothesis #4: Companies with Mature Supply Chain and Risk Management Processes Are
More Resilient to Risk Disruptions than Companies with Immature Risk Management Processes
HO: Mature Risk Management Processes Have No SignificantEffect on a Company 's
Business and FinancialPerformance
Mature Risk Management ProcessesHave a Sign'ficant Effect on a Company 's
Business and FinancialPerformance
HA:
Hypothesis #5: Mature Companies Investing In Supply Chain Flexibility Are More Resilient To
Disruption than Those That Do Not Invest In Supply Chain Flexibility
Ho: Mature Supply Chain Flexibility Processes Have no Significant Effect on a Company's
Business and FinancialPerformance
Mature Supply Chain Flexibility Processes Have a Significant Effect on a Company's
Business and FinancialPerformance
HA:
Hypothesis #6: Mature Companies Investing in Risk Segmentation Are More Resilient To
Disruptions than Those That Are Not Investing In Risk Segmentation
Ho: Risk Segmentation Has no Significant Effect on a Company's Business and Financial
Performance
HA: Risk Segmentation has a Significant Effect on a Company's Business and Financial
Performance
Hypothesis #7: Mature Companies Applying Push-Pull Supply Chain Strategy Are More
Resilient To Risk Disruptions Compared To All Companies
Ho: Push-PullSupply Chain Strategies Have no Significant Effect on a Company's
Business and FinancialPerformance
59
Push-PullSupply Chain Strategies Have a Significant Effect on a Company's Business
and FinancialPerformance
HA:
After excluding mailing errors, 1551 emails were send out. The survey response rate cannot be
calculated because PwC also contacted companies in Japan, India, China, Mexico etc. using their
own internal lists. After cleaning the data from test records and screening them for missing
values the sample of 209 companies was retrieved and used to test the hypotheses. Statistical
methods were used to develop the conclusions of the tests.
6. Supply Chain Risk: Key Insights
The empirical study offers valuable insights into how mature capabilities in supply chain and risk
management leads to better operational performance. At the same time, it provides value insights
into the impact of disruptions on the company's business and operational performance indicators
over the last 12 months for mature vs. immature companies. These indicators cover the full
spectrum of company performance along the profitability, efficiency and service dimensions. In
particular, the study measures the scale of the impact as well as the time it took to recover to
prior or improved levels of performance. The important contribution of this work is that the key
insights offered are not based on anecdotal evidence but are validated using the data the 209
companies provided by participating in this study.
6.1
Key Insight #1: The Majority of the Companies Have Immature Supply
Chain Operations And Risk Management Processes In Place
The framework presented in the previous section is critical in evaluating each company's
strategy. It reveals an important insight in the current maturity state of the company's supply
chain operations and risk management processes. The data demonstrates that:
The majority of the companies have immature supply chain operations and risk management
processes in place. Figure 36 suggests that most of the companies pay marginal attention to
managing supply chain risk. Only 41 percent of the companies are classified as having mature
processes. The study suggests that 59 percent of the companies have immature risk governance,
internal integration, external collaboration, supplier alignment or flexible business processes in
place to effectively address incidents. Most of companies (42%) are in Level II, a sizeable piece
(32%) belongs to Level III and only a small part (9%) belongs to the highest Level IV. This
60
maturity profile illustrates that only a minority of companies are fully prepared to address
potential challenges from supply chain disruptions in increasingly complex environments.
Capability Classification of Companies
42.O%
45.0%
40.0%
35.0%
30.0%
25.0%
20.0%
15.0%
.2%
10.0%
5.0%
0.0%
LEVEL
1
LEVEL 3
LEVEL 2
LEVEL 4
Figure 36. Capability Maturity Profile of the Surveyed Companies
We have asked our participants to indicate "what department or functional area is responsible
risk management within the organization. Figure 37 shows the responses: Operations (26.4
percent), Finance (23.6 percent), Corporate (11.5 percent) and Procurement (10.3 percent). It is
noted that the majority (80%) of the companies that selected "None" are Immature Companies.
