This paper aims to develop a methodology for designing job roles with a core set of knowledge requirements, skill sets and activities adaptable to different contexts, contributing to job role clarity as a dimension of supply chain visibility.
The study undertook a multi-method approach, including an archival study of over a thousand job adverts, published professional recruitment documents and qualitative analysis of expert focus groups. Detailed data coding was followed by applying Bloom’s taxonomy to establish strategic, tactical and operational knowledge and skills requirements for indicative job roles.
The developed methodology created a framework relating specified job role characteristics, detailing knowledge and activity requirements and training needs. With a core set of evolving identifiers, the job role enabled local adaptation to be accessible at various levels of local, national and international markets.
The methodology was focused on the work of expert teams and would benefit from the addition of a data-driven component based on machine learning technologies.
The five-step methodological approach leads to a framework for determining job role requirements, applicable in different contexts and situations across a supply chain, using a standard template to enhance visibility to all participants. The framework reduces job ambiguity while contributing to supply chain visibility by clarifying job roles, and identifying requirements and training needs for each defined job role.
The value gained from using the developed methodology is that SCM managers and departments can work closely with HR departments to understand the primary skills, knowledge gaps and training necessities. The benefit is gained by the individual, the organisation and the specific sector with comparable job roles to provide consistency for recruitment requirements, pay scales and remuneration and training and education requirements across and between supply chains.
