Barriers to big data analytics in manufacturing supply chains: A case study from Bangladesh

Abstract

Recently, big data (BD) has attracted researchers and practitioners due to its potential usefulness in decision-making processes. Big data analytics (BDA) is becoming increasingly popular among manufacturing companies as it helps gain insights and make decisions based on BD. However, there many barriers to the adoption of BDA in manufacturing supply chains. It is therefore necessary for manufacturing companies to identify and examine the nature of each barrier. Previous studies have mostly built conceptual frameworks for BDA in a given situation and have ignored examining the nature of the barriers to BDA. Due to the significance of both BD and BDA, this research aims to identify and examine the critical barriers to the adoption of BDA in manufacturing supply chains in the context of Bangladesh. This research explores the existing body of knowledge by examining these barriers using a Delphi-based analytic hierarchy process (AHP). Data were obtained from five Bangladeshi manufacturing companies. The findings of this research are as follows: i) data-related barriers are most important, ii) technology-related barriers are second, and iii) the five most important components of these barriers are a) lack of infrastructure, b) complexity of data integration, c) data privacy, d) lack of availability of BDA tools and e) high cost of investment. The findings can assist industrial managers to understand the actual nature of the barriers and potential benefits of using BDA and to make policy regarding BDA adoption in manufacturing supply chains. A sensitivity analysis was carried out to justify the robustness of the barrier rankings.

The Impact of Big Data Analytics on Company Performance in Supply Chain Management

“…In previous studies of specialists, numerous benefits related to SCM information technology (IT) optimization have been identified, such as (1) the exchange of information between SC stakeholders [57][58][59][60]; (2) the transformation of intra-and inter-organizational business processes (cancellation, redesign, automation) [61][62][63], operational efficiency [64] and revenue growth [59], profitability, and improvement of stakeholder relations [65,66]; and (3) improving relational and contractual governance by effectively mitigating the opportunism of partners [67]. In addition, BDA could also generate future opportunities for stakeholders such as obtaining a competitive advantage [68] and reducing exposure to fraud or other malfunctions [69,70].…”

“…With regard to expertise and investment barriers, specialist studies have shown interesting aspects of BDA in SCM: (1) a lack of qualified IT staff and high investment cost [72,73]; and (2) a lack of funds and facilities for research and development of BDA instruments [70]. Data barriers have highlighted interesting aspects of the implementation of BDA in SCM, such as: (1) complexity of data integration and data quality [72,73,76]; and (2) data security, confidentiality, performance, and scalability [72,73].…”

Exploring Challenges to Implementation of IT Service Management System ISO 20000: Implications in Managing Big Data in Emerging Economy

“…Kakouris [33] [36] found that technology-related barriers are significant barriers to big data analytics in manufacturing supply chains. In [37], it was reported that a lack of technological infrastructure is the most significant challenge to implement Industry 4.0 in the leather industries of Bangladesh.…”

Application of fuzzy analytic hierarchy process (FAHP) in failure investigation of knowledge-based business plans

“…As discussed, the prioritization process should be conducted using a MCDM technique. There are different approaches which can be considered to rank/select alternatives using numerous decision making criteria [39]. These approaches include deterministic and stochastic methods which might be applied with regard to the nature of the considered problem.…”