Investigation of capillary tools to reinforce the decision-making capabilities for transforming SCM into smart supply chain management (SSCM)

Purpose In the present study, a group of capillary tools are presented with the purpose to reinforce the decision-making (DM) capabilities of supply chain management (SCM) and to transform SCM into smart supply chain management (SSCM). Here, a bunch of DM tools are presented that can assist in providing thinking capabilities to multiple segments of the activities of supply chains (SCs). Design/methodology/approach In this study, the literature review is considered as a research methodology, where the main thrust of the methodology is to determine the capillary tools for SSCM design based foundation for reinforcing SCM activities. The study mapped the existing literature knowledge related with DM tools to present a surface picture of capillary tools that can provide self-thinking capabilities and DM power to SCM. In this study, a thorough investigation is presented to interpret the overall pictorial representation of SCM assets that can be managed by DM tools. Findings The findings of the study have admired the utility of various support tools, i.e. agent-based system (ABS), the genetic algorithm (GA), an expert system (ES), artificial neural network (ANN) system, big data (BD) techniques, deep learning and natural language processing (NLP) prominent to be implicated for handling and maintaining the diverse SCM activities. The study has described support tools that can be implemented under the domain of SCM to import self-thinking capabilities, induce decision-making power for SSCM, create alerts, inform companies about state of mismanagement, forecast true need of concerns and to lead in evading SC troubles. Originality/value The study originally presented SCM-related activities and mapped the appropriateness of capillary tool to be used to create an understand-ability about the importance of capillary tools for managerial solutions. The study originally provided a widespread impression of diverse DM capillary tools that can be used to handle widespread stream of SCM activities to make it more sustainable. In this study, discussions pertaining to various support tools are presented for estimating their potential and implementation in handling the accurate SCM activity, and the arguments are presented for building SSCM designs based on the need of capillary tool to handle SCM activity.