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This paper aims to examine the impact of a Manufacturing Execution System (MES) on a specific set of Supply Chain performance metrics. MES are intra-company, integrative Supply Chain Information Technology (IT) systems that emerged in the mid-1990s, as a further development of the Computer Integrated Manufacturing (CIM) concepts (Kletti, 2007). There are two core functionalities provided by an MES. Firstly, the integration of corporate-level IT systems with the plant automation systems, and secondly, providing a common platform for the various plant automation systems, which are often heterogeneous legacy systems. The latter is a common situation on global shop floors - leading practitioners to use the term “islands of automation” (Taghipour, 2014; Nagalingam and Lin, 2008; Kletti, 2007).
In his seminal book on MES, Kletti (2007) argues that competition in today’s markets is no longer based on single attributes like pricing or quality, but rather between firms’ business processes. This statement is in line with the Resource-Based View (RBV) of an organization, which postulates that companies who possess and can skilfully utilize “valuable, rare, imperfectly imitable, and not substitutable” (Barney, Wright & Ketchen, 2001, p. 625) resources gain a competitive advantage. Wernerfelt (1984) provided a helpful analogy where he states that a high tree in a low forest gets more sun and, thus, grows faster and stays taller than his “competition”, the lower trees.
Considering the chronological context, SCM's advent coincided with the shift from production-oriented to customer-oriented strategies in the 1960s/70s (Sheth, Sisodia & Sharma, 2000) and the opening of China in the 1980s as the triggering point for globalization (Deng and Moore, 2004). Furthermore, this era saw disruptive IT developments fuelled by increasing computing power at a lower cost and the increasing development of the internet. The latter enabled firms to manage ever-increasing data volumes; thus, the complexity of their global supply networks and to enhance inter-organizational coordination and integration (Prajogo and Olhager, 2012).
The coordination and integration of business processes require adequate coordinates to steer the activities. These coordinates are reflected in performance management frameworks, such as the Supply Chain Operations and Reference (SCOR) model developed by the American Production and Inventory Control Society’s Supply Chain Council. For this research, order lead time, inventory, and logistic costs are the selected performance indicators to that firms with an MES in operation perform better on these specific metrics than firms without an MES. Reduced lead times directly impact customer satisfaction and working capital performance (Cotteleer and Bendoly, 2006); and, therefore, translate into a competitive advantage (Stenberg and Larsson, 2016; Pan and Hsiao, 2005). Logistics costs are a vital indicator for supply chain and company performance (Töyli, Häkkinen, Ojala & Naula, 2008; D’Avanzo et al., 2003; Gunasekaran, Patel & Tirtiroglu, 2001; Fellenz & Brady, 2010) and are a large portion of firms’ Cost of Goods Sold (Thomas and Griffin, 1996). Inventory costs might be the only position on the balance sheet to dwarf logistics costs (Gunasekaran, Patel & Tirtiroglu, 2001). Hence, scholars consider inventory performance (i.e., the reduction of) as positively correlated to a firm’s financial performance (Wagner, Grosse-Ruyken & Erhun, 2012; Li et al., 2006; Christopher and Gattorna, 2005; Ramdas and Spekman, 2000). Inventory distinguishes further into raw material-, work-in-process- and finished goods inventory (Isaksson and Seifert, 2014; Capkun, Hameri & Weiss, 2009).