Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management
Kuala Lumpur, Malaysia, March 8-10, 2016
Supply Chain Risk Management in the Indonesian Flavor
Industry: Case Study from a Multinational Flavor Company in
Indonesia
Fransisca Dini Ariyanti and Aditya Andika
Industrial Engineering Department
Bina Nusantara University
Jakarta, Indonesia
[email protected]
Abstract—Supply Chain Risk Management is a relatively new discipline that has the objective of supporting management in
handling risks in the supply chain. The objective of this study is to identify the risks in the flavor supply chain and then assess them
in order to develop appropriate mitigation strategies. Failure Mode and Effect Analysis (FMEA) is utilized to assess the risks. This
study uses a case study approach. The object of the study is a multinational flavor company in Indonesia. This study identified 22
risk factors in the flavor supply chain. Based on the assessment of the risk factors, there are three high priority risk factors:
economic downturn, demand fluctuation, and raw materials shortage. Overall, this study identified and assessed supply chain risk
factors in the Indonesian flavor industry.
Keywords—supply chain risk management; FMEA; flavor; Indonesia
I.
INTRODUCTION
Competitive dynamics and turbulent economic conditions constantly present new challenges to the business environment.
Organizations around the world are continuously seeking ways to gain competitive advantage. One of the ways to improve
competitive advantage is through supply chain management (SCM) practice. Higher level SCM practices by organizations may
lead to the enhancement of their competitive advantage [1].
Organizations currently pursue better ways in their supply chain management practices. One of the ways is by
implementing risk management concepts in their supply chain. Managing risk has become an important business issue and has
been studied in many business disciplines [2]. SCM is one of the business disciplines that have extensively integrated risk
management concepts into its discipline. This integration between SCM and risk management has given birth to the concept
called Supply Chain Risk Management (SCRM). Every manufacturing organization must consider implementing SCRM to
achieve better supply chain executions by using risk mitigation combined with appropriate strategies [3]. Flavor companies as
a manufacturing organization must also consider implementing SCRM.
Flavor companies in Indonesia face various supply chain-related challenges, e.g., raw material shortage, regulations and
standards, and demand fluctuation. They have to manage their supply chain very meticulously. Fig.1. describes the supply
chain for a multinational flavor company in Indonesia that is studied for this research. The name of the company is withheld
for confidentiality reason and will be referred to as “Company X”.
© IEOM Society International
1448
Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management
Kuala Lumpur, Malaysia, March 8-10, 2016
Fig.1.Supply Chain of Company X (source: interview)
This study seeks to identify various risks in the flavor supply chain in Indonesia and then assess those risks in order to
develop appropriate strategies to mitigate those risks.
II.
LITERATURE REVIEW
A. Supply Chain Management
Supply chain management (SCM) is the management of material, information, and financial flows through a network of
organizations with the goal of producing and delivering products or services for the consumers that includes the processes
and activities coordination and collaboration across different functions within the organizations network [4]. SCM has the
main objective of minimizing the cost and maximizing customer satisfaction [5]. Companies that successfully manage their
supply chain will gain several benefits because SCM practices has a positive influence towards operational performance [6]
and business performance [7].
B. Risk Management
Risk is defined in [8] as “… a chance of danger, damage, loss, injury or any other undesired consequences.” Risks need to
be managed. The process of managing risks is called risk management. Risk management is the process in identifying and
assessing risk and then reducing the risk to an acceptable level through various methods [9].
C. Supply Chain Risk Management
Supply Risk is defined in [10] as “the probability of an incident associated with inbound supply from individual supplier
failures or the supply market occurring, in which its outcomes result in the inability of the purchasing firm to meet customer
demand or cause threats to customer life and safety.”
Supply Chain Risk Management (SCRM) is the process in managing risks in supply chain through coordination or
collaboration between supply chain partners to ensure profit and continuity [11]. SCRM in [12] is defined as “the
identification and management of risks for the supply chain, through a co-ordinated approach amongst supply chain
members, to reduce supply chain vulnerability as a whole.”
