Integrated Barrier-Cost-KPI Framework for IoT Readiness in Indian Sheet Metal MSMEs

Indian sheet metal Micro, Small and Medium Enterprises(MSMEs), vital to automotive and appliance sectors, face acute IoT adoption barriers including legacy equipment integration, skill shortages, high costs and precision control challenges that inflate raw material wastage (up to 75%) and reduce operational efficiency. This study aims to develop and validate an integrated framework quantifying how these barriers influence cost structures and Key Performance Indicators (KPI), addressing the gap in sector-specific, impact-based readiness models.A multi-stage quantitative methodology was employed. This included literature-derived shortlisting of 19 barriers, 20 cost categories and 17 KPIs, followed by primary survey data from sheet metal MSME professionals (50-250 employees). Data is analysed using normality checks, reliability assessment (Cronbach’s alpha>0.886), exploratory analysis (yielding 9 barriers, 6 cost and 5 KPI factors) and regression and correlation techniques to derive latent factors and their interrelationships.The integrated framework is developed by modelling barrier factors as predictor variables while cost and KPI factors as dependent variables. This design allows empirical estimation of which barrier clusters create the strongest pressure on operational and investment-related costs and on core KPIs relevant to sheet metal competitiveness. Major Findings: Human-organizational, financial-access and technological-legacy barriers significantly predict cost escalation (R2 =0.559/0.426) and KPI depression (R2 =0.521/0.438) in Indian sheet MSMEs, with financial constraints (β=0.517) and skills gaps showing strongest impacts on labour, training and operational efficiency. The integrated framework enables impact-bases prioritization of IoT interventions over frequency-alone assessments.