An interpretive analysis of influential drivers for control tower adoption in supply chains

Angappa Gunasekaran · Vaibhav S. Narwane

8 citations0/0 files storedSupply Chain Analytics

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Quality and Supply Management Big Data and Business Intelligence Supply Chain Resilience and Risk Management

Abstract

A Supply Chain Control Tower (SCCT) provides real-time information, analytics, and decision support for supply chain management, helping organizations manage disruptions and inefficiencies before they occur. The complexity of contemporary supply chains is characterized by various influential factors that significantly affect the performance of Supply Chain Control Towers (SCCT). Interpreting the interactions among these factors is the key for supply chain managers in their efforts to improve decision quality and performance. Factor analysis is used to identify, prioritize, and rank the influential success factors that help accomplish SCCT effectiveness. This study investigates the influential drivers that shape SCCT adoption by applying Total Interpretive Structural Modeling (TISM) to evaluate how they relate and MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée à un Classement) analysis to determine their relative importance. The results illustrate that SC visibility and transparency are the principal factors, while the sustainable growth strategy is the least important factor influencing SCCT. This study delivers valuable practical understanding to supply chain managers regarding expediting efforts and effectively applying SCCT, ultimately boosting supply chain performance. • Identify key success factors for control tower implementation in supply chains. • Analyze factor relationships using interpretive structural modeling methods. • Highlight visibility and transparency as the most influential control tower driver. • Redevelop a hierarchical model to guide control tower deployment strategies. • Provide practical insights for enhancing decision-making in supply chain operations.

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References

2015Building theory of sustainable manufacturing using total interpretive structural modelling 2018Frugal innovation for supply chain sustainability in SMEs: multi-method research design 2020Use of Proximal Policy Optimization for the Joint Replenishment Problem 2020A Commons for a Supply Chain in the Post‐COVID‐19 Era: The Case for a Reformed Strategic National Stockpile 2020Analysing green human resource management indicators of automotive service sector 2024Analysis of the enablers to deal with the ripple effect in food grain supply chains under disruption: Implications for food security and sustainability 2019A review of operational spare parts service logistics in service control towers 2023Exploring the barriers to ESG adoption using modified TISM approach

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