Performance- and value-oriented decision support for supply chain configuration

Abstract

The task of supply chain (SC) configuration is to establish a product-specific SC for new products. Apart from cross-regional network aspects and inter-disciplinary factors, the problem complexity is driven by dynamics and uncertainties of short product life cycles. SC configuration affects SC performance and value creation. Hence, resulting impacts have to be measured and compared under consideration of dynamics and uncertainties. In the conceptual part of this paper, dynamics and uncertainties of SC configuration are integrated into a conceptual framework for value-based supply chain management. In the modelbased part of this paper, this framework is linked to a discrete-event simulation model. The performance outcomes and value impacts of SC configuration options are empirically assessed in a case study of a fast-moving consumer goods manufacturer. The shortfalls of costfocused decision-making without consideration of capitalrelated factors and non-financial aspects are illustrated.

Low carbon supply chain configuration for a new product – a goal programming approach

“…A case study research is executed in five steps (Stuart et al 2002): (i) research question definition, (ii) instrument development, (iii) data gathering, (iv) data analysis and (v) dissemination. The case example builds on a realistic project for a new product of a global FMCG manufacturer (Brandenburg and Schilling 2012;Brandenburg et al 2014b;Schilling, Kuhn, and Brandenburg 2010) and elaborates on three research questions: Downloaded by [Imperial College London Library] at 10:50 06 April 2015…”

“…The deterministic approaches are based on comparably sophisticated solution approaches such as dynamic programming (Graves and Willems 2005), MINLP (Amini and Li 2011) or a problem-specific solution algorithm (Chauhan, Nagi, and Proth 2004). Most of the stochastic models reflect demand uncertainties, either by MILP-based optimisation (Pan and Nagi 2010;Butler, Ammons, and Sokol 2006;Wang, Lai, and Shi 2011) or by simulation models (Brandenburg and Schilling 2012;Brandenburg et al 2014b;Higuchi and Troutt 2004;Schilling, Kuhn, and Brandenburg 2010). Higuchi and Troutt (2004) employ system dynamics (SD) to show that a misestimated market potential can lead to capacity bottlenecks and sales losses, while an overestimated PLC length can result in unprofitable capacity extensions.…”

“…Schilling, Kuhn, and Brandenburg (2010) illustrate the advantages of sophisticated solution approaches over more simple ones as the example of an FMCG manufacturer. Based on this case example, Brandenburg and Schilling (2012) and Brandenburg et al (2014b) exemplify that SC configuration decisions should be based on cash flow and company value that is created over the whole PLC rather than on a static cost comparison.…”

How do different supply chain configuration settings impact on performance trade-offs?

“…Using a case study to reflect on how to employ product and process architectures as an equivalent to the value chain, they propose five domains for the value chain architecture. Brandenburg et al (2014) propose a conceptual framework for the design of value-based supply chains, in addition to assessing the performance outcomes and impact of supply chain configuration on value creation.…”

“…The supply chain configuration's importance arises from its impact on supply chain decisions and accordingly on the performance, which is the reason behind various studies analysing the configuration. For example, Meixell and Gargeya (2005) explore different configurations of global supply chains; Cagliano et al (2008) define clusters of global and local supply chains; von Haartman (2012) examines Fisher's (1997) model and highlights that the level of innovation and technological maturity are more complex phenomena that influence supply chain design; Caniato et al (2013) develop four configuration archetypes based on the level of outsourcing and the location of manufacturing and sales points; Farahani et al (2014) scrutinise supply chain network competitive design in various industries with different contextual factors to identify a framework for competitive network design; Dubey et al (2015) propose a design for supply chain networks with respect to the sustainability and responsiveness dimensions; and other studies (see e.g., Brandenburg et al, 2014;Holweg and Helo, 2014) develop a supply chain network design based on maximising value creation. The configuration constituents are defined in many studies, predominantly as entities (e.g., supplier, manufacturer or distributor), the size and geographical location of these entities, the relationships between them, the information flow, the supply chain structure and the organisational structure (Randall and Ulrich, 2001;Min and Zhou, 2002;Tang, 2006;Chandra and Grabis, 2007;Srai and Gregory, 2008;Marsillac and Roh, 2014).…”