In the "Other" category, the functional areas that were denoted were: Risk Management, Supply
Chain, or Cross Department (managed by Corporate)
61
Functional Area Managing Risk
Operations
I
Finance
I-I-I-g-
2:
I-I
Corporate
*11.5%
Other (Legal, Quality)
10.9%
Procurement
10.3%
None
7.59
4.6%
Manufacturing
Supply Chain
1%
1..%
Sales
HR
26.4%
o.6%
C.0%
5. 0%
10.0%
15.0%
20.0%
25.0%
30.0%
Figure 37. Functional Area Managing Risk
6.2
Key Insight #2: A Company May Be Mature In One Risk Reduction Enabler
Area and Immature In Another
Table 2 shows a company's supply chain and risk management classification ranking against
each enabler. For example, based on our criteria, Company 2 is assessed as Level 4 with respect
to Risk Governance, Level 2 with respect to Flexibility, Level 1 with respect to Upstream and
Downstream Integration and, Level 3 with respect to Alignment, Integration, Data Models and
Analytics. The assessment shows that Company 2 is immature in the Flexibility and, Upstream
and Downstream Integration areas but mature in the other areas. Overall, Company 2 is assessed
as Level 3, matured. Table 2 reveals the following observation:
A company may be mature in one risk reduction enabler area and immature in another
62
Table 2. Capability Classification per Risk Reduction Enabler per Company
Su
1 Chain Risk Enabler Dimensions
1
LEVEL 2
2
3
4
8
9
EELLEVEL
LEVL2
6
7
2
LEVEL2
LEVEL 2LEL
LS
LEVEL 2
LEVEL 2
LEVEL 2
LEVEL 2
VEL 2
VEVE2
10
LEELE
LEVEL 2
13
Is
LV
IEVEL 2
LEE22
LVL
EV
L
EVEL2
iLEEL
2
LEVEL
VEL 2
LEVEL22LV
2
!LEVELVEL
202 LEEL
2L
ELL
LEVEL 2
VEL2
is
LEVEL
EVEL 2
LE
LEM 2
23
6.3
Key Insight #3: Companies with Mature Capabilities In Supply Chain And
Risk Management Do Better Along All Dimensions Of Operational And
Financial Performance
A closer look into the supply chain / risk management framework suggests that company
executives need to comprehend and determine what are the business and financial consequences
of their last 12 months' supply decisions. The capability maturity evaluation will enable
company executives to assess the risk position and maturity of the company measured in terms
of their operations and financial performance.
Figure 38 illustrates the prior 12 months' business and operational performance for all companies
that participated in our survey. Using the capability maturity model we compared the differences
in overall performance between companies with mature and companies with immature risk
processes. The multiple graphs in Figure 13 show that for each measure of supply chain
indicator the mature companies have better performance overall. For example, immature
companies have far less Inventory Days of Supply (56.8 days) than mature companies
(80.3days), a 29 percent improvement. Similar results are obtained for Lead Time in the supply
chain, on-time delivery performance to requested date (.5 percent), inventory carrying costs (24
percent), fill-rate level (6.8 percent), costs of obsolescence -34 percent), cash-to-cash cycle
63
(5.9%), inventory turnover and total asset turnover. In some cases best in-class companies are
performing even better. The study divulges a very key insight:
Companies with mature riskprocesses achieve better business operationsandfinancial
performance than companies with immature riskprocesses
Lead Tfme inyourSupply
Chain (day)
nvvnorydaysofSupp1y
(days)
58
56
60
3.8
W
ToralAssetTurnoter
Cash-to-CashCyde(days)
1.4
76
o.6
40
o.a
Immantg(Lj- Monwa(L-La)
La) Coiupaats
4n8 ma(La-
CaMpania
La) Conpauis
Manzr(L£La)
68-
Corniasw
nmarum(Zj-Z.)
L
Maara(Li -LO)
iaue(a)
compaief
Menw.(L-La)
campanim
im
Inventory Turnoverratio
CostofObsolescencw(asa%of
totalrevunje)
&
InventrxCarrrinqCostsas
a %ofRevenue
7.396
6.u%
.%
8o o%
14&A
4.0%
i
I
6.*M
2.0%-
88%
s
0**
0.0%
On-timedeliueryperformunce
torequestedDate(%)
I
-- -L
La)C.pc.iUa) C-Paxei-
Cs~cL
Ci-wps,.i
Orderfiullf&nenrleadtime
(MTS) (days)
Fillrateby order(MIS only)
(96)
86.o%
"2.0m
351
Zmnira('Lj Mawr (Li-La)
hnmaWu(Lz- Man"r(Li-Lq)
Ua) Companf
CcePauit
La) Corpaial
Ccanlma
Figure 38. Mature capability companies performed operationally better than immature ones
Similarly, Figure 39 shows the revenue growth for mature capability companies is 11.6 percent
vs 6.3% for immature ones, an 84 percent difference. Mature capability companies have an
average EBIT Margin of 13.7 percent vs. 11.7 percent for immature ones, an 18 percent
difference.
64
a55%
14*0 N
A4-09
15.0%
13+5%
8%
a5%
a4oM
lmniatwft(Lz -a)
CavUPiff
EBITMargin(%)
RevenueGrowth(%)
MarketShare(%)
6.
