This study introduces and validates the Inter Plant Productivity Model (IPPM), a novel framework designed to measure and enhance productivity in continuous production systems with multiple interconnected plants. It addresses the critical gap of capturing inter-plant dependencies to achieve system-wide efficiency.
The study applies the IPPM, a structured framework that integrates cross-plant data to evaluate productivity holistically. Unlike conventional models that assess individual plant performance, IPPM enables system-wide optimization by incorporating three key productivity factors: Specific Consumption Efficiency Factor (SCEF), Minimum Loss Factor (MLF) and Overtime Minimisation Factor (OMF). These weighted metrics allow for a detailed breakdown of inefficiencies, enabling real-time corrective actions and improved resource allocation across plants. Statistical validation techniques—including paired t-tests, ANOVA and regression analysis—were employed to confirm the model's effectiveness.
The implementation of IPPM led to a statistically significant 12% increase in overall productivity. SCEF was identified as the most influential driver, with regression analysis confirming that SCEF, MLF and OMF collectively explain 78% of the productivity variation.
The academic contribution of this study lies in the application of a holistic operations management framework within a real industrial setting, offering practical evidence for performance improvement methodologies. The case reinforces the relevance of data-driven decision-making, participatory problem-solving and continuous process evaluation in industrial operations. From a performance management perspective, the study offers a replicable model that integrates operational metrics with employee involvement to achieve sustained productivity gains. The findings are especially relevant for scholars and practitioners focusing on applied industrial engineering, operations strategy and performance optimization in emerging markets.
IPPM enables organizations to identify and resolve inefficiencies in real time, fostering a competitive environment among interconnected plants and supporting continuous improvement. The structured computation of the Plant Productivity Factor (PPF) facilitates objective performance comparisons, enhances decision-making and supports strategic resource allocation. The model's flexibility ensures its applicability across various industrial sectors, including fertiliser production, automotive, pharmaceuticals and electronics manufacturing.
This study's primary contribution is the empirically validated IPPM, which bridges a critical gap between theoretical productivity models and the practical realities of interconnected production systems. IPPM offers a novel, systems-thinking framework for performance management, enhancing traditional models like Total Productivity Measure (TPM).
