Supermarkets play a crucial role in modern life, offering convenience and a wide range of products to meet the diverse needs of consumers. They provide a one-stop shopping experience, saving time and effort while catering to diverse preferences and budgets. However, when you regard supermarkets as an interim point to accommodate consumer demand for the food industry, sustaining a certain level of products is critical for long-term profitability. Each instance of an out-of-stock item represents a missed sales opportunity. In addition, effective inventory management is essential for balancing supply and demand, optimizing stock levels, and minimizing excess inventory. The objective of this study is to estimate the effect of the expected shifts in the availability of products on sales revenue. The dataset, including the average availability of sub-categories and corresponding sales revenue, was modelled using Vector Autoregressions (VAR), and we captured the dynamic relationship between availability and sale revenue over time. The impulse response functions (IRF) are crucial as they help trace the impact of a shock in one variable through the system, showing the effect on another variable over time. In our study, we employed IRFs to determine the potential weekly profit and loss scenarios in sales revenue that resulted from a shock in availability. Using the model purpose in this publication, a sales officer can foresee the consequences of expected changes in availability on sales revenue. The model can be used as an early warning system.