D. Failure Modes and Effects Analysis (FMEA)
FMEA is a methodology that is used to identify potential failure modes before problem occurs [10]. Risks in FMEA method
are evaluated in three components: severity (S), occurrence (O), and detection (D) [11]. The components of risk in the FMEA
method is similar to the dimensions of risk defined by [13]: likelihood of occurrence of a particular event or outcome;
consequences of the particular event or outcome occurring; and causal pathway leading to the event.These three components
are used in calculating the Risk Priority Number (RPN). FMEA uses the RPN to determine the risk priorities of failure modes
[14].
© IEOM Society International
1449
Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management
Kuala Lumpur, Malaysia, March 8-10, 2016
RPN is calculated with this formula:
RPN = S x O x D
(1)
Failure modes are prioritized based on the RPN values. Failure modes with higher RPN values are given higher priority than
those with lower RPN values [15].
In addition to RPN, several researches also used Risk Score Value (RSV) in the FMEA methodology, such as [16], [17], [18].
The formula of RSV:
RSV = S x O
(2)
The formula of RSV in [16], [17], [18] is in line with the formula of Risk in [19]. Reference [19] defined the Risk Formula
as:
Risk = Probability (of the event) * Business Impact (or severity) of the event
III.
(3)
METHODOLOGY
This study uses a case study approach. Data is collected through questionnaires and interviews. The sampling method used
is judgment sampling. Judgment sampling is a sampling method where study participants are selected based on their expertise
in the subject investigated [20]. Three supply chain management-related managers of Company X were asked to participate in
this study. They were chosen to be the study participant because they were considered as supply chain experts by both the
authors and the management of Company X. All of them agreed to participate.
To identify the risk factors in the flavor supply chain, this study developed a questionnaire that contained a list of risk
factors that were identified in several studies [16], [17], [18], [21]. The study participants will be interviewed by using the
questionnaire in order to identify which of those risk factors are relevant to the flavor supply chain and to add other relevant
risk factors that have not been included in the list. The risk factors are categorized into five categories: demand risk, supply
risk, technology risk, environment risk, and logistics / operational risk.
To assess the priority of the risk factors in the flavor supply chain, this study uses the FMEA approach. The study
participants will be interviewed to determine the values of the severity (S), occurrence (O), and detection of each risk event
(D). The range of score for each of the values is 1 – 10.
The following is the sequence of the research:
1. Interview the managers using a questionnaire to identify risk factors in the flavor supply chain and then assess the
priority of those risk factors by determining the severity, occurrence, and detection values of each risk event.
2. Analyze the questionnaire and interview results.
3. Finalize the severity, occurrence, and detection values of each risk factor with the managers.
4. Calculate RPN value and RSV value of each risk event.
5. Determine the critical value of the RPN and RSV.
6. Develop RPN-RSV Matrix in order to assess which risk factors are high priority risk factors.
7. Conduct group discussion with the study participants to develop risk mitigation strategies for high priority risk
factors.
© IEOM Society International
1450
Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management
Kuala Lumpur, Malaysia, March 8-10, 2016
IV.
RESULTS AND DISCUSSION
A. Research Results
There are 22 identified risk factors that are relevant to the flavor supply chain. Those risk factors can be seen in TABLE I.
TABLE I.
INTERVIEW QUOTES REGARDING RISK FACTORS
Risk Factors
Quotes from the Interview
Demand Risk
Changes in customer taste
Food and beverage taste has trend and life cycle; need good communication,
collaboration and business intelligence to capture trend.
Demand fluctuation
Due to weaken global economic condition, the majority of our customer demand
has fluctuated over past few years. Except key customer, forecast accuracy from
non key customer is less than 50%.
Order cancelation
We have a procedure that is strong and impenetrable to the order cancellation.
Substitutive alternative
Customer request on stronger flavor but cheaper version.
Supply Risk
Raw material shortage
Raw materials from overseas are more vulnerable than local raw material; it has
longer lead time.
Supply quality risk
Global climate change has an impact on natural raw materials & food ingredient.
Procurement risk
Important to choose sustainable supplier for business continuity.
Supplier communication and collaboration failure
To reduce supply chain risk, we build a good relationship and collaboration.