4.0%
1.%
2,o%
LS.0%
0.01%
Mazaw(LI-LO)
cwqift
Immatu.I-Ls)
cnmwu~
MaWr. (L-La)
cmuom
L
immatur. (Li -La)
Co"Jpw1ff
Uann-. (i-La)
Coruania
Figure 39. Mature capability companies performed financially better than immature ones
Figure 38 and Figure 39 provide an important insight to Chief Executive Officer of the
Company. Actual data show that companies with mature risk processes in-place perform far
better across the board on both operations and financial performance than companies with
immature risk processes. Risk Mature supply chain strategies and decisions have a direct impact
on working capital, but working capital flows and balances have a direct impact on the financial
viability and performance of a company.
In Summary, the company's supply chain and risk management strategies have direct
implications on the company's competitive advantage
6.4
Key Insight #4: Supply Chain Disruptions Have Significant Impact on a
Company's Business and Financial Performance
To better understand the impact of disruptions 2 , we assessed the performance of companies that
were faced with at least three disruption incidents over the last twelve months. Survey findings
reveal that these supply chain disruptions have had a significant impact on companies'
profitability, efficiency and service indicators over the last 12 months. For example, as shown in
Figure 40, 54 percent of all companies faced with three or more supply chain disruption incidents
over the last twelve months suffered a three percent or higher impact on their sales revenue as a
result of these disruptions. Similarly, 64 percent of all companies with three or more supply
chain disruptions suffered a 3 percent or higher decline in their customer service level as a result
of these disruptions. In all the operational KPIs examined, at least 60 percent of companies that
faced supply chain disruptions reported a 3 percent or higher loss of value. The high percentage
2
Information about disruption impacts are self-reported by survey participants.
65
of impacted companies demonstrates the importance of having mature capabilities in place to
deal with supply chain disruptions.
% Companies Impacted
80.0%
70.0%
63.9%
66.7%
63.6%
65.1%
67. 9'
60.0%
52.3%
I
50.0%
4 0.0%
41.0%
3 0.0%
20.0%
10.0%
0.0%
-
I-
P.6
AN~
6
Figure 40. Percentage of Companies that suffered 3% or higher impact on their performance
6.5
Key Insight #5: Companies with Mature Supply Chain and Risk Management
Processes Are More Resilient to Risk Disruptions than Companies with
Immature Risk Management Processes
The company classification profile, which is shown in Figure 36, divides the companies into a
set of immature and mature capability clusters of observation for the purpose of generating
insight. The study shows a significant performance difference due to the impact of disruptions
between the two clusters. Figure 41 shows the percentage of companies with more than 3
incidents that suffered an impact 3 percent or higher on their performance as a result of supply
chain disruptions in the last twelve months. The results provide a validation of an obvious
statement:
The percentage of mature companies suffering more than 3 percent impact on theirperformance
as a result of disruptionsis significantly less than companies with immature risk processes
Companies with mature risk managementprocesses are more resilientto risk disruptions than
companies with immature risk managementprocesses
66
For example, only 44 percent of the companies with mature processes, faced with three or more
supply chain disruption incidents, suffered a 3 percent or more decline in their revenue in
comparison to 57 percent to companies with immature processes. This is a 13 percent difference
in the number of companies between the two groups. The difference is striking in key areas such
as total supply chain cost, order fulfillment lead-times and lead-time variability. Considering that
these areas are among the ones most heavily impacted by supply chain disruptions, mature
companies gain an advantage that is potentially decisive.
Market valus of the company
45.0%.
40 if,
Total cn
Market-share
Sales Revenue
90.0%
40
70.0%
,0.0%
60.0%~
3:.cft
40.094
~
5
L
300%
15.0%
20.0%
10.0%
0. W
Jm.'mttwe
mature
Cuatomar service levlor RK-rate
Inventory turas
Supply cAuk ast allzudon
m(r0%
66L L96
Total supply chain lead-those
70.0%
$
68.0%6
680%y
(6 t
62 0%
N
62.0%
62,D%
60.1%
W 066
.5096
5$,0%
54.09
54.0%
Imosute
56-06
imunetle
Y~f u
i
Mate
Total supply chain lead-time
Vuff.616
8021%
M (At
W00%
75J0%
50.0%
4609%
3im696
30.09.
Y0.0%
MD1%
10.05.
0D%1
C0.
Iemiut
wmat
Order f iliment lead-time
variability
70D1%
Irrwrtur-
Mat it
B)ov
J4-,.
Figure 41. Key Performance Indicator resilience to disruptions between mature and immaturity levels
6.6
Key Insight #6: Mature Companies Investing In Supply Chain Flexibility Are
More Resilient To Disruption than Those That Do Not Invest In Supply
Chain Flexibility
Flexibility is a very important aspect of a company's capability to adapt to change. For example,
companies may respond to demand changes, labor strikes, technology changes, currency
volatility, volatile energy / and oil prices based on the degree of flexibility in their businesses.
