Supply Chain Risk Management Approaches Under Different Conditions of Risk

Date01 September 2014
Published date01 September 2014
DOIhttp://doi.org/10.1111/jbl.12051
Supply Chain Risk Management Approaches Under Different
Conditions of Risk
Ila Manuj
1
, Terry L. Esper
2
, and Theodore P. Stank
3
1
University of North Texas
2
Sam M. Walton College of Business at the University of Arkansas
3
University of Tennessee
Arecent Deloitte study of 600 Supply Chain and C-Level executives revealed that 45% felt that their supply chain risk management pro-
grams were only somewhat effective or not effective at all, while a mere 33% used risk management approaches to proactively and strate-
gically manage supply chain risk based on conditions in their operating environment. Using a two-method approach, the research summarized
in this paper investigates the effectiveness of different supply chain risk management approaches by examining how performance varies when
these approaches are applied under different risk conditions. The results counter prevailing knowledge regarding the appropriate use of such
widely acknowledged risk management approaches as postponement and speculation, and highlight the dangers of functionally isolated decision
making. The results lend credence to increasing calls for interdisciplinary research to address broad-based supply and demand chain problems,
and support the need to utilize performance metrics such as net prot to accurately assess supply chain decisions.
Keywords: supply chain risk management; global supply chains; risk management approaches; simulation
INTRODUCTION
Effective supply chain risk management seeks to control unex-
pected outcomes by systematically implementing appropriate
approaches to managing and/or mitigating risk (J
uttner et al.
2003; Norrman and Jansson 2004; J
uttner 2005). Supply chain
risk management is of utmost importance to senior managers
given the potential dire consequences of risk occurrences. For
example, Boeing, Cisco and Pzer each encountered unexpected
losses and/or expenses of greater than $2 billion due to ineffec-
tive supply chain risk management decisions (Hult et al. 2010).
Despite the potential negative outcomes, a recent Deloitte study
of 600 Supply Chain and C-Level executives revealed that 45%
felt that their supply chain risk management programs were only
somewhat effective or not effective at all, and a mere 33% used
risk management approaches to proactively and strategically
manage supply chain risk based on conditions in their operating
environment (Deloitte Development LLC 2013).
The purpose of this research, therefore, is to investigate the
effectiveness of different supply chain risk management
approaches by examining how performance varies when
approaches are applied under different conditions of supply chain
risk. Grounded in systems design theory (SDT), the research uses
a two-method approach. First, a conceptualization of key supply
chain risk management opportunities is developed based upon
results of eld-generated research to portray the relationships
between the use of different supply chain risk approaches under
differing conditions of supply chain risk. Next, computer simula-
tion modeling is used to precisely observe the impact of the use
of four different supply chain risk approaches (hedging, assum-
ing, postponement, and speculation) under varying conditions of
supply chain risk on overall net prot. This research makes two
important contributions:
1. We enhance understanding of the relationships between sup-
ply chain risk management approaches and performance under
different supply chain risk conditions.
2. We provide broad insights on supply chain risk decision mak-
ing to inform future research and practice.
The following sections present the results of the grounded the-
ory research and computer simulation modeling, providing a
brief review of relevant literature as appropriate to support the
qualitative results and develop research hypotheses. Results of
post hoc analyses and interviews conducted to obtain practitioner
insights of the results are then reported, followed by a summary
of the research and managerial implications.
STUDY 1: INDUCTIVELY FRAMING THE RESEARCH
As we began the study, anecdotal evidence suggested that rms
were struggling to design effective risk management systems (we
elaborate on systems design preceding hypothesis development).
Specically, as rms seemed to lack insight into how to align
risk strategies with risk scenarios, we conducted in-depth inter-
views with 14 supply chain managers from nine different manu-
facturing rms. The number and content of in-depth interviews
was based on the concept of theoretical sampling(Glaser and
Strauss 1967; Mello and Flint 2009). The initial participant sam-
ple was selected based upon experience with the phenomena, job
prole and responsibility, and willingness to participate in the
research. Additional participants were selected as the interviews
progressed to enable further exploration of new categories and
concepts that emerged. Interviews continued until theoretical
saturationwas reached. The participants came from a variety of
Corresponding author:
Ila Manuj, Department of Marketing and Logistics, University of
North Texas, 1155 Union Circle #311160, Denton, TX 76203-5017,
USA; E-mail: ila.manuj@unt.edu
Journal of Business Logistics, 2014, 35(3): 241258
© Council of Supply Chain Management Professionals
different roles within multiple industries, with most having over
10 years of experience. Appendix 1 provides demographic
details about the interviewees.
The interview protocol included the use of broad open-ended
questions followed by focused and directed questions as concepts
emerged within and between successive interviews (Strauss and
Corbin 1998; Mello and Flint 2009; Randall et al. 2010; Manuj
et al. 2014). The interviews, which were conducted over a six-
month period, lasted from 40 and 60 min; interviews were audio-
taped and transcribed verbatim. ATLASti was used for coding
the transcripts and standard qualitative techniques were followed
to develop core categories of strategic approaches, supply and
