Predicting food sales and adjusting production is a crucial skill for culinary managers who want to optimize their food cost, minimize waste, and satisfy their customers. In this article, you will learn some practical methods and tools to help you forecast your demand and plan your production accordingly.
One of the simplest and most reliable ways to predict food sales is to use historical data from previous periods, such as weeks, months, or seasons. You can analyze your sales records, invoices, inventory reports, and customer feedback to identify patterns, trends, and fluctuations in your demand. For example, you can compare your sales on weekdays versus weekends, holidays versus regular days, or rainy days versus sunny days. You can also adjust your predictions based on special events, promotions, or changes in your menu or prices.
Make sure to also follow the consumer price index. As the cost of goods rise patrons tend to have less expendable income impacting your potential sales.
Another important factor to consider when predicting food sales is your sales mix, which is the percentage of each menu item sold relative to the total sales. Your sales mix can help you determine which items are more popular, profitable, or seasonal, and which ones need improvement, promotion, or elimination. You can calculate your sales mix by dividing the number of each item sold by the total number of items sold, and multiplying by 100. For example, if you sold 50 burgers and 150 sandwiches out of 200 items, your sales mix for burgers is 25% and for sandwiches is 75%.
Once you have gathered and analyzed your historical data and sales mix, you can use different forecasting methods to estimate your future sales. Moving average, for instance, calculates the average of your sales over a certain number of periods and uses it as the forecast for the next period. Exponential smoothing, on the other hand, gives more weight to the most recent sales data and less weight to the older data to account for changes in demand over time. Additionally, regression analysis uses a mathematical formula to find the relationship between your sales and one or more variables that affect your demand. These variables can range from weather, season, price, or promotion. With these methods, you can predict your sales based on expected weather or other variables.
Keep your run rates short. 3 to 6 months max. Anything longer in a volatile market will only cost you money in the long run.
After you have predicted your food sales, you need to plan your production accordingly. You need to consider how much and when to order, prepare, cook, and serve your food items, based on your forecasted demand, available resources, and quality standards. You can use tools such as production sheets, par levels, batch cooking, and portion control to help you organize and manage your production process. For example, you can use a production sheet to list the menu items, ingredients, quantities, recipes, and procedures for each meal period. You can also use par levels to determine the minimum and maximum amounts of each item to keep in stock, based on your expected sales and frequency of delivery.
Production sheets are only as accurate as the information being recorded. Basic accounting, garbage in = garbage out. Hold your team accountable for consistent and accurate information.
Finally, you need to monitor and evaluate your performance and results, and compare them with your predictions and goals. You need to measure and record your actual sales, food cost, waste, customer satisfaction, and feedback, and analyze the differences and reasons for any discrepancies. You can use tools such as variance reports, food cost percentage, food cost per cover, and customer surveys to help you assess your effectiveness and efficiency. For example, you can use a variance report to compare your actual sales and production with your forecasted sales and production, and identify the causes and impacts of any overproduction or underproduction. You can also use food cost percentage to calculate the ratio of your food cost to your sales, and food cost per cover to calculate the average amount of food cost for each customer.
Predicting food sales and adjusting production is not an exact science, but a skill that requires constant learning and improvement. By using these methods and tools, you can enhance your culinary management and achieve your food cost control objectives.
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Gerente de Alimentos y Bebidas @ Almar Resort | Hospitality Industry Expert
Consider the use of technological tools, such as online drives with worksheets for everyone involved to see, and that can be easily understandable, that way you erase from the equation the time wasted on sending emails for someone else to review and then give it back to you so you can make the input in the data and then resend it for reviewing, that will only consume working time. Also, information will be available as soon as you input it into the workflow.