The higher the degree of flexibility the more expensive it is to achieve it. There is a similar
situation with the customer service levels. On the other hand, certain companies strive for
67
minimizing costs vs. investing in flexibility or customer service level. In the study we asked the
companies to identify the key supply chain value drivers for their leading customer value
proposition. Figure 42 shows that high customer service level (34%) and flexibility (27%) are the
top two drivers followed by cost minimization (22%) and efficient use of the inventory (14%).
Value Drivers
High Customer Service Levels
4.0%
Flexibility and Responsiveness
2713%
Total Supply Chain Cost Minimization
22. %
Efficient Use of Inventory and Supply Chair Assets
Other
0.0%
3.9%
2.9%
5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0%
Figure 42. Key supply chain value driver to match customer value proposition
Apparently, the choice of supply chain value drivers form two very interesting groups: the costefficient group, which contains the mature companies that at the same time selected a cost or an
efficiency supply chain value driver, and the flexible-response group which contains the mature
companies that at the same time selectedflexibility or customer service levels as their key supply
chain value driver.
The performance resilience to supply chain disruptions for both groups is assessed. Figure 43
highlights the major difference between the two groups. The percentage of companies that
suffered a 3 percent or higher impact on their KPIs as a result of more than 3 supply chain
disruptions faced in the last twelve months is significantly lower for the flexible-response group.
The performance of cost-efficient companies has suffered more from the changes and disruptions
in their supply chain even if they possess mature capabilities in deploying their strategy. This
observation leads to another important insight:
68
Mature companies investing inflexibility, responsiveness and customer service, demonstrate
higherperformance resilience comparedto companies whose strategies emphasize cost and
efficiency.
Market
valase of the company Greater
thee 3% Impact
4612%
43.0%
40.M
Saks revnue Greater
49D%
47D%
53.3%
3901%
46-19i
460%
45Dhp
37.0%
36.0%
51.0%
10.(A
5.49
0.4
31.0%
C
Cost Eficiet
700
200
Cost
Fite~l trr
Customer
Inentory turns Greater .haens3% himpact
70D3%
64.0%
S
%
62a1%
Effdent
FIebe
Coltfiet
Response
service level or fill-ret. Greater
Total
F460 tle
Well
supply delie lead-tSle Greater
than 3% Impact
then 3% Impact
66D%
S
607
111D0%
73F
p
44.0%
4020 S
300
41110%
t0%p
colt Efficirnt
Fllile Respowe
Supply chain aeaet utilletion Greater
taen S% Impact
2O
50.0%
330%,
32.3%
420%
35.0
30.0
S3%
35.7%
43.0%
20.M
Total costGreatertl*An 35 inspact
Market-share Greater then 3% Impact
than 396 Impact
60.0%
40.0%
54.0%
S
10.01S
560k
30D%
201)
54D%
100%
30.0%
20.0%
10.0%
020!
C"lt Efficent
FeibheResponse
cost Efficien
Cog Efcient
F6Ul trn
Total supplychain led-tm vulablility
Fexible Response
Cot Efiint
Fv1beAesos
Ordr fulfllrment lead-time Greater than
3% Impact
GreatartOwn 3% inspact
SO.0%
73.3%
70D%
50.3%3
70V%
60.3%
40.0%
40.0%
10.0%
30.3%
20%
Colt Efficient
Fietil Response
Cost Efficient
Flexble Response
Figure 43. Performance of mature cost-efficient vs mature flexible-response companies
The findings presented in Figure 42 also illustrate that the largest majority of cost-efficient
companies are faced with high variability in their supply chain lead-times once a supply chain
disruption takes place. This observation is interesting considering that low variability is one of
the key drivers of an efficient operations strategy.
6.7
Key Insight #7: Mature Companies Investing in Risk Segmentation Are More
Resilient To Disruptions than Those That Are Not Investing In Risk
Segmentation
Companies with different value propositions within the supply chain emphasize different value
dimensions. At the same time, today in order to target different market segment companies you
need to typically compete with more than one customer value proposition. It is common, for
example, that one part of the product portfolio may emphasize the price dimension as key
69
differentiator while a second part may emphasize product innovation or product selection and
availability. Figure 44 shows the key dimension of the leading customer value proposition for
the companies participating in the survey. The top three choices are: Quality (23%), Innovation
(14%) and Price (14%).
Customer Value Proposition
Quality
23.2%
Innovation
i40%
.
Price
'3.7%
Product Selection and Availability (Product Portfolio)
10.8%
Customer Experience
9%
Delivery Reliability
8. %
Value Added Services
6 2%
Volume Flexibility
2
0.0%
5.0%
10.0%
15.0%
20.0%
25.0%
Figure 44. The key value dimension of the leading customer value proposition of survey participants
Different value propositions - and the corresponding operating strategies - do not necessarily
have the same risk profile. Value dimensions are not exposed to the same threats and
vulnerabilities. As a result, the management of supply chain risk - exposure reduction and
mitigation strategies - may need to vary significantly. For example, consider a value proposition
emphasizing product innovation. The high speed of innovation, the corresponding lower forecast
accuracy, the higher price risk and the higher supply risk will essentially determine the type of
strategy the company deploys with its supplier. For example, if the price risk or supply risk is
higher as a result of the speed of innovation then it is more likely that flexible risk-sharing
contracts, rather than the build-up of inventory buffers is appropriate. Figure 45shows what
percentage of companies actively pursued risk strategy segmentation: almost 60 percent of the
companies apply risk segmentation strategy across their product portfolio and 40 percent do not
apply risk segmentation.
