Big Data Future Influence on Global Supply Chain

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Big Data Future Influence on Global Supply Chain

Abstract

The main focus of the report was to determine the influence of big data on the global supply chain in the future. The report examined literature and undertook a SWOT analysis on the use of big data in the global supply chain. Essentially, the findings indicate that the strengths of big data are they drive contextual intelligence, promote collaboration, and enhance the development of complex supply chain. The opportunities presented by big data are effective market analysis, promotion of the use of technology in business, and growth of the big data industry in the global supply chain. However, the weaknesses are the existence of limited experience and expertise, inherent failure of technological systems, and inapplicability in new startups that have no secondary data. The monopoly of big data and privacy concerns are some of the issues that threaten the use of big data in the global supply chain. Therefore, the recommendation is that the global supply chain should utilize big data because it has immense benefits and opportunities.

Overview of the Forum

Analysis of the global supply chain indicates that it is a massive network that allows manufacturers and suppliers to distribute products to consumers via diverse distribution centers, warehouses, and stores. The distribution of products is dependent on logistics operations that manufacturers and suppliers have chosen. Fundamentally, the choice of logistics operations is dependent on the information obtained from the global supply chain. In this view, big data provide information that is essential to the design of logistics operations. Wang et al. report that big data offers important information, such as market trends, purchasing behavior of customers, supply chain trends, and consumer needs, for the global chain supply to make appropriate adjustments (98). Thus, big data has numerous benefits to the global supply chain as it provides the required information.

Introduction

The evolution of technology has enhanced and hastened the process of data collection across the world resulting in the generation of big data. As the global supply chain requires information to understand market trends and distribution of products, they analyze big data and utilize information generated in making evidence-based decisions, which are effective in revolutionizing logistics operations. As big data grow each time, and there is increasing utilization in organizations, the question is how will the big data influence the global supply chain in the future? Essentially, the use of big data in the global supply chain has some benefits and setbacks, which requires critical analysis for the management to leverage and optimize the effectiveness of the global supply chain. Therefore, the report examines the literature review, undertakes SWOT analysis, and provides recommendations regarding how big data will influence the global supply chain in the future.

Literature Review

Given that big data has marked influence on the global supply chain, ample literature exists. The supply chain management experiences numerous challenges and encounters diverse opportunities in the production and utilization of big data in the global logistics industry. In their study, Zhong et al. observed that collection, storage, transmission, processing, utilization, and interpretation of data pose some of the challenges and present opportunities that exist in the future use of big data in service and manufacturing supply chain management (SM-SCM) (586). The challenges exist because the effective use of big data requires the application of technology. Moreover, the use of bid data presents massive opportunities for SM-SCM can utilize information generated in making evidence-based decisions. Zhong et al. recommend the application of the advanced tool in the analysis of big data, extraction of information, and effective decision-making (590). Therefore, it is evident that technology plays a central role in the analysis of big data, extraction of information, and effective decision making in the global supply chain.

Increasing the production of big data in the global supply chain has led to the emergence of big data business analytics, which allows businesses to analyze and utilize data in improving their strategies and operations. Wang et al. explain that big data refers to the aspects of volume, velocity, and variety in data processing while business analytics involves interpretation of data and utilization in decision-making (101). So, the emergence of big data business analytics has improved decision-making among organizations and logistics and supply chain management (LSCM). Supply chain analytics (SCA) is a form of business analytics that is applicable in LSCM and aids in enhancing logistics operations in the global chain supply. Wang et al. found out that SCA is beneficial to the global supply chain for it enables organizations to measure their performance, benchmark operations for value-addition, and optimize business operations (108). Hence, as an aspect of big data, business analytics and supply chain analytics are critical for the achievement of the benefits of the global supply chain.

The growth of data in various sectors of business has resulted in the emergence of the big data industry. The technology has hastened collection, analysis, and interpretation of data across the world, and thus, contributed significantly to the growth of data. A qualitative study undertaken to examine development trends of big data industry in Taiwan revealed that big data is in the formative stages, which requires effective collection and utilization of data to bridge Taiwans businesses to international markets (Weng and Lin 210). In this view, the use of innovative technologies and equipment are opportunities available for the growth of Taiwans big data industry. According to Ittmann, big data improves the performance and competitiveness of the global supply chain because it hastens decision-making and enables optimization of operations (2). Therefore, the literature review shows that big data have enormous potential in shaping the future of the global supply chain.