Technology Risk
Infrastructure failure
A part of contingency plan, other plants in other countries can help us ensure the
continuity of supply for our customers.
Business intelligence
Food and beverage taste has trend and life cycle; need good communication,
collaboration and business intelligence software to capture big data in order to
acquire information regarding trend.
Failure in IT system
Implementation of the integrated system throughout the worldwide site plan can
be interrupted at any time.
Environment Risk
Economic downturn
Over past few years all around the world, customer demand was weaker; demand
downturn.
Natural disaster: flood, earthquake, landslide
Natural disaster, such as flooding, has an impact on logistics. However, it rarely
happened.
© IEOM Society International
1451
Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management
Kuala Lumpur, Malaysia, March 8-10, 2016
Terrorist attack
It is unexpected, but we need to prepare it, another site plan will continue supply.
Currency fluctuation
Over the past few years, we do currency hedging.
Pandemic
It is unexpected thing, but we need to prepare it, another site plan will continue
supply.
Logistics / Operational Risk
Internal quality risk
We have procedure to monitor quality.
Regulatory compliance
Scheduled audit to maintain regulatory compliance
Under-utilized capacity
Expand to export market and business segment to optimize capacity
Labor unavailability
In peak demand, we do overtime and outsource operators.
Warehouse inadequacies
Raw material and some finished products warehousing are handled by 3rd party
Logistic company.
The questionnaires and interview results are analyzed. The risk factors are then assessed by using the FMEA approach. The
managers are interviewed again to determine the severity, occurrence, and detection values of each risk factor. Based on the
finalized questionnaires, the RPN and RSV values are calculated. The values can be seen in TABLE II.
TABLE II.
RISK FACTORS IN THE FLAVOR INDUSTRY
Code
Risk Factors
RPN
RSV
Demand Risk
D1
Changes in customer taste
135
15
D2
Demand fluctuation
252
42
D3
Order cancelation
98
14
D4
Substitutive alternative
48
6
240
48
Supply Risk
S1
Raw materials shortage
S2
Supply quality risk
120
24
S3
Procurement risk
120
15
S4
Supplier communication and collaboration failure
75
15
Technology Risk
T1
Infrastructure failure
168
24
T2
Business intelligence
63
9
T3
Failure in IT system
45
15
Environment Risk
E1
Economic downturn
225
45
E2
Natural disaster: flood, earthquake, landslide
90
9
E3
Terrorist attack
70
7
E4
Currency fluctuation
45
9
E5
Pandemic
24
3
© IEOM Society International
1452
Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management
Kuala Lumpur, Malaysia, March 8-10, 2016
Logistics / Operational Risk
L1
Internal quality risk
175
35
L2
Regulatory compliance
80
16
L3
Under-utilized capacity
45
9
L4
Labor unavailability
18
6
L5
Warehouse inadequacies
18
6
To assess which risk factors need to be prioritized, a critical value is assigned to both RPN and RSV. To define the critical
value, 80/20 Pareto Rule is used [16], [17], [18]. The critical value is the product of 80% and the highest value. The highest
value for RPN is 252; the critical value for RPN is 202. The highest value for RSV is 49; the critical value for RSV is 39.
RPN-RSV M atrix
39
250
E1
High
200
RPN
150
E2
E3 T2
D4 E4
L3
100
50
D1
S3
D3
S4L2
S1
202
L1
T1
Low
D2
S2
T3
E5 L5
L4
0
0
10
20
Low
30
RSV
40
High
50
Fig.2. RPN – RSV Matrix
Fig.2. shows that most of the risk factors are located on the bottom-left area of the matrix. Since their RPN and RSV values
are below the critical values, these risks should not be a priority. The risk factors that need to be prioritized in terms of
mitigation strategies are the ones located on the top right of the matrix: demand fluctuation (D2), raw materials shortage (S1),
and economic downturn (E1). These three risk factors have the highest RPN and RSV values among all other risk factors.
© IEOM Society International
1453
Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management
Kuala Lumpur, Malaysia, March 8-10, 2016
B. Risk Mitigation Strategies
The risks involved in the flavor supply chain of the company case study were identified and assessed. The risks should be
treated by determining what will be done in response to the identified risk. The high priority level risks have to be mitigated by
using specific supply chain strategies.
