Debt Structure, Capital Composition, and Liquidity Assessment in Global Beverage Corporations: A Case Study of Diageo
DOI:
https://doi.org/10.55047/transekonomika.v6i2.1167Keywords:
Corporate Risk Management, Deleveraging Cycles, Financial Leverage, FMCG Financial Analysis, Solvency RatiosAbstract
Background: Effective capital structure management is vital for multinational corporations navigating volatile global markets. This study examines the relationship between debt components and revenue generation in Diageo Plc, a global leader in the alcoholic beverage industry with a diverse portfolio of over 200 brands.
Objectives: The research evaluates cyclical debt trends, leverage risk, liquidity adequacy, and debt-servicing capacity to determine how capital structure influences financial performance.
Methodology: Spanning a ten-year period (2015-2025), the study utilizes public financial statements to calculate three primary ratio series: capital structure (G1), asset coverage (G2), and debt servicing (G3). This quantitative approach facilitates a longitudinal analysis of the company’s fiscal health through various economic cycles.
Findings: Results indicate that Diageo employs a high-leverage strategy, particularly during strategic acquisitions and the COVID-19 pandemic. Debt levels exhibit cyclicality, spiking during high-investment phases and moderating during deleveraging periods. Despite high leverage, the company maintains adequate liquidity and a stable equity buffer. Debt-servicing indicators, specifically EBIT-to-interest coverage, remain robust, confirming Diageo’s capacity to meet obligations under market volatility.
Conclusions: Diageo successfully balances aggressive leverage with prudent liquidity planning, enabling global growth without compromising solvency. This dual approach serves as a benchmark for corporate debt management in the beverage industry. The scientific novelty of this study lies in the integrated G-series ratio approach, which provides a more granular assessment of corporate debt burden than traditional univariate analysis.
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