Weighing Out Versus Cubing Out$$Mini Case Study

Value Grocers has decided to expand its model to include product lines such as packaged deli meats and cheeses, crackers, potato chips, canned nuts, yogurt, and milk. You can find the detailed storage and logistics characteristics for each of our new product groups along with a sample model and detailed instructions for further analysis within the Value Grocers Expanded Product Line Exercise.zip file on the book Web site.

a$.$ In the first model built, found in the file referenced above, we use only the weight of the products to determine transportation costs. What are the resultant transportation costs in the results of this model?

b$.$ Let's do further analysis to see how accurate these transportation costs might be$.$ Using the Value Grocers Expanded Product Line Measurements.xls to start, complete your own calculations to determine which of these product groups will "weigh out" versus "cube out" $($hit the max capacity based on weight or volume limits first$)$ in real$-$life transportation costing. Remember that a single truckload of product can transport up to $40,000$ pounds or $2,000$ cartons of product.

i$.$ Which products will weigh out?

ii$.$ Which products will cube out?

ii$.$ What is the resultant per$-$carton transportation cost for each product grouping based on this? What would it be if we didn't differentiate between the products?

c$.$ Back in our model, let's adjust the model to include both the weight and the volume characteristics of each of our products, as well as apply both capacity constraints on the truckload carrier costs.

i$.$ How does this impact our overall transportation costs within the model?

ii$.$ Does this cause the model to select different optimal warehouse locations?

iii. Do certain product groupings tend to come from certain warehouse locations, or are product groupings fairly evenly distributed across the selected warehouses?