The following risk mitigation strategies were developed in a group discussion between the authors and the supply chainrelated managers of Company X. Company historical data and past risk mitigation strategies were taken into consideration in
the discussion.
The issue of Economic downturn could manage by three mitigation strategies. The first strategy is to expand to the export
market. Recently export market area is South East Asia market will expand out of South East Asia, which have similar taste
flavors. The second strategy is to expand the business segment. The current business segment is the food and beverage
industries. The company could expand to bakery, restaurant, fast food, etc. The third strategy is cost containment. Company
can increase efficiency by value engineering or value analyzing.
Demand fluctuation risks could be managed by three mitigation strategies. The first mitigation strategy is to strengthen
partnership relationship with customers in order to acquire information regarding their future plans, such as new product
launch and market expansion. These pieces of information can be utilized to create better demand forecast. The second strategy
is to improve and enhance MRP and ERP system. The last strategy is to strengthen market research capabilities.
Raw material shortage risks exist because most raw materials are imported from overseas. These risks could be managed by
several mitigation strategies. The first strategy is sourcing from sustainable supplier. The second is to develop strategic
sourcing strategies to manage shorter lead time, competitive price, and sustainable raw material. The last mitigation strategy is
to always have a back up supplier as contingency plan to reduce risk if primary suppliers cannot supply raw materials with the
right quality at the right time.
V.
CONCLUSIONS, RESEARCH LIMITATIONS, AND FUTURE RESEARCH
This research identified and then assessed risks in the flavor supply chain. This research also developed mitigation
strategies for high priority risk factors. The FMEA method was used in this study. FMEA provides guidance in making
prioritization of the risk factors.
This research found that the high priority risk factors for the flavor supply chain are demand fluctuation, raw materials
shortage, and economic downturn. Appropriate mitigation strategies were developed for each of these risk factors.
The results of this study have limited generalization. This research was conducted only at Company X which is a largesized multinational flavor company in Indonesia. Small to medium-sized companies may have different high priority risk
factors and may even have different risk factors. The number of study participant in this research is small because this study
only selects those considered as supply chain experts in Company X as study participants.
Future research can be done by involving larger numbers of study participants from flavor companies of all sizes in
Indonesia. The purpose is to gain more accurate generalization of the research results and to find whether there are differences
in terms of supply chain risk factors between small to medium-sized companies and large companies.
REFERENCES
[1]
[2]
[3]
[4]
[5]
[6]
S. Li, B. Ragu-Nathan, T.S. Ragu-Nathan, and S.S. Rao, “The impact of supply chain management practices on competitive advantage
and organizational performance,” Omega, vol. 34, pp. 107-124, 2006.
G.A. Zsidisin, “A grounded definition of supply risk,” Journal of Purchasing and Supply Management, Vol. 9, pp. 217-224, 2003.
D. Elangovan, G. Sundaraj, S.R. Devadasan, and P. Karuppuswamy, “Development of futuristic supply chain risk management pilot
strategies for achieving loss reduction in manufacuring organisations,” World Journal of Enterpreneurship, Management and
Sustainable Development, Vol. 6(1/2), pp. 39-51, 2011.
C.S. Tang, “Perspectives in supply chain risk management,” International Journal of Production Economics, Vol. 103(2), pp. 451-488,
2006.
M. Karthick and V. Manikandan, “FMEA based Quantification Analysis of Outbound Supplier Risk and its Resilience,” Global
Journal of Researches in Engineering (G), Vol. 14(1), pp. 1-8, 2014.
P.L.S. Miguel and L.A.L. Brito, “Supply Chain Management measurement and its influence on Operational Performance,” Journal of
Operations and Supply Chain Management, Vol. 4(2), pp. 56-70, 2011.
© IEOM Society International
1454
Proceedings of the 2016 International Conference on Industrial Engineering and Operations Management
Kuala Lumpur, Malaysia, March 8-10, 2016
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
A. Agus, “Supply Chain Management, Product Quality and Business Performance,” International Proceedings of Economics
Development and Research, Vol. 10, pp. 98-102, 2011.
