Impacts of Reshoring on the Organization and Its Supply Chain Network

This section aims to aims to analyze the possible impacts of reshoring on the organization and its supply chain network. First, the role of the organizational, situational, and industrial context on the impact will be examined, before moving on to discuss the overall impact of the supply chain network by considering the three main drivers discussed earlier. It is important to note that the aforementioned drivers motivating re-shoring activities are generally theoretically supported based on current data and future predictions of the likelihood state of the factors considered. However given that research into such strategies is relatively new and context-related, empirical evidence analyzing the likely impact of re-shoring activities against these drivers is fairly limited (Foerstl, 2016). Most literature studied examines not the actual results, but rather suggests frameworks allowing for their measurement. Given that re-shoring is merely a location decision (Gray, 2013), our analysis of the impact will be not only based on literature related to re-shoring, but also on other location-decision frameworks and practices.

In order to appropriately measure the impact of re-shoring on the supply chain network, it is crucial to analyze the several factors at play that will determine whether or not the re-shoring decision should be made in the first place. Factors such as product quality, cost, size, and shipping requirements should be analyzed and plot against the different shoring options’ capabilities (Tate, 2013). Given the ongoing advancements in technology and the fact that most original off-shoring decisions due to cheaper labor costs, innovation in technology can offset the high level of costs associated with the “home” country. For example, Disney is developing 3D printed lighting for interactive toys, and claims that in the future, final products will be produced increasingly through 3D printing, transitioning from labor-intensive processes to capital-intensive. (The Economist, ND) In the table below, Kent (2013) groups factors into 3 parts: product characteristics, cost drivers, and future trends and suggests that these need to be weighed in to capture the potential impact of reshoring on the supply chain network:

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As for the assessment of these factors in the reshoring decision making process, Tate et al (2013) suggest that a key aspect is that of scenario planning, “which considers the impact of alternative futures on long-term decisions.” In many offshoring cases, only focusing on low unit costs reflected negatively on the total costs, and hence appropriate cost models should be developed that consider different scenarios under a range of variables, as well as aggregate costs incorporating elements such as lead time and transportation. Finally, Tate et al (2013) proposes that managers need to understand how these issues affect the choice of location, as well as the likeliness of their occurrence. Gray (2013) proposes several assertions for further research related to re-shoring, among these assertions is the consideration of the original outsourcing practices as re-shoring can only be pursued if offshoring was carried out in the first place, highlighting the link between the two practices.

This section aims to identify any potential impacts on the supply chain network resulting from re-shoring practices. It is written based on the assumption that the assessment of the aforementioned factors, scenario planning, and cost model yielded results that show it is indeed efficient for the organization to re-shore back to it’s home country.

(Juliette’s Part on SC RISK)

One of the main positive impacts of re-shoring is flexibility enhancement. (W.L Tate) states that management of innovation and product changes are easier in a shortened supply chain, this is due to the decrease in the geographical distance, lack of cultural and language barriers, as well as clearer and more direct communication channels across the supply chain. Moreover, Williamson (2012) suggests that locating manufacturing closer to the end consumer is associated with faster response time and leaner supply chain. This will allow for increased agility and quicker responsiveness to consumers tastes and market trends through product design, as well as more efficient delivery times.  In addition, lean production allows for more efficient inventory management and practices such as JIT and hence can lead to decreased inventory and utility costs (Shih, 2014). Moreover, quality control and assurance can be enhanced through improved communication and closer supervision across the shorter supply chain, further increasing perceived customer expectations.

A practical application is the case of LED lightning maker NeuTex, in which production was moved to Houston, Texas after years of production in China. According to its founder, it now spends 30% more on its labor, however factoring in shorter shipping time, fewer defects, and increased automation, the overall additional costs of manufacturing in the United States fell to 4%, which is offset by increased demand due to improved perceived customer expectations as the product is now ‘Made in the USA’.  (Neutex Lighting, 2011).

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