70
% of Companies Using Risk Management
Segmentation
70.0%
59.4%
60.0%
50.0%
40.6%
40.0%
30.0%
20.0%
10.0%
0.0%
Companies that Segment their Companies that do not Segment
their Risk Strategy
Risk Strategy
Figure 45. Percentage of companies that perform risk strategy segmentation
The companies that pursued risk segmentation were asked the question "What are the product
differentiators for their strategy?" Figure 46 reveals that the top three choices were: strategic
importance (56%), then demand volatility (52%) and finally sales volume (45%).
Risk Differentiation Parameters (%)
II
III
-I-I-I-i-I-
Strategic importance
56 .0%
-I-I-I-I-
Demand volatility
51.7%
-I-I-I-I-
Volume
45.
-i-I-I-
Profit margin
40.2%
in fioln
-I-I-I'
Purchase price risk
Supplier historical performance
-I-I........ 24.
The stage of product in life cycle (Early Life,
23.09
Maturity, End ot Lite)
The lengLh of product life cyde
19.6%
Other
0.0%
5.3
10.0%
20.0%
30.0%
40.0%
50.0%
Figure 46. Key product differentiators for risk strategy segmentation
71
60.0%
The study clustered all companies with mature capabilities into two main groups: the ones that
perform risk strategy segmentation and the ones that do not. Then, the performance resilience to
supply chain disruptions for both groups was assessed. Figure 47 highlights the major difference
between the two groups across operations and financial performance indicators. For example, in
the sales revenue category, only 32 percent of the mature companies were significantly impacted
as a result of incidents that occurred in comparison to 70 percent of immature companies - this is
a 38 percent difference! This observation presents the following insight:
Mature companies investing in risk segmentation strategiesbased on different value proposition
riskprofiles, demonstrate higherperformance resilience compared to companies that do not
segment their risk strategies.
Markat value of the company
Greater than 3% Impact
54.591
60.0%
800%
Market-share Greaterthan 3%
Impact
700
80.0%
10.0%
70.00%
60.0%
50.0%
40
Sales revenue Greater than 3%
Impact
0%
30.0%
50.0%
40.0
20.0%
30.0%
0.0%
Do not Segment Risk
strategy
40.0%
30.0%
800%
'700%
-
Do not Segment
70
50,0%
40.0%
30.0%
20.006
10.00/
0%
30"0%
200%
1010%
0.0%
Sno
egmari Risk
Stmtegy
Segment R
iey
100%
b
0%
500%
40-0%
90.0%
80.8%
-
20.01N
300%
30 09.
Do not
Segment Risk
Strategy
Segment Risk
Strategy
Do not SegmetI Risk
ttmteo
Segment Risk
Stmleav
order fulfillment Iead-tim* Greater
than 3%Impact
80.0%-
SO.0%
70.0%
6040%
50.0%
400%
70.0%
0.0%
90.0%
591%
Strategy
20.0%
Total supply chain lead-time
variability Greatorthan 3% Impact
80.0%
70.0%
6010%
50.0%
Se1
nt Risk
Strategy
$0.0%
80.0%
10.0%
Do not Segment Risk
Total supply chain lead-time
Greater thea 3% Impact
90.0%
90.0%
Segment Risk
Straeg
Dotot Segment
Riek Strategy
Segment Risk
Sbtegv
Customer serice level or mI1-rate,
Greater than 3% Impact
100.0%
90.0%
0.0%
Do not Segment Risk
Sap,
Invegnory terms Greater than 3%
Impact
600%~
D
segment Risk
Strategy
RI* Stratety
10.0
10.0%
00%
0.0%
7D7%
5%
40.0%
30.0%
Segment Risk
Strategy
Sapply chain asset atzation
Greater than 3% Impact
63.6%
60.0%
L%%
20.0%
10.0%
00%
Total cost Greater than 3%Impact
70D1%
455%
400%_
30.0%
300%
10.0%
10,0%
Do not Segment Risk
Strategy
-
20.0%
10.0%
0.09A
Do not Segment Risk Segment
Strategy
Segment Risk
Strategy
Risk Strategy
Figure 47. Difference in performance impact based on risk strategy segmentation
Figure 48 highlights another key insight: a company that uses mature supply chain and risk
management methods has a resilient supply chain that allows it to recover faster from disruptions
in comparison to a company that uses immature methods. For example, in the customer service
72
level function, only 50% of the mature companies with 3 or more incidents recover in more than
2 weeks vs 70% of immature companies. This observation presents the following insight:
Mature companies investing in risk segmentation strategies based on different value proposition
riskprofiles, demonstrate lower than 2 week recovery time in their KPIs comparedto companies
that do not segment their risk strategies
Market valu, of the company:
Greeterihan 2 wk Recovery Time
Salee revenue: Greater than 2 wk
90.0%
loto.R
W0ON
80.0
70 0%
60.0%
SO OR
40b0%
30.0%
Mom
61L9%
60.0%
20.0%J-
10.0% -
Market-share: Greater than 2 wk
Recovery Time
Recovery Time
80.0%
70.0%
60.0%
50.0%
40.006
30.0%
20D0%
10.0%
80.0%
800%
70.0%
50096
,0.0%
7-2.%
Risk
Segment Risk
Strategy
Do not Segment
Risk Strategy
Strategy
Supply chain sow utilization:
doan 2 wk Recovery Time
Greater
737%
I
75.0%
650%
60,0%
000%
-
650%
70.0%
20.0%.
