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Supply Chain Management and Associated Risks

Potential Disruptors of a Supply Chain

When defining the factors that are most likely to cause a disruption in the supply chain management (SCM) process, one must mention that these factors can be split into two large categories, i.e., the external and the internal ones. The internal factors are typically restricted to a poor design of the logistic strategy and the inconsistencies in the communication process.

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In their turn, the external ones are enhanced by changes in political, economic, and natural environments. Specifically, the problems such as terrorist activities, natural disasters, and labor-related issues deserve to be mentioned at the top of the list (Skipper & Hanna, 2009, p. 405). Therefore, the internal factors can be interpreted as changeable, whereas the external ones cannot be altered.

Contributors to Flexibility

Flexibility is an essential quality of a supply chain that allows the latter to be resilient to a range of external factors that may affect the company’s operations in a negative manner. According to Skipper and Hanna’s study findings, information technology and collaboration are considered to be the key contributors to the promotion of flexibility in a company’s framework (Skipper & Hanna, 2009).

To be more exact, the incorporation of the latest IT tools creates premises for the active use of contingency in the process of planning. As a result, the slightest chances at facing risks can be identified and addressed correspondingly.

Collaboration, in its turn, presupposes that the staff members should work independently yet coordinate their actions so that the production process should not be disrupted and the information transfer should occur at a fast speed. Therefore, the specified elements can be viewed as an integral part of building flexibility of the SCM process.

Multiple Linear Regression Model: Measuring Flexibility

Although flexibility is an abstract concept, there are ways to measure it; moreover, identifying flexibility rates in a company is crucial to the location of the possible issues that the firm may be facing soon. Additionally, the outcomes of flexibility evaluation can be used as the means of informing the further strategy of the organization in terms of the choice of the SCM approach.

Flexibility can be measured with the help of the Multiple Linear Regression Model (MRM). Defined as an improvement of the traditional single-factor linear regression model, the given tool helps assess the effect of several independent variables on the dependent one (Sengupta & Datta, 2014).

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Since the flexibility of a company depends on several factors, including the external and the internal ones, it is necessary to use the MRM tool to facilitate a detailed and accurate analysis.

Process of Contingency Planning

The tools for enhancing the flexibility of an organization are very numerous, and contingency planning is one of them. Skipper and Hanna (2009) define the phenomenon of contingency planning as a “strategic planning tool” (p. 406) that helps arrange the steps to be taken to achieve a particular objective. Specifically, the tool in question locates the areas that may serve as a breeding ground for risks in the future, therefore, informing the risk management strategies adopted by the company.

The location of the organization’s assets that are vulnerable to the outside factors is the first step of contingency planning. Afterward, the assets mentioned above are prioritized according to their significance. Finally, the means of safeguarding these assets are identified (Skipper & Hanna, 2009). Thus, the organization’s security strategy is reinforced.

Reference List

Sengupta, S., & Datta, R. (2014). Identification of demand forecasting model considering key factors in the context of healthcare products. International Journal of Application or Innovation in Engineering & Management (IJAIEM), 3(3), 365–369.

Skipper, J. B., & Hanna, J. B. (2009). Minimizing supply chain disruption risk through enhanced flexibility. International Journal of Physical Distribution & Logistics Management, 39(5), pp. 404-427.

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