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I suggest Tesla use the linear regression model with a time series filter based on the recent experience because it will deliver several benefits for them such as it provides greater flexibility and ensures accurate data prediction at all times so that forecasting becomes effective and feasible. This forecasting model uses past sales research in recent times where all sales details are listed, measures the sales pattern over time, and identifies the quantity level of the sales at the time. The recent sales fluctuations help find an optimal quantity level that is beneficial for the company to make the expected forecasting and organize other organization planning with this forecasting. This model is helpful for the company to get effective forecasting because it has been developed on past research and trend of sales, so almost every fluctuation level will be used, and an optimal solution will be beneficial for the company at all times. This forecasting model helps mitigate the complexity of forecasting and offers an easy and accurate forecasting method. Tesla has to manufacture the products at a limited level due to higher costs involved in the production, so this model is helpful for them to predict the best time for production and to hold the inventory to access the most elevated profit conditions.

Conclusion: the linear forecasting method is helpful for organizations to identify accurate measurements for forecasting and mitigate the complexity for Tesla to make effective decision making.