Data science skills and domain knowledge requirements in the manufacturing industry: A gap analysis. (July 2021)

• Record Type: Journal Article
• Authors: Li, Guoyan; Yuan, Chenxi; Kamarthi, Sagar; Moghaddam, Mohsen; Jin, Xiaoning
• Is Part Of: Journal of manufacturing systems. Volume 60(2021)
• Page Start: 692
• Page End: 706
• Publication Date: 2021-07
• Subjects: Industry 4.0 -- Labor market analysis -- Skills gap -- Data science; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2021.07.007
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: Industry 4.0 brings changes to the labor market structure and the demand for prospective workforce skills. Identifying gaps in critical skills and domain knowledge is essential for the digital transformation of manufacturing. The paper has identified and ranked gaps in skills and domain knowledge topics in four major technology clusters. Job market data such as job postings and professionals' profiles are used for quantitative analysis of skills gap. Key insights on the trend and opportunities of workforce upskilling and retraining are provided. Abstract: Manufacturing has adopted technologies such as automation, robotics, industrial Internet of Things (IoT), and big data analytics to improve productivity, efficiency, and capabilities in the production environment. Modern manufacturing workers not only need to be adept at the traditional manufacturing technologies but also ought to be trained in the advanced data-rich computer-automated technologies. This study analyzes the data science and analytics (DSA) skills gap in today's manufacturing workforce to identify the critical technical skills and domain knowledge required for data science and intelligent manufacturing-related jobs that are highly in-demand in today's manufacturing industry. The gap analysis conducted in this paper on Emsi job posting and profile data provides insights into the trends in manufacturing jobs that leverage data science, automation, cyber, and sensor technologies. These insights will be helpful for educators and industry to train the next generation manufacturing workforce. The main contribution of this paper includes (1) presenting the overall trend in manufacturing job postings in the U.S., (2) summarizing the critical skills and domain knowledge in demand in the manufacturing sector, (3) summarizing skills and domain knowledge reported by manufacturing job seekers, (4) identifying the gaps between demand and supply of skills and domain knowledge, and (5) recognize opportunities for training and upskilling workforce to address the widening skills and knowledge gap.