Disruptions in Supply Networks: A Probabilistic Risk Assessment Approach
Published date | 01 September 2015 |
Date | 01 September 2015 |
DOI | http://doi.org/10.1111/jbl.12086 |
Disruptions in Supply Networks: A Probabilistic Risk Assessment
Approach
Anssi K€
aki
1
, Ahti Salo
1
, and Srinivas Talluri
2
1
Aalto University
2
Michigan State University
Supply disruptions are attracting growing attention. Even in geographically, politically and economically stable locations, companies are
exposed to disruptions, because they depend on their suppliers and suppliers’suppliers. The analysis of these disruptions helps mitigate
risks: for example, instead of relying on local measures such as safety stock or insurance, a company can introduce new supply contracts or
backup risky suppliers. In this article, we analyze risks caused by supplier disruptions by introducing concepts from probabilistic risk assess-
ment (PRA), which is a widely employed methodology for the risk analysis of complex engineering systems. We apply PRA to examine simple
networks such as triads analytically, and use simulation to analyze disruption risks in random networks of realistic size. We also illustrate how
PRA can support strategic decisions such as whether or not to use single or multiple suppliers; which suppliers are more risky than others; and
what impacts the complexity of the supply base has on the reliability of the supplier network.
Keywords: supply networks; supply disruptions; risk analysis; probabilistic risk assessment
INTRODUCTION
Supply networks have become more complex due to the growth of
global supply alternatives and strategic outsourcing. While the
expansion of a company’s supply base can decrease costs, it affects
the risks, responsiveness, and suppliers’innovation capabilities
(Choi and Krause 2006). Thus, the goal of supply network man-
agement has shifted from short term cost savings to the pursuit of
long term strategic benefits and the improvement of network resil-
ience (Christopher and Peck 2004; Simchi-Levi 2010). Indeed,
Proposition 4 by Zsidisin et al. (2005, 3417) propose that:
[...] supply risk management will evolve so that it
becomes embedded in the everyday strategic practices of
purchasing organizations.
For many reasons, risks caused by disruptive events are chal-
lenging to analyze. First, strong interdependencies imply that dis-
ruptive events must be tracked to disruptions at a supplier, a
supplier’s supplier, or even further upstream in the network (see
e.g., Sheffi2005). Second, most supply networks are large and
consist of numerous nodes (suppliers, tiers) and arcs (supplier
relationships). Third, there can be a very large number of events
that can cause operational, environmental, or financial risks
(Wagner and Bode 2008). Snyder et al. (2010) review disruption
management models that account for these challenges, but most
of these models are built for very specific decision-making situa-
tions, such as where to locate inventory buffers.
In this article, we develop a generic methodology for assessing
risks caused by supplier disruptions in a supply network. The
methodology is based on probabilistic risk assessment (PRA),
which is a standard paradigm for the analysis of complex techni-
cal systems such as nuclear power plants or spacecrafts (Bedford
and Cooke 2001; Stamatelatos et al. 2011). Applications of PRA
methods typically follow the same process: (i) create a structural
model of the system; (ii) identify the key risks and their likeli-
hood; and (iii) conduct a quantitative risk analysis to identify the
critical (most risky) parts of the system. In keeping with this pro-
cess, we examine how much different disruptions in the supply
base contribute to the disruption risk at the focal company. In
particular, we examine how the supplier’s reliability and its posi-
tion in the supply network impact the supplier’s risk importance,
as indicated by probabilistic risk importance measures.
The presented methodology has both theoretical and manage-
rial implications. In contrast to earlier quantitative supply net-
work risk studies that have focused on supplier reliability
modeling, our methodology also addresses dependencies between
suppliers. This provides a new perspective on supplier risk: in
addition to analyzing disruptions per se, we illustrate how
supplier dependencies can mitigate or aggravate the risk in the
supply network. We also present how the supplier’s risk impor-
tance (or, criticality) can be calculated so that it also reflects net-
work risks, in addition to the attributes of the individual supplier.
In strategic managerial decision making, the methodology sup-
ports the design of supply networks. For example, it can be used
to assess whether the use of single or multiple suppliers involves
greater risks, or how the reliability of the supplier network
depends on network complexity. In tactical decisions such as
designing supplier contracts, the methodology can be employed
to evaluate potential actions for improving reliability through
contracts that establish incentives for increased product quality,
for instance. At the operational level, the methodology can be
used for risk mapping and for deciding how closely different
suppliers should be monitored. While the range of possible appli-
cations can be wide, we also note that applying the methodology
is challenging, as quantification of both disruption probabilities
and supplier dependencies can be an arduous task.
The rest of this article is structured as follows. Section “Earlier
approaches to disruptions in supply networks”reviews related
Corresponding author:
Anssi K€
aki, Department of Mathematics and Systems Analysis,
School of Science, Aalto University, P.O. Box 11100, 00076,
Finland; E-mail: anssi.kaki@gmail.com
Journal of Business Logistics, 2015, 36(3): 273–287 doi: 10.1111/jbl.12086
© Council of Supply Chain Management Professionals
To continue reading
Request your trial