Abstract

Traditional budgeting practices in many organizations continue to rely heavily on historical figures without incorporating structured forecasting techniques, which limits their usefulness for long-term financial planning in fast-changing industries. This study examines budget forecasting as a strategic tool for financial planning and control, using Zomato Ltd. a rapidly expanding Indian food-delivery and quick-commerce platform as an analytical case. Using five years of consolidated financial data (FY2019–FY2024) drawn from public company filings, the study applies linear trend projection and simple linear regression, computed in Microsoft Excel, to forecast revenue for FY2025–FY2029 and to test the statistical relationship between time and financial performance. Results show a positive linear trend in revenue (y = 1512.7x + 4191.4) and a regression equation of Y = 4585.9 + 1414.1X with R² = 0.527, though the time coefficient was not statistically significant at the 5% level (p = 0.274). A two-sample t-test comparing historical and forecasted revenue found a statistically significant difference (t(8) = −4.50, p = 0.002), indicating that the forecasting model produces projections that differ materially from historical performance. The findings support time-series trend forecasting as a practical, low-cost planning aid for management even where formal regression significance is not established, and point to the value of combining classical trend methods with more advanced techniques, such as ARIMA or machine-learning models, in future research.

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