62.0%
Do not Segment Risk
Segment Risk
Strategy
Strategy
Do not Segment
R.IkShtegy
200%
571%
10.0%
Do not Segment Risk Segment Risk Strategy
Strategy
Segment Risk
Uitegv
--
I
30.0%
10.0%
500%
7~
700%I-..-
40-0%
f
40.0%
30.006
---
50.0%
I
50.0%
55.0%
Total supply chain lead-tirne: Greater
than 2 wk Recovery Time
Customer service level or fiil-rete:
Greater than 2 wk Recovery Time
90.0%
10.0%
80,0%
Do not Segment Risk Segment Risk Strategy
Strategy
Segment Risk Strategy
Strategy
Strategy
78.0%
76.0%
72.0%
74.0%
72.0%
70.0%
680%
F
10.0%
Do not Segment Risk
Risk
laveetery tares: Greaterlthan 2
wk Recovery Time
820%
750%
segment
I
20.0%
0a0%
Do not Segment
Total cost: Greater than 2 wk
Recovery Time
Do not Segment Risk
Strategy
Segment Risk Srategy
Order fulfiment laedtlime: Greater
then 2wkRecovery Time
Total supply chain lead-time
variability: Greater than2 wk
Recovery Time,
00%
72.0%
70.0%
W0.0%
64.0%
62.0%
60.0%
511.0%
70.0%
602.0%
70.0%
5D.0%
50,0%
90.0%
40.0%
30.0%
0.0%
Do not Segment Risk
Strategy
10.0%
Segment Risk
Strategy
Do not Segmentlitsk Segment Risk Strategy
Strategy
Figure 48. Difference in performance impact based on risk strategy segmentation
6.8
Key Insight #8: Mature Companies Applying Push-Pull Supply Chain
Strategy Are More Resilient To Risk Disruptions Compared To All
Companies.
Manufacturing supply chain strategies are categorized into push, pull and push-pull strategies:
the push strategy where production and distribution is based on long-term forecasts and pushes
inventory to retailers, the pull strategy where production and distribution respond to customer
demand and the push-pull strategy, a hybrid combination of the push and pull. As expected,
almost 60 percent of the companies use the combination of push-pull strategy, 24 percent use the
pull strategy and 16 percent use the push strategy. Figure 49 shows the distribution.
73
Operational Strategy
70.0%
59.4%
60.0%
50.0%
40.0%
30.0%
244%
20.0%
10.0%
0.0% 4
Combination of push-pull
(hybrid)
Pull (respond to customer
demand)
Push (inventory)
Figure 49. Operational Strategy
The study looked at the relation between operations strategy and performance parameter
resilience. Figure 50 shows that the percentage of mature companies with a combination of pushpull operations strategy are less impacted. This finding leads to another observation:
Mature companies applying a combination ofpush-pull supply chain strategy are more resilient
(exhibit 3% or high impact to their KPIs) to risk disruptions comparedto all companies
Operational Strategy (push-pull):
Inventory Turns Greater than 3% Impact
Operational Strategy (push-pull):
Lead-Time Greater than 3% Impact
Operational Strategy (push-pull):
Service Level Greater than 3% Impact
62.0
020%
000
610%
000%
6(10%
56.0%
55.0*
.A0
SIM
U
orlull
AhorPull
4.0%
,4 /%
W3.%
5300
,
480%
460%
Nl Levels
mature
Operational Strategy (push-pull): LeadTime Var. Greater than 3% Impact
7n ft.
Operational Strategy (push-pull):
Order Fullfilment Lead Time
700
60.0%
66.0%
6
629
%
Is,6h oll
0D.0%
15*
*'s::t-r
mtI
48,6*
4,2*
45*
f
a71.
