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Introduction
Supply chain plays significant roles in the domestic and the global economy. Each passing day, business processes, and operating environment are increasingly becoming complex. They hence require attention. This requires an effective supply chain that is able to respond efficiently to disruptions from unexpected events.
Supply chain needs to be streamlined to be more responsive to disruptions from the external environment. This calls for an efficient supply chain risk management. There are many risk management tools that can be utilized in supply chain management to reduce the impact of disruptions in the supply chain.
This paper discusses the risks that are inherent in supply chain. In addition, it provides varied definitions of risk, supply chain management, and supply chain risk management by different authors. Furthermore, it discusses the importance of supply chain management. Risk analysis models are discussed with reference to five articles by different authors. However, the report is constrained by lack of sufficient time in the preparation and submission, as well as the human resource factors.
Reviews of books and Literature
Supply Chain Risk
The supply chain is vulnerable to risks of different levels. There are varieties of definitions of the term “risk”. A risk is an uncertainty with regard to future events that distort a functionality of business operations (Mun, 2004). Manuj and Mentzer (2008) define risk as unpredictable disruptions or breakdowns to the initial objective and projections. Lastly, risk can be defined as uncertainty with regard to events that compromise expected outcomes (Pryke, 2009).
Singh, Mishra, Jain, and Khurana (2012), define supply chain risk as a potential deviation from the planned objectives that cause additional costs on value added activities, at different stages of the supply chain. On the other hand, Wagner and Bode (2008), describe risk as a loss or a damage to supply chain that is caused by disruption of supply chain activities.
Risk can also be defined as an organizational, environmental, or a supply chain related variable that is not easy to predict with certainty. Therefore, it affects the outcomes of supply chain activities (Faisal, Banwet, & Shankar, 2006).
Supply chain risks are classified as internal, or external. The Internal risks arise from improper coordination of supply chain operational activities. These risks include production, distribution, supplies, and demand risks. On the other hand, external risks are factors that occur due to the interaction of the supply chain with the external environment. They include natural disaster risks, exchange rate risks, terrorist attacks, and regulatory risks (Singh, Mishra, Jain & Khurana, 2012; Lin & Zhou, 2011).
These risks are inevitable in supply chains, and hence the high need to manage them. Risks damage and disrupt the efficient performance of supply chains. They can be managed through effective supply chain management strategies (Singh, Mishra, Jain & Khurana, 2012; Lin & Zhou, 2011). More so, supply chain risk analysis is also critical for the internal and external management of risks that are inherent in this field.
Supply Chain Management
Supply Chain Management (SCM) has been addressed widely in the supply chain literature. The term was first coined to differentiate it from logistics management. SCM can be defined as an efficient integration and coordination of supply chain activities with an objective of satisfying the end user (Faisal, Banwet, & Shankar, 2006).
Mentzer et al. (2001) define SCM as a systematic and strategic coordination of business operations across business functions with an objective of enhancing long-term efficiency of supply chains. On the other hand, Hugos (2011) defines SCM as the coordination of key chain activities such as location, production, inventory, and transportation among other activities in supply chains in order to produce the best mix that is efficient and responsive to markets being served by a company.
SCM primary role is to facilitate quick movement of products and services to the end user. SCM creates a flexible and agile organization that supports distribution networks by allowing quick changeovers in the supply chain (Hugos, 2011). In addition, SCM is important in quantifying the bottom-line impacts of supply chain activities, hence enhancing cost controls.
At the same time, SCM enhances company’s competitiveness in the market through eliminations of supply chain bottlenecks. It also helps in the achievement of operational efficiencies and meeting the needs. It enables companies to achieve their objectives (Hugos, 2011).
SCM is a critical tool for businesses. It helps businesses to boost their customer services. This is achieved through a timely delivery of products in different locations.
Furthermore, SCM helps business to streamline supply chain activities and take necessary measures against unexpected occurrences. It also enables businesses to improve their bottom-line through increased efficiencies. Furthermore, the supply chain management enables business to build a sustainable supply chain, and hence enhance improvements in the social and environmental responsibility (Hugos, 2011).
