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Supply chain complexity
(2019)
Supply chain management (SCM) is known as a competitive strategy in today’s business. Through increasing product variety, structures and processes, managers struggle with an increase in supply chain complexity (SCC), which leads to a negative influence on a firm’s efficiency in terms of lead times, flexibility and costs. In order to manage complexity, supply chain managers need to know its drivers or define appropriate management measures. However, managers can no longer manage SCC internally. In order to cope with this challenging issue and achieve overall benefits, it is necessary that the complete supply chain is involved in optimising supply chain processes. An aligned supply chain should ensure that supply chain partners benefit from cost savings. At the same time, supply chain processes should be agile to respond to market volatility, while also being cost-efficient to survive in the highly competitive world.
In this dissertation, three research cases are conducted with different focus areas whereby first drivers for internal and external SCC are explored in a single case study. In order to gain a representative overview of relevant drivers, not only interviews with top managers from a manufacturer are held but also with key managers from suppliers and customers. With the interviews held from the upstream to downstream supply chain, this part of the dissertation sheds light on topical SCC drivers and provides some hypotheses for managing detailed and dynamic SCC. With this case, an academic contribution is provided to better understand the relevance of SCC.
In a second step, another qualitative study addresses the requirements of a supply chain. The basis for this part is the triple-A supply chain of Hau Lee (2004), where he states from a theoretical perspective the prerequisites of a supply chain, namely agility, adaptability and alignment. In this dissertation, this approach is reviewed from a managerial perspective. It is analysed which key performance indicators of a firm are affected by the three aforementioned qualities. Finally, it is presented how agility, adaptability and alignment are linked together. In order to gain a common understanding, semi-structured interviews are conducted to extend literature through managerial experience.
In a third step, a quantitative simulation creating a discrete-event simulation model is provided to evaluate inventory and logistics costs’ effects in a company that faces significant SCC. The target is to align the supply chain by changing the existing distribution channel to direct delivery. The result shall demonstrate the financial benefit for the supply chain partners, as well as illustrating the conditions and risks when changing supply chain processes.
This dissertation shows that companies are increasingly faced by SCC. In order to respond flexibly to market volatility, supply chains must be agile to ensure that financial risk shall not alarm a company’s existence. Therefore, it is recommended to align the supply chain with a collaborative supply chain model.
This paper examines the role of uncertainty in the context of the business cycle in the Eurozone. To gain a more granular perspective on uncertainty, the paper decomposes uncertainty along two dimensions: First, we construct the four different moments of uncertainty, including the point estimate, the standard deviation, the skewness and the kurtosis. The second dimension of uncertainty spans along three distinct groups of economic agents, including consumers, corporates and financial markets. Based on this taxonomy, we construct uncertainty indices and assess the impact on real GDP via impulse response functions and further investigate their informational value in rolling out-of-sample GDP forecasts. The analysis lends evidence to the hypothesis that higher uncertainty expressed through the point estimate, a larger standard deviation among confidence estimates, positive skewness and a higher kurtosis are all negatively correlated with the business cycle. The impulse response functions reveal that in particular the first and the second moment of uncertainty cause a permanent effect on GDP with an initial decline and a subsequent overshoot. We find uncertainty in the corporate sector to be the main driver behind this observation, followed by financial markets’ uncertainty whose initial effect on GDP is comparable but receding much faster. While the first two moments of uncertainty improve GDP forecasts significantly, both the skewness and the kurtosis do not augment the forecast quality any further.