Analysis and Discussion

Strengths and Opportunities

SWOT analysis of bid data indicates that it has numerous strengths and opportunities as well as weaknesses and threats in the global supply chain. The ability of big data to drive contextual intelligence is strength for it allows the global supply chain to utilize the data it generates and provides critical information. The big data industry constantly receives data from various organizations and supply chains. Effective analysis and interpretation of the data drive contextual intelligence since it provides vital information to organizations and the global supply chain. As a strength, big data promotes collaboration among diverse supply chain networks for shared knowledge and intelligence act as linkages. Research data obtained from diverse markets enables suppliers and manufacturers to meet customer needs, and thus, collaborate in the global supply chain. The ability of big data to support the development of more complex supply chain networks is strength since they permit globalization of the supply chain. The development of complex networks of the supply chain promotes collaboration and sharing of knowledge across diverse networks comprising the global chain. Thus, the big data forms the basis of creating the global networks of the supply chain that allows collaboration, sharing of knowledge, and the creation of robust networks that span global jurisdictions.

Big data present numerous opportunities for the growth and development of the global supply chain. An important opportunity that big data presents is the market analysis of trends in various regions of the world (Itmann 2). Given that big data comprise customer needs, purchasing power, and preferences, these forms of data present opportunity for suppliers and manufacturers to understand their customers and make appropriate adjustments on their products to boost their market share. Another opportunity that big data presents is the use of technology in decision-making and optimization of operations in the supply chain. According to Chen et al., information technology, powerful computers, and personal electronic devices have made it possible for businesses to undertake an accurate and valid analysis of data for effective decisions (1173). Hence, technology allows businesses to utilize big data in data analytics and boost performance. Other opportunities for growth are data collection, storage, transmission, analysis, management, and interpretation, which are integral aspects essential for the growth of the big data industry (Zhong et al. 586). The growth of the big data industry promotes data analytics and the growth of the global supply chain through collaboration and sharing of knowledge.

Weaknesses and Threats

However, despite the strengths and opportunities, big data have weaknesses and threats, which reduce its influence in the global supply chain. Weng and Lin note that big data have weaknesses because there are limited experience and expertise in the analysis and utilization of data by various organizations and diverse supply chain networks (208). In this view, the global supply chain would not be able to reap optimal benefits from big data due to the complicated and sophisticated analysis required. As big data relies on information technology, the inherent failure of technological systems is another weakness. The failure prevents or compels organizations or supply chain networks to make inaccurate decisions resulting in huge losses (Nedelcu 17). The fact that big data is secondary data is a weakness because they do not promote new startups, which have not big data.

A threat to the use of big data in the global supply chain is the monopoly and standardization of data by big companies (Weng and Lin 208). Since big companies can monopolize data, they develop standards that favor them so that they could commercialize the data. Consequently, small companies would be unable to access big data and utilize in generating information of interest. Another threat to the use of big data is the infringement of the privacy of customers. Some legal jurisdictions consider the collection and utilization of big data as illegal and tantamount to the infringement of customers privacy (Nedelcu 18). Thus, the use of big data in the future is dependent on the state of monopoly and ethical address of privacy issues.

Conclusion

In a bid to elucidate the role of big data in the global supply chain, the study examined literature and performed a SWOT analysis of big data. The findings of the study provided robust findings showing that strengths and opportunities of big data outweigh weaknesses and threats. As for strengths, big data generate contextual intelligence, support collaboration, and augment the development of intricate supply chain. As opportunities, big data improve market analysis, promote the use of technology, and support the growth of the big data industry in the global supply chain. Nevertheless, limited experience and expertise, inherent failure of technological systems, and inapplicability to new startups are some of the weaknesses of big data. The issues of monopoly and privacy infringement are some of the threats of big data. In this view, the study recommends the use of big data in the global supply chain because they have immense benefits and opportunities.

Works Cited

Chen, Hsinchun, Roger Chiang, and Veda Storey. Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, vol. 36, no. 4, pp. 1165-1188.

Ittmann, W. The Impact of Big Data and Business Analytics on Supply Chain Management. Journal of Transport and Supply Chain Management, vol. 9, no. 1, 2015, pp. 1-9.

Nedelcu, Bogdan. About Big Data and Its Challenges and Benefits in Manufacturing. Database Systems Journal, vol. 4, no. 3, 2013, pp. 10-19.

Wang, Gang, Angappa Gunasekaran, Eric Ngai, and Thanos Papadopoulos. Big Data Analytics in Logistics and Supply Chain Management: Certain Investigations for

Research and Applications. International Journal of Production Economics, vol. 176, nol.1, 2016, pp. 98-110.

Weng, Wei-Hsiu, and Woo-Tsong Lin. Development Trends and Strategy Planning in Big Data Industry. Contemporary Management Research, vol. 10, no. 3, 2014, pp. 205-213.

Zhong, Ray, Stephen Newman, George Huang, and Shulin Lan. Big Data for Supply Chain Management in the Service and manufacturing Sectors: Challenges, Opportunities, and Future Perspectives. Computers & Industrial Engineering, vol. 101, no. 1, 2016, pp. 572-591.

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