Full length articleBig data analytics as an operational excellence approach to enhance sustainable supply chain performance
Introduction
Operations management as a discipline emphasizes planning and configurations of resources to achieve organizational outcomes, especially in engineering and management sciences. The synchronization between operational activities (internal) and supply chain management (external) activities is indispensable to ensure enduring supply chain performance. Supply chain managers carefully benchmark their operational performance (Lun, 2011; Zhou and Zhou, 2015; Hu et al., 2019; Mangla et al., 2019; Taelman et al., 2019). However, contemporary supply chains are exposed to dynamic business environments with high levels of uncertainties (Ahmadi et al., 2017; Bag, 2017; Bag et al., 2018; Bag et al., 2019). In response to uncertainty, rather than develop resources, firms focus on the development of dynamic capabilities to mitigate risks (e.g., a loss of reputation) and build competitive advantages. The concern with risks is particularly relevant now as the environmental impact from firms’ activities can lead to reputational and financial risks for failing to meet sustainability objectives (Wood et al., 2018).
Big data analytics (BDA) tools may support significant business benefits and drive organizational improvements (Gunasekaran et al., 2017). In general, big data is characterized by 5 Vs (viz., volume, veracity, variety, velocity, and value) (Tao et al., 2018). BDA elicits two major viewpoints to achieve the operational excellence of the organizations. First, the collection of big data (BD) from the firm and external environment. This type of data suggests high volume and velocity of processing data that can provide many improvements and benefits when compared with the existing form of traditional data processing systems (Frank et al., 2019). Second, the use of BD in business analytics (BA) to inform decisions and manage operations. BA consists of capabilities and the potential to assess the strategic move of organizations to attain successful planning of businesses of the organizations. The strategic improvements available through BA (such as forecasting, statistical, and operational analysis via optimization techniques) significantly contribute to the enhanced operational efficiency (Mathivathanan et al., 2018; Chams and García-Blandón, 2019). The combination of these two aspects results in a comprehensive concept of big data analytics (BDA). BDA not only benefits organizations with an enhanced competitive advantage but also results in correct and timely decisions. Improved competitiveness often rests on the gains in operational efficiency and appropriate decisions made by the organizations (Olugu et al., 2011; Hazen et al., 2014). Corporations widely recognize the importance of the BDA phenomenon as it contributes to the strategic objectives of the organizations. It is nonetheless pertinent to mention the importance of strategic planning towards the operational efficiency of the organizations as this supports and enhances the supply chain sustainability performance (Singh et al., 2019). Supply chain management constitutes a necessary process in the overall efficiency of the organizations. The consideration of BDA and the connection within a range of operational and supply chain practices (such as procurement, inventory, logistical, and planning activities) is gaining popularity (Wang et al., 2016; Gong et al., 2018). The overall business or financial performance can be effectively addressed by applying BDA to supply chain management processes of organizations (Lin et al., 2018).
This research explores BDA to enhance sustainable supply chain performance within the South African mining sector. The context is important as mining resources are considered the backbone of this continent, and the activities have environmental consequences. The workforce also suggests social effects of mining decisions as the industry depends on a large workforce. Due to the ethnic composition of the workforce, black economic empowerment (BEE), which has evolved into the broad-based black economic empowerment (BBBEE) scorecard, has become an increasingly crucial managerial factor for workforce the skill development initiatives. The preservation of the mining industry and its resources becomes even more critical because it is one of the fastest-growing sectors in South Africa. However, the advent of technology is posing severe challenges for this industry. Mining companies are developing dynamic capabilities at two levels in ways that enhance the sustainable outcomes from their operations. Dynamic capabilities and sustainability performance improvements occur at the business process level and during the management of organizational resources (Braganza et al., 2017; Dubey et al., 2013). Business process management aims to optimize the structure, functions, and organizational elements (Samaranayake, 2009). Every mining company can potentially optimize their sales order process cycle, procurement process cycle, manufacturing execution cycle, and logistics process cycle (Yadav and Desai, 2016; Yadav et al., 2017; Yadav and Desai, 2017; Yadav et al., 2018a, b). Business process optimization can save significant funds and reduce lead times resulting in enhanced customer satisfaction levels. It also plays an instrumental role in conserving scarce natural resources to improve sustainable outcomes (Powers, 1989; Wu and Dunn, 1995; Glenn Richey et al., 2005; Ghadimi et al., 2019).