demand risk, and performance outcomes. Categories that
emerged from the grounded theory research were then compared
to existing research to provide a literature-based grounding for
the contextualized concepts found in the eld. Table 1 provides
sample quotes that support the categorization of supply chain
risk management approaches, risk categories, and appropriate
performance metrics.
Study 1 results
Managers in the qualitative study emphasized the importance of
risk arising from the external environment that was out of their
direct control. In particular, managers were most concerned with
the performance implications of the strategic choice of risk man-
agement approaches that are inappropriate considering the char-
acteristics of the risk environment. A review of the academic
literature suggests the same theme, as the appropriateness of sup-
ply chain risk management approaches based on differing condi-
tions of supply and demand risk environments has been
identied as an issue that needs further and immediate attention
(J
uttner et al. 2003; Wagner and Bode 2008; Schoenherr 2009).
Over 40 supply chain environmental risk conditions were
identied. These risk conditions could be grouped into two pre-
dominant categories. The rst category, supply-side risk, is the
risk associated with the availability of raw materials or subcom-
ponents from upstream suppliers that affect the ability of the
focal rm to meet customer demand within anticipated cost and
delivery time requirements (Zsidisin 2003; Manuj and Mentzer
2008a,b). The second risk category is demand-side risk associ-
ated with availability of nished product to meet customer
demand within anticipated cost and time requirements (Zsidisin
2003; Manuj and Mentzer 2008b). Many events related to secu-
rity, policy, competitive, and resource risk eventually manifest
themselves as supply or demand risk.
Interview managers indicated that the appropriate risk manage-
ment approach involves a decision to minimize or to take on
risk. For supply-side risk, the approaches included hedging or
assuming. Demand-side risk approaches included postponement
or speculation. These approaches are dened below:
1. Hedging is designed to balance exposure to supply-side risk
through a globally dispersed portfolio of suppliers and facili-
ties such that a single event (like currency uctuations or nat-
ural disasters) does not affect all the entities at the same time
and/or with the same magnitude (Carter and Vickery 1989;
Bartmess and Cerny 1993).
2. Assuming strategy is designed to internalize supply-side risk
through vertical integration of supply to focus resources and
exploit economies of scale (Wernerfelt and Karnani 1987).
3. Postponement defers the actual commitment of resources by
delaying manufacturing and/or logistics operations to manage
risk in demand uncertainty by maintaining exibility and
delaying incurred costs (Bucklin 1965; Wong et al. 2009). It
must be noted that while postponement includes both form
and time, we focus on form postponement as the qualitative
interviews revealed a greater use of mass customization and
agile manufacturing as the desired means to improve coordi-
nation between supply and demand (Yang et al. 2004; Boone
et al. 2007).
4. Speculation involves maintaining an inventory of nished
products instead of component parts, basing manufacturing
and logistics decisions on anticipation of customer demand,
committing resources in advance but reducing unit costs
through economies of scale, experience curves, etc. (Bucklin
1965; Miller 1992).
The qualitative research also revealed signicant complexities
associated with applying the most appropriate approach to effec-
tively manage or mitigate supply chain risk. The most important
of these was the notion that functional metrics are not sufcient
to assess the effectiveness of global supply chain risk manage-
ment strategies. Rather, the ndings suggest that an overall met-
ric such as total prot is preferred as it takes into account
multiple performance elements including revenue, operating costs
(production, warehousing, transportation, and inventory), and
penalty costs associated with risk events. Such a comprehensive
and holistic measure was viewed as preferred, but difcult to
execute in practice. For example, when discussing total protas
a key measure, participants noted an excessive focus on unit pur-
chasing cost, with one respondent commenting, The import of
that product was (supposed to be) very protable, but a lot of
protability got wiped out.Another suggested that, you can
see pretty quickly that your leverage on a price increase is far
better than your leverage on a cost reduction. (But) we do so
much work on that cost reduction.Similarly, a singular focus
on revenue was also cited as a challenge to protability. For
example, one manager noted, weve done a great job growing
our revenues, but weve not done a great job growing margins.
Despite respondentsdesire to use a broader metric like prot,
many stated that obtaining such information was a challenge. For
example, one manager complained that, I dont have any quan-
tiable facts or gures that I can give youon prot because he
could not gather the data.
The results of the qualitative research provided an interesting
glimpse into the complexities of choosing the appropriate supply
chain risk management approach to optimize performance given
different supply- and demand-side risk characteristics. Supply
chain risk management research and practice could benet from
quantitative research that specically investigates the relation-
ships among the strategic approaches and risk categories identi-
ed in Study 1. Such an investigation requires a method that
allows for the precise observation of the performance implica-
tions of simultaneous and holistic combinations of different stra-
tegic risk approaches and environmental conditions. Thus, we
242 I. Manuj et al.

To continue reading

Request your trial

VLEX uses login cookies to provide you with a better browsing experience. If you click on 'Accept' or continue browsing this site we consider that you accept our cookie policy. ACCEPT