40.036
0 PW
-Pu I
200
44
2r*
670*
42.0*
C Pu
10016
005
All COIes
66.0%
61 7%0
W5
300Off
A00.
Operational Strategy (push-pull):
Total Cost Greater than 3% Impact
Y0.
504o%
64%
6
150%
540%
W06
6ai.e
Ales4wi
AIL-el
Figure 50. Companies with Push-Pull strategies are more resilient
74
MILL..
O,0u
I
6.9
Linking Supply Chain Risk with Operational and Financial Performance
The analysis and the key findings are summarized in Figure 51. The horizontal axis provides
information about the maturity levels of the risk management processes, and the vertical axis
provides information about the maturity levels of the supply chain functions. Box A represents
companies with immature supply chain and risk management processes. The study shows that
these companies' operations and financial performance is impacted significantly in the face of
disruptions. The impact is on inventory days of supply, cost of obsolescence, inventory carrying
costs, sales revenue and EBIT margin.
Cd
0O
S
CZ
B
Integrated and Collaborative Supply Chain
C
Dynamic supply chain tunctions and
with Buffer planning capability
" Systems internally & externally integrated
flexible risk management
* Superior operations/financial performance
* Information sharing btw internal functions
" Build capacity/invcst in inventory to
mitigate risk
" Better operations and financial
*
improvement potential
" Better resilience improvement
- Apply push-pull strategies effectively
Mature risk segmentation strategy
Invest in flexibility to mitigate riskb
* Higher sales revenues
* Superior resilience to disruptions
*
potential
A
D
Adhoc risk management disconnected supply
chain processes
Proactive Rik Management with Integrated
supply chain management
* Lower than average operations& financial
- Systems internally integrated
performance in face of disruptions
* Slower time to recover
- Higher percentage of companies impacted
9 Visibility among supply chain partners
* Proactive risk management
- Business continuity plans in place
in the face of disrnptions
*
Better operations and financial
improvement potential
-Bcttcr
rcsilicncc improvcmcnt potcntial
Mature
Immature
Risk Management Processes
Figure 51. Link between Supply Chain Risk decisions and performance
Box B represents companies with mature supply chain processes and immature risk management
processes. Box D represents companies with immature supply chain processes and mature risk
management processes. Both B and D type of companies perform better that the companies in
Box A but they still have a lot of performance improvement potential. The operation and
financial performance is above average and their resiliency to disruptions is good.
75
Box C represents companies with mature supply chain and risk management process. The
companies are resilient to risk disruptions and exhibit better operations and financial
performance. They apply effectively risk segmentation and push-pull strategies, and invest in
flexibility in order to reduce the impact of disruptions. The study has proven the higher a
company's maturity level in supply chain and risk management the higher performance yield.
What is not clear yet is where the boundaries between mature supply chain / immature risk
processes, immature supply chain / mature risk process and mature / mature processes are. The
cases require further analysis.
76
7. Supply Chain Risk: Summary and Recommendations
The objective of this study is to analyze the supply chain operations and risk management
approaches of large revenue size companies with global footprint and propose a framework and a
set of principles that will help all companies manage today's risk challenges and prepare them
for future opportunities.
The MIT/PwC Global Survey solicited input from 209 companies. The data indicate that
globally operating organizations are faced with incidents that exposed them to high risk
scenarios ranging from controllable risk such as raw material price fluctuation, currency
fluctuation, market changes or fuel price volatility to uncontrollable ones such as natural
disasters. These risks have a disruptive impact on the company's operations and financial
performance. The study shows that 65 percent of the companies suffered impact of three percent
or higher on their performance indicators as a result of supply chain disruptions in the past
twelve months. The degree of disruption depends on the strategic mitigation actions the
company takes to anticipate and plan in advance to address these risks. The survey responders
specified three top strategic actions to address these risks: (a) use both regional and global
strategy, (b) implement a business continuity plan and, (c) implement a dual sourcing strategy.
Implementing these strategies does not mean that the risk will be totally avoided when the
incidence occurs, but rather it will minimize the likelihood of a significant impact and expedite
time to recover.
We developed a supply chain operations and risk management model to provide a capability
maturityframework to classify how well the companies are applying the most important supply
chain and risk reduction enablers (e.g., flexibility, risk governance, alignment, integration,
information sharing, data analysis and models, and complexity) and their associated processes.
The model reveals where a company stands in relation to its competition and the rest of the
industry. The data show that 60 percent of the companies pay marginal attention to risk
reduction processes. These companies have immature risk processes in place and address risk by
either increasing capacity or strategically positioning additional inventory. This is not a surprise
as most of these companies are focused either on maximizing profit, minimizing costs or
maintaining service levels.