Supply Chain Risk Management
Supply chains are susceptible to risks due to the complex activities and the environment in which businesses operate. Supply Chain Risk Management (SCRM) is critical in combating supply chain risks (Wu et al. 2013). SCRM is defined as the application of risk management process tools in collaboration with partners in the supply chain to mitigate risks and uncertainties that arise as a result of logistics related activities (Norrman & Lindroth, 2002).
Olson and Wu (2008) view SCRM as a coordination and collaboration process that identify, assess, avoid, and mitigate risks that are inherent in supply chain.
SCRMP can also be defined as a management arrangement that addresses the likelihood of risk occurrence, its consequences, and the forces that drive particular sequence of events, as well as how best the forces can be managed to minimize the consequences and improve the positive outcomes (Ritchie & Brindley, 2007). Petroleum Supply Chain risk management model that was developed by Fernandes, Barbosa-Póvoa, and Relvas (2010) give a good example of SCRM.
Supply Chain Risk Analysis
There are various theories and models that are used to analyze supply chain risks. These models are used to identify, analyse, and mitigate risks in different industries. For instance, Christopher, and Peck (2004) research focused on the development of a managerial agenda that would enable identification and management of risks in the supply chain. It utilized chain resilience model in the analysis of risks in different UK industries.
Their analysis provides an end-to-end perspective of product flow from raw material sources to customer delivery. Their research sought to answer the following questions; how best managerial agenda can identify and manage supply chain risks, and how best resilience of supply chain can be improved (Christopher & Peck, 2004).
They model risk decision-making across business functions in and outside of the organization (Christopher & Peck, 2004). Their study is justified by an apparent acknowledgment that organizations in the UK are yet to fully recognize supply chain risks and utilize lean systems for supply chain efficiency.
Khan, Christopher, and Burnes (2008), provide an analysis of the impact of the product design on the SCRM, in a more complex global context case study. Their research constructs a framework that incorporates product design in supply chain risk management. This framework is a creative platform that is capable of managing supply chain risks (Khan, Christopher, & Burnes, 2008).
Its research questions are the roles, which the product design can play in mitigation of risks, and how it enhances supply chain agility in clothing and textile industry in the UK. The Risk Matrix and the Risk Register Models are used by researchers in the analysis of Marks and Spencer risk management. The justification of the research is the recognition of the product design as integral to the competitiveness of a supply chain that is achieved through an effective identification and mitigation of risks (Khan, Christopher, & Burnes, 2008).
Chopra and Sodhi (2004) provide an analysis of supply chain risks as a result of natural disasters. They provide an overview of how companies can be prepared for natural disaster eventualities. They hold an opinion that effective management of natural disaster risks calls for managers to understand the interconnectedness of supply chain risks and focus design of strategies for effective risk reduction and mitigation strategies.
The authors answer the question how best companies can be prepared to deal with risks associated with natural disasters, fires, labour strikes, and terrorism that is likely to disrupt supply chains. They utilize Disaster Management Model and Framework (DMM&F) to analyze and mitigate risks. The justification of the study is the need of strengthening natural disasters, fire, and labour strikes preparedness so as to reduce its impacts on the supply chain.
Vosooghi, Fazli, and Mavi (2012) provide an analysis of risk involved in the crude oil supply chain. They acknowledge that crude oil supply chain is complex and vulnerable to a variety of risks. They identify environmental and regulatory risk to be rampant to the crude oil supply chain.
The research question of this paper is how best oil supply chain managers can understand different risks and how effectively they mitigate them. Fuzzy Analytical Hierarch Process (FAHP) model is utilized in the analysis of the risks involved in the crude oil supply chain (Vosooghi, Fazli, & Mavi, 2012). The justification of this research is making a contribution towards management and mitigation of risks in the crude oil supply chain that is more vulnerable to risks.
The research paper by Sinha, Whitman, and Malzahn (2004) provide a descriptive methodology designed to mitigate risks in an aerospace supply chain. This paper answers the question of how best risks in an interconnected supply chain can be identified, analyzed, and mitigated in the aerospace industry.
The authors utilize Supply Chain Operations Reference model (SCOR) in the analysis of the risks inherent in the aerospace industry. The justification this research was to provide an efficient methodology capable of mitigating supply chain risks in a competitive industry (Sinha, Whitman, & Malzahn, 2004).
