An organic produce company divides Canada into five regions: West, Prairies, Ontario, Quebec, and Atlantic. Each has its own greenhouses for growing organic produce and its own distribution system to retail outlets. The fruits and vegetables are produced without pesticides, thus reducing their shelf life, and for the past two years the company has been facing a problem with spoilage and a short shelf life after delivery to the retailer. Critique (making four separate points) the following discussion between the vice presidents of Logistics and Marketing:

Marketing: “You’ve got to deliver the product faster to the retailers. We’re losing customers because the product has too short a shelf life when they receive it.”

Logistics: “Nonsense. The problem is that your sales- T people don’t get us enough customers. If we had more volume we could make a more efficient delivery system and get the product to the stores earlier.”

Marketing: “I think short shelf life is causing reduced sales. You think low sales are causing reduced shelf life. Let’s sort this out with actual data. We’ll get data on shelf life (at time of delivery) and sales volume for each region for the past 24 months. I’ll do a regression of sales against shelf life as the explanatory variable and I bet the slope comes out significantly positive. That will prove that increasing shelf life will increase sales. Also it will tell us how much sales will be if we can increase shelf life beyond what it has been in the past two years.”

Logistics: “I don’t think the slope in your regression will be significant, but if I regress shelf life against sales as the explanatory variable, I bet my slope will be significantly positive. That will show that if you can increase sales, I will be able to increase shelf life.”