77
Our data also illustrate that 40 percent of the companies pay strong attention and invest in
acquiring advanced risk reduction enabler capability. These companies think beyond the
economics that made off-shoring attractive in the first place (e.g., low cost labor). The study
reveals five key insights:
a. Key Insight #1: Supply chain disruptions have significant impact on company
business and financial performance
b. Key Insight #2: Companies with mature risk management processes are more resilient
to risk disruptions than companies with immature risk management processes
c. Key Insight #3: Mature companies investing in supply chain flexibility are more
resilient to disruption than those that do not invest in supply chain flexibility
d. Key Insight #4: Mature companies investing in risk segmentation are more resilient to
disruptions than those that are not investing in risk segmentation
e. Key Insight #5: Companies with mature capabilities in supply chain and risk
management do better along all dimensions of operational and financial performance
Insights #1-#5 display the competitive power of being capability mature. One important
contribution of this work is that the key insights offered are not based on anecdotal evidence but
are validated with the 209 companies that participated in this study. Using the data we validated
that companies with mature risk processes do operationally and financially better. This is an
important message to the CEO and CFO. Managing risk is not only about operations and supply
chain management but includes every aspect in a CEO's sphere of influence for product design,
development, operations and sales. Insurance is not the solution to address risk incidents;
insurance does not cover everything. Using the capability maturity model we can "assess" each
business's ability to respond.
Finally, a company needs to be self-aware where they and their competition stand with respect to
managing risks. If the competition has a lower risk maturity capability level than your business,
then this attribute is your competitive advantage over them
78
8. Appendix A - Operations and Financial Definitions
The key operations [11] and financial performance [12] indicators used in this study are
described below.
Market- Value:
The current market value of a company is the total number of shares outstanding multiplied by
the current price of its shares. Recent research has shown that shareholder value can be
significantly impacted by severe supply chain disruptions. For example, Mattel, the world's
largest toymaker, had to issue a major product recall due to quality assurance and consumer
product safety risks . Mattel's stock-price suffered a steep fall when the recall was announced in
Q3 2007 and did not recover for many months to come.
Sales Revenue:
The revenues a company makes after the sale of its products. Supply chain disruptions or
structural market shifts can impact a company's capability of delivering the value proposition
and can lead to loss of sales volume and sales revenue.
Market-Share:
It is the company's sales over the period and divided by the total sales of the industry over the
same period. Loss of delivery capability or damaged brand image can lead to market-share loss,
especially, when the impact of a supply chain disruption is long-lasting.
Earningsbefore Income and Taxes (EBIT)Margin
It is the earnings before interest and tax (EBIT) divided by total revenue. EBIT margin can
provide an investor with a cleaner view of a company's core profitability
Total Supplv Chain Cost:
It is the costs to procure materials and, manufacture and deliver products to customers. Supply
chain disruptions have an impact on total supply chain cost as a number of activities need to be
expedited or redesigned across the various functions to adjust and recover.
Supplv Chain Asset Utilization:
79
Supply chain asset utilization is a measure of actual use of supply chain assets divided by the
available use of these assets. Assets include both fixed and moving assets. Fixed assets enable
direct product development, transformation, and delivery of a company's products or services, as
well as indirect support, and, typically, have greater than one year of service life. A disruption
can directly impact the usability of assets and resources or cause their re-positioning in order to
recover. As a result, the utilization of key assets and resources may deviate significantly from the
set targets.
Inventory Turns:
Inventory turnover ratio measures the efficiency of inventory management. It reflects how many
times average inventory was produced and sold during the period. A disruption or change may
impact inventory efficiency either by introducing increased obsolescence or by changing
inventory positioning and consumption plans.
Customer Service Levels:
It is the probability that a customer demand is met. The loss of delivery, customer
communication or customer service capability due to a supply chain disruption can impact
customer service levels.
OrderFulfillmentLead-Time:
The average actual lead times consistently achieved, from order receipt to order entry complete,
order entry complete to start-build, start build to order ready for shipment, order ready for
shipment to customer receipt of order.
Total Supply Chain Lead-Time:
Total supply chain lead-time in supply chain management is the time from the moment the
customer places an order (the moment you learn of the requirement) to the moment it is received
by the customer. In the absence of finished goods or intermediate (work in progress) inventory, it
is the time it takes to actually manufacture the order without any inventory other than raw
materials. Supply chain disruptions can introduce significant delays across all supply chain
stages.
Total Supplv Chain Lead-Time Variability:
80
Total supply chain lead-time variability is the time variation around the total supply chain leadtime mean. Supply chain disruptions can introduce variability and fluctuations in the standard
lead-time levels within the supply chain..
81
9. Appendix B. Capability Maturity Classification Model
Table 3 provides amplifying information about the Supply Chain Risk Maturity Classification
Model.
Table 3. The Capability Maturity Classification Model
82
10.
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83