The Factor Method is best suited for operations with historical data that show a difference between sales and food cost. Which statement describes this usage?

The Factor Method is best suited for operations with historical data that show a difference between sales and food cost. Which statement describes this usage?

• A. Best for startups with no historical data
• B. A method used to forecast demand
• C. A simple markup method appropriate when historical data shows a difference between sales and food cost
• D. Used only for beverage pricing

Answer: (C)

The Factor Method prices menu items by using a factor derived from the historical relationship between food cost and sales. You look at past data to see what percentage of sales goes to food cost, then convert that percentage into a pricing factor. That factor is applied to the cost of each item to determine its selling price. It’s a straightforward markup approach that relies on a stable cost-to-sales ratio. Why this fits: if historical data shows a consistent relationship between sales and food cost, you can set prices so that food cost remains in line with that history. The math is simple: selling price = cost ÷ target food cost percentage (which is the same as cost × factor, where factor = 1 ÷ target food cost percentage). For example, with a target food cost of 35%, the factor is about 2.857, so a dish costing $5 would be priced around $14.29. This approach isn’t about predicting demand or trends, and it isn’t restricted to beverages. It also isn’t suitable when there’s no historical data to establish the cost-to-sales relationship.

The Factor Method prices menu items by using a factor derived from the historical relationship between food cost and sales. You look at past data to see what percentage of sales goes to food cost, then convert that percentage into a pricing factor. That factor is applied to the cost of each item to determine its selling price. It’s a straightforward markup approach that relies on a stable cost-to-sales ratio.

Why this fits: if historical data shows a consistent relationship between sales and food cost, you can set prices so that food cost remains in line with that history. The math is simple: selling price = cost ÷ target food cost percentage (which is the same as cost × factor, where factor = 1 ÷ target food cost percentage). For example, with a target food cost of 35%, the factor is about 2.857, so a dish costing $5 would be priced around $14.29. This approach isn’t about predicting demand or trends, and it isn’t restricted to beverages. It also isn’t suitable when there’s no historical data to establish the cost-to-sales relationship.