Final answer:
To utilize sales history in forecasting foodservice sales and costs, statistical methods like regression analysis are applied to past sales data to identify trends that predict future sales. Market events and changes are also considered to refine sales predictions, enabling strategic business decisions.
Step-by-step explanation:
To forecast foodservice sales and costs using a sales history, one can apply various statistical methods and predictive models. Sales history data gives insights into patterns and trends which help in estimating future sales. For instance, regression analysis might be used to identify relationships between variables such as the day of the year and sales figures. A regression equation, such as ลท = 101.32 + 2.48x, could be used to predict sales on a specific day, with x representing the day.Additionally, understanding how external factors like market changes or events affect demand can refine these forecasts. For example, analyzing scenarios like the end of a conflict or reopening of a major port and its impact on supply, could dictate changes in sales projection due to increased or decreased product availability.
In essence, reviewing historical sales data, understanding market dynamics, and applying statistical models plays a crucial role in forecasting foodservice sales and costs, enabling businesses to make strategic decisions regarding inventory, staffing, and budgeting.