Fitting together a select number of well-priced products to return the best profits is at the core of a vending or micro market business. It requires time, attention and data. With more products than ever before, the task has some operators struggling. That’s why Michael Kasavana, Ph.D., NAMA Endowed Professor, School of Hospitality Business at Michigan State University, introduced a redesigned menu engineering model borrowed from the foodservice sector, and tailored it to the vending and micro market industry. Kasavana presented the model, called Product Intelligence, to attendees of the NAMA OneShow session, Product Engineering: Pricing Drives Success on April 9. “Menu engineering, as a pricing model, is the no. 1 selling pricing model for restaurants. Through product intelligence, it can be part of the vending and micro market business,” he told operators.
Kasavana first went through menu engineering basics, which include looking at the food item, the selling price, the cost, the food cost as a percentage of price and possible menu mixes. For an example, he choose steak and chicken. At a fictitious location, steak sells for $15. Chicken sells for $9. Cost for steak is $7.50 (50 percent of sale price) compared to $3.00 (33 percent of sale price) for chicken. Possible menu mix might include 100 chicken and no steak, 100 steak with no chicken or 50-50 steak and chicken.
At first glance someone might assume to increase profits, the food costs should be minimized, therefore it would be best to go with chicken, or at least more chicken in the menu (See Menu Engineering Example 1). However, the secret to successful menu engineering is calculating the contribution margin (CM) - the selling price minus the direct cost. Taking it a step further, subtracting out the indirect costs from the CM gives an operator total profits. In our steak-chicken scenario, the CM is as follows: $600 for all chicken, $750 for all steak, and $675 for 50 of each. These results would counter the idea that the cheapest product will get the operator the most money.
Kasavana then expanded the of idea menu engineering to vending and micro markets using tables (See Examples 2 & 3) to show product CMs in each point-of-sale type. The item with the highest CM is always going to give operators the most profits. That is why it is important that in all instances, operators must calculate the CM. This is a large part of product intelligence.
Two-For-One’s are not the answer
Using the CM model, Kasavana also dispelled a myth that an operator might sell-out a slow selling product using two-for-one deals. For the example, he took a product with a selling price of $10, subtracted a direct cost of $4 to get a CM of $6. When the deal is a two-for-one, the numbers change to look like this: $10 - $8 = $2. To get the same margin as selling one item, the operator would need to sell six items. If the product is already a slow seller, how could an operator suddenly hope to sell six, Kasavana asked the audience.
How to establish the best price
The CM can also be used to determine the best price for a product. While other ways of determining a price exist, the product intelligence model uses the average contribution margin (ACM) to determine the best price. The ACM is found by taking the average contributed margin for that category. Kasavana used a pastry example where a pastry costs an operator $0.75. With different pricing models, the operator might list the product for $1.65 (arbitrary markup), $2.25 (cost times 3) or $1.90 (cost plus ACM). Using the ACM to dictate price ensures that the operator isn’t underpricing or overpricing an item.
How to adjust the product mix
Kasavana also presented the CM as a way for operators to determine more profitable product mixes in their machines and markets. First, operators need to calculate the volume or sales mix (SM), SM classification (high or low), item CM and CM class (high or low) for current products. Then based on the classifications, the item is labeled a Plow horse (high SM, low CM), Puzzle (low SM, high CM), Star (high SM, high CM) and Dog (low SM, low SM). In the product intelligence model, operators should retain star items, re-price plow horse items, reposition puzzle items and remove dog items. “This will be popular because VMS and micro markets systems have this data,” said Kasavana.
Product intelligence is essentially a new vending product pricing model designed to evaluate competing item contribution margins within a category. Kasavana’s ultimate goal is for operators to use product intelligence to redesign (engineer) their next product mix within a category to be more profitable than the previous product mix. And with a CM based model – the numbers will prove it. “This method will give you a benchmark of [whether you are] doing better each month,” Kasavana concluded.