Abstract: This study provides an in-depth analysis of government subsidies and grants aimed at fostering industrial growth, focusing on key challenges and the relationship between financial support and quantified benefits. Through descriptive statistics, the analysis reveals significant variability in budget allocations and beneficiary numbers across various schemes. This disparity highlights differences in the scale and reach of these programs, prompting a need to understand the underlying policy drivers that influence resource distribution. Moreover, the study demonstrates a strong positive correlation between subsidy amounts received and observed benefits, suggesting that increased financial support directly contributes to industrial advancements. However, the challenges in subsidy distribution, such as application process delays, infrastructure gaps, and reimbursement delays, significantly impact the effectiveness of these programs. The study proposes actionable recommendations for improving subsidy allocation, addressing the identified challenges, and enhancing the overall impact of government support. These recommendations include the investigation of budget allocation policies, the analysis of beneficiary targeting, and the collection of missing data on the validity periods of schemes. The paper also suggests conducting a detailed disaggregation of subsidy types and exploring their respective impacts on the quantified benefits achieved. Additionally, the analysis calls for a comprehensive evaluation of challenges in subsidy distribution, with an emphasis on multi-instance data collection and root cause analysis to develop targeted solutions. Through these steps, the study aims to optimize the efficiency and effectiveness of government grants and subsidies, fostering sustainable industrial growth and equitable access to financial support.

Keywords: Targeting beneficiaries, quantified benefits, application process, infrastructure gaps, policy drivers, financial assistance, data analysis, equity of subsidies, efficiency analysis.

| DOI: 10.17148/IARJSET.2025.12525