Conclusion
Supply chain management and supply chain risk management continue to draw attention of companies and other practitioners. This is due to its role in the performance of the companies and the economy. With globalization increasing competition and business functions becoming more complex, the supply chain is becoming more vulnerable to unexpected disruption.
Effective reduction of the impacts of the dynamic environment on supply chain call for efficient supply chain management and supply chain risk management. There are different risk management tools that organizations should use to tailor their risk management strategies towards effective mitigation of risk. In doing so, supply chain would be more efficient and responsive to environmental disruption, and hence enhances business competitiveness.
List of References
Chopra, S & Sodhi, MS 2004, “Managing risk to avoid supply-chain breakdown,” MIT Sloan Management Review, vol. 46, no. 1, pp. 52-61.
Christopher, M & Peck, H 2004, “Building the resilient supply chain,” International Journal of Logistics Management, vol. 15, no. 2, pp. 1-13.
Faisal, MN, Banwet, DK & Shankar, R 2006, “Supply chain risk mitigation: modelling the enablers,” Business Process Management Journal, vol. 12, no. 4, pp. 535-552.
Fernandes, LJ, Barbosa-Póvoa, AP & Relvas, S 2010, “Risk management framework for the petroleum supply chain”, Computer Aided Chemical Engineering, vol. 28, pp. 157-162.
Hugos, MH 2011, Essentials of supply chain management. Hoboken, N.J: Wiley.
Khan, O, Christopher, M & Burnes, B 2008, “The impact of product design on supply chain risk: a case study,” International Journal of Physical Distribution & Logistics Management, vol. 38, no. 5, pp. 412-432.
Lin, Y & Zhou, L 2011, “The impacts of product design changes on supply chain risk: a case study,” International Journal of Physical Distribution & Logistics Management, vol. 41, no. 2, 162-186.
Manuj, I & Mentzer, JT 2008, “Global supply chain risk management strategies,” International Journal of Physical Distribution & Logistics Management, vol. 38, no. 3, pp. 192-223.
Mentzer, JT, DeWitt, W, Keebler, JS, Min, S, Nix, NW, Smith, CD, & Zacharia, ZG 2001, Defining supply chain management, Journal of Business logistics, vol. 22, no. 2, pp. 1-25.
Mun, J 2004, Applied risk analysis: Moving beyond uncertainty in business, Wiley, Hoboken, N.J.
Norrman, A & Lindroth, R 2002, March, Supply chain risk management: purchasers’ vs planners’ views on sharing capacity investment risks in the telecom industry, In 11th International IPSERA conference, Enschede, The Netherlands.
Olson, DL & Wu, D 2008, “Supply Chain Risk Management,” In New Frontiers in Enterprise Risk Management, pp. 57-67, Springer Berlin Heidelberg.
Pryke, S 2009, Construction supply chain management: Concepts and case studies, Wiley-Blackwell, Chichester, UK.
Ritchie, B & Brindley, C 2007, “Supply chain risk management and performance: a guiding framework for future development,” International Journal of Operations & Production Management, vol. 27, no.3, pp. 303-322.
Singh, A, Mishra, P, Jain, R & Khurana, M 2012, ‘Design of global supply chain network with operational risks’, International Journal Of Advanced Manufacturing Technology, 60, 1-4, pp. 273-290.
Sinha, PR, Whitman, LE & Malzahn, D 2004, “Methodology to mitigate supplier risk in an aerospace supply chain,” Supply Chain Management: An International Journal, vol. 9, no. 2, pp. 154-168.
Vosooghi, MA, Fazli, S & Mavi, RK 2012, “Crude Oil Supply Chain Risk Management with Fuzzy Analytic Hierarchy Process,” American Journal of Scientific Research, No. 46, pp. 34-42.
Wagner, SM & Bode, C 2008, “An empirical examination of supply chain performance along several dimensions of risk”, Journal of Business Logistics, vol. 29 no. 1, pp. 307-325.
Wu, T, Huang, S, Blackhurst, J, Zhang, X, & Wang, S 2013, ‘Supply Chain Risk Management: An Agent-Based Simulation to Study the Impact of Retail Stockouts’, IEEE Transactions On Engineering Management, vol. 60, no. 4, pp. 676-686.
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