From Efficiency to Resilience Advantage: System Shift as a Structural Diagnostic Framework for Manufacturing Continuity in a Pharmaceutical Manufacturing Group
DOI:
https://doi.org/10.55324/ijoms.v5i11.1307Keywords:
System Shift, manufacturing resilience, pharmaceutical manufacturing, bottleneck severity, supply chain resilienceAbstract
Manufacturing continuity in pharmaceutical systems is increasingly exposed to structural turbulence arising from supply disruptions, energy volatility, regulatory dependencies, capacity concentration, and quality system constraints. Although conventional manufacturing indicators, such as utilization and output, remain useful for operational monitoring, they often provide limited explanatory power when addressing why some manufacturing systems remain adaptive while others experience delays, stagnation, or fragility. This study introduces System Shift as a structural diagnostic framework for assessing manufacturing resilience within an anonymized Indian pharmaceutical manufacturing group. The framework operationalizes seven dimensions: System Condition (SC), Domain Lock (DL), Actor Complexity (AC), Chokepoint Severity (CP), Position Quality (POS), Strategy Quality (STR), and Feedback Maturity (FB). Using a synthetic-anonymized dataset comprising 64 manufacturing cases, this study examined whether the framework predicted Delay_Days, Progression, Success, and Continuity_Index more effectively than conventional utilization-based status indicators. The results provided strong exploratory empirical support for the framework. Chokepoint Severity (CP) demonstrated a strong correlation with Delay_Days (r = 0.863) and significantly predicted delays in linear regression analysis (R² = 0.744; p < 0.001). The composite System_Shift_Risk_Score demonstrated an even stronger predictive capability for Delay_Days (R² = 0.836; p < 0.001) and substantially outperformed utilization-only status in predicting Delay_Days, Success, and Progression. Strategy Quality significantly predicted Success and Progression in logistic regression models, whereas Feedback Maturity demonstrated positive but weaker directional effects. Feature importance analysis and cluster analysis further identified three theoretically coherent manufacturing states: adaptive low-risk, transitional medium-risk, and stagnant high-risk.
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