C. Harland, R. Brenchley, and H. Walker, “Risk in supply networks,” Journal of Purchasing & Supply Management, Vol. 9, pp. 51-62,
2003.
H. Tohidi, “The role of risk management in IT systems of organizations,” Procedia Computer Science, Vol. 3, pp. 881-887, 2011.
R. Thakore, R. Dave, and T. Parsana, “A Case Study: A Process FMEA Tool to Enhance Quality and Efficiency of Bearing
Manufacturing Industry,” Scholars Journal of Engineering and Technology, Vol. 3(4B), pp. 413-418, 2015.
S. Sharma and R. Pratap, “A Case Study of Risks Prioritization using FMEA Method,” International Journal of Scientific and
Research Publications, Vol. 3(10), pp. 1-4, 2013.
U. Juttner, H. Peck, and M. Christopher, “Supply Chain Risk Management: Outlining an Agenda for Future Research,” International
Journal of Logistics: Research and Applications, Vol. 6(4), pp. 197-210, 2003.
B. Ritchie and C. Brindley, “Supply chain risk management and performance: A guiding framework for future development,”
International Journal of Operations & Production Management, Vol. 27(3), pp. 303-322, 2007.
Y.M. Wang, K.S. Chin, G.K.K. Poon, and J.B. Yang, “Risk evaluation in failure mode and effects analysis using fuzzy weighted
geometric mean,” Expert Systems with Applications, Vol. 36, pp. 1195-1207, 2009.
K.H. Chang, Y.C. Chang, T.C. Wen, and C.H. Cheng, “An Innovative Approach Integrating 2-Tuple and LOWGA operators in
process failure mode and effects analysis,” International Journal of Innovative Computing, Information and Control, Vol. 8(1B), pp.
747-761, 2012.
R.A. Anggara, “Implementation of Risk Management Framework in Supply Chain: A Tale from a Biofuel Company in Indonesia,”
Manchester Business School Working Paper, Number 614, 2011, Available at SSRN: http://ssrn.com/abstract=1763154 or
http://dx.doi.org/10.2139/ssrn.1763154
[17] K.O. Sarpong, O.F. Alexander, and E.K. Anin, “An assessment of supply chain risks in the cocoa industry in the Ashanti region,
Ghana,” International Journal of Humanities and Social Science, Vol. 3(19), pp. 191-201, 2013.
[18] E.K. Anin, O.F. Alexander, and D.E. Adzimah, “Managing supply chain risks: A perspective of exportable pineapple fresh fruits in
Ghana,” European Journal of Business and Management, Vol. 7(3), pp. 59-71, 2015.
[19] A. Norrman and U. Jansson, “Ericcson’s proactive supply chain risk management approach after a serious sub-supplier accident,”
International Journal of Physical Distribution & Logistics Management, Vol. 34(5), pp. 434-456, 2004.
[20] U. Sekaran and R. Bougie, Research Method for Business: A Skill-Building Approach, 6th ed. Chichester, West Sussex: Wiley, 2013.
[21] A. Diabat, K. Govindan, and V.V. Panicker, “Supply chain risk management and its mitigation in a food industry,” International
Journal of Production Research, Vol. 50(11), pp. 3039-3050, 2012.
BIOGRAPHY
Fransisca Dini Ariyanti is a lecturer in the Industrial Engineering Department at Bina Nusantara University, Jakarta, Indonesia. She
earned her Bachelor of Chemical Engineering from Diponegoro University, Indonesia and Master of Industrial Engineering from
University of Indonesia, Indonesia. She has taught supply chain-related courses and published conference and journal papers. Her research
interests include supply chain management, performance management, and quality management.
Aditya Andika is a lecturer in the Industrial Engineering Department at Bina Nusantara University, Jakarta, Indonesia. He earned his
Bachelor of Industrial Engineering from Trisakti University, Indonesia and Master of Business Administration from Gadjah Mada
University, Indonesia. He has taught management-related courses and published conference papers. His research interests include
knowledge management, performance management, and supply chain management.
© IEOM Society International
1455