Article Preview
TopIntroduction
Contemporary multinationals execute business functions related to long, medium and short-term benefits. These multinationals are commercial entities primarily engaged to generate profits offering value through the manufacture, purchase, sale, and management of products and services. Optimising businesses generates increased outputs, revenues together with ensure business consistency, sustainability, and competitiveness (Balko & SAP, 2013). Business optimization is a collection of measures explored for investigating business conditions, presenting a maximum or minimum value based on a defined response, maximising external and internal productivity (Kim & Chai, 2017; Van Der et al., 2016; Stock & Seliger, 2016). The digital revolutions stimulate a shift in the existing approaches employed in the execution of a business (Ivanov et al., 2018; Trkman et al., 2010). Smart production, a sub-aspect of the digital revolutions related to business execution, describes the global standards employed towards an intelligent production and networked business processes (Zheng et al., 2018; Chen, 2018). This research is specific to configuring and networking sets of logistics business functions, delivering on a real-time digitalised logistics architecture based on global best practice. The logistics architecture aims for integration and global synergies of fundamental logistics business components via 4IR implementations. This delivers strategic, significant and operational business value. This is executed via a global, process-centric, systemic and simulation approach resolving the inter-functional integration and execution of fundamental logistics business components. The effectiveness of business process models in capturing business functions cannot be overstated (Kastalli & Van Looy, 2013). The architecture includes business process optimisation models is sustainable and a shift from the traditional method of business decision support which offers limited capabilities, for predictive enablement, monitoring, and management of a business.
Key value adds of the proposed logistics architecture is presenting a structure, which repositions from current approaches for capturing, reviewing, observing, interconnecting, predicting, quantifying and optimizing a business in real-time. Gartner in one its white paper 2013 publications established a larger percentage of existing businesses will manage business execution based on real-time predictive analysis in years to come. The advent of digital revolution related to facilitating business growth and targets results in businesses exploring diverse corporate best practice initiatives (Kristianto et al., 2017). Contemporary multinationals have employed numerous global optimisation, technology and sustainable initiatives such as the deployment of Enterprise Resource Planning (ERP), Manufacturing Execution System (MES) and Process Control Systems (PCS) for the execution of business functions (Medoh & Telukdarie, 2016). These initiatives and technologies have not effectively been integrated with the emerging 4IR implementations. This limitation is intense within the logistics business domain, where existing architecture presents gaps related to presenting a collaborative and predictive decision support structure via business process optimisation models.