This research is important as it explores how operational activities and workforce capabilities support BDA in enhancing operational and sustainable outcomes. Unstructured data generated from social media, mobile devices, machines, and sensors provide valuable business insights (Wamba et al., 2017). BDA can be used to enable plant automation in this age of fourth industrial revolution (Tseng et al., 2018; Telukdarie et al., 2018). However, existing literature fails to explain how BDA capabilities can influence the innovative green product development and employee development and further impact on innovation and learning performance, which is the foundation of sustainable supply chains in connection to the mining industry in South Africa. Hence, the principal objective is to explore how BDA enhances supply chain management performance when operational excellence is emphasized. To address this objective, this study aims to answer two key research questions: RQ1 Do BDA capabilities (management and talent) affect sustainable supply chain performance to attain operational excellence? RQ2 Does supply chain innovativeness moderately affect the sustainability of supply chain performance for operational excellence?
The rest of the article is organized as follows. We present the literature review with a particular focus on sustainable components of supply chains and the development of our hypotheses. We then present the research design, the survey structure and sampling, and statistical analysis and the results. The final sections present the results in context and explain the relevance to past studies before we draw the conclusions and the subsequent managerial implications.
Section snippets
Literature review
Operational excellence in an organization is the foundation for success in other functions. With respect to the day-to-day requirements of the customers, as end-users of every product and service, operations management stands responsible for interaction with all other concerned people and departments. Management of operations is also affected by various technological evolvements, including BDA. Similarly, supply chain management performance is not an exception but is the external extension of
Conceptual framework and hypothesis development
The preceding section extensively explains the theoretical base for our study. We developed a conceptual framework based on the review of the literature and objectives of the study. The dynamic capability view forms the theoretical basis for our study and model (Fig. 1).
The definition of dynamic capabilities from Augier and Teece (2009, p. 412) is “the ability to sense and then seize new opportunities, and to reconfigure and protect knowledge assets, competencies, and complementary assets with
Research methods
To address the research questions, we opted to use a statistical survey and structural equation modeling. The approach enables us to test hypothesized relationships and moderation simultaneously. The research team used established processes to develop the survey items following the literature review and discussion with five mining industry executives having more than ten years of work experience. The scales are drawn from established research and were selected to ensure reliability and validity
Data analysis
We used the variance-based Partial Least Squares Structural Equation Modelling (PLS-SEM) approach to analyze the data. This is a multivariate data analysis approach that enables the simultaneous examination of multiple relationships among many variables, including latent variables. PLS-SEM is appropriate for exploratory analysis of relationships as it maximizes R2 for the endogenous constructs, minimizes unexplained variance, supporting superior theoretical model development. Therefore, PLS-SEM
Discussion
The present study is based on the assumption that operational excellence is one of the major requirements for an organization. The sustainable existence of the organizations seems difficult as every activity revolves around the fact of how operational activities are being carried out. The shared work aimed to investigate whether BDA can enhance sustainable supply chain performance of organizations and develops an improved understanding of implementation pathways. The research team developed a
Conclusion
In this paper, we provide evidence for the positive association between BDA talent capability and employee development. Our results suggest a connection between the employee development and human capital of the organization and the sustainable supply chain outcomes. Product innovation not only leads to the development of employees but also enhances their performance and the level of innovation. Managers can optimize the performance of their employees by encouraging a learning environment. The
Funding
The work of Lei XU was supported in part by National Natural Science Foundation of China (Grant No. 71672125), major research project of National Natural Science Foundation of China (Grant No. 91646117).
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