Beyond Project Status: System Shift as a Structural Diagnostic Framework for Predicting Delay, Stagnation, and Adaptive Progression in Pharmaceutical Development Portfolios

Abstract

The pharmaceutical industry continues to face significant challenges in research and development (R&D) productivity, characterized by increasing development costs, extended timelines, and high rates of project delay and stagnation. Although project status classifications are widely used to monitor development progress, they often fail to explain the structural factors that cause projects to become stalled. This study aims to evaluate the System Shift framework as a structural diagnostic model for predicting delay, stagnation, adaptive progression, and success in pharmaceutical development portfolios. An exploratory empirical-methodological approach was employed using data from a pharmaceutical development portfolio consisting of 112 projects, from which 41 project-level cases were selected and coded. The framework operationalized seven dimensions: System Condition, Domain Lock, Actor Complexity, Chokepoint Severity, Position Quality, Strategy Quality, and Feedback Maturity. Data were analyzed through descriptive statistics, correlation analysis, regression models, logistic models, and cluster analysis. The findings reveal that Chokepoint Severity is the strongest predictor of project delay (r = 0.932; R² = 0.868), while Feedback Maturity and Strategy Quality significantly enhance progression and success. Furthermore, the System Shift Risk Score demonstrated superior predictive performance compared to traditional status-based classifications. The study concludes that System Shift provides a promising diagnostic framework for identifying structural constraints and adaptive capacities, thereby supporting more effective portfolio governance, decision-making, and organizational learning in pharmaceutical development environments.