Olympic Car Wash
Determine how many cars, on average, turned to the Aalst location of Olympic Car wash during bad weather? What does this tell you about the managerial performance of the Aalst location?
From the two tables given in the case we could extract the following data: Actual revenue earned by Aalst in that quarter = 124,080 Vehicles washed on average per hour during good weather = 24 Average revenue earned per vehicle = € 11 Hours of good weather in that quarter = 470 Hours of good bad in that quarter = 450 Vehicles washed on average per hour during bad weather = unknown variable x Those variables can be put into a mathematical equation where: (470 hours of good weather * 24 vehicles washed per hour * € 11 revenue per vehicle) + (450 hours of bad weather * x vehicles washed per hour * € 11 revenue per vehicle) = 124,080 actual revenue earned by Aalst in that quarter. Solving the equation for x leads to: x = 0. Thus, during bad weather no vehicles were washed at the Aalst location. The fact that no customers visited the Aalst location to get their cars cleaned during bad weather is supposedly reasoned in them not wanting their vehicles to be dirty again right after they leave the car wash. This customer preference is out of control of the Aalst management and therefore is no indicator of their performance at all.
What does the variance report tell you about the managerial performance of the Aalst location?
Price variance The first entry of price variance measures how much more gross profit was generated due to the fact that Aalst increased the sales revenues to € 11 and while assuming that the variable expenses stayed the same, namely € 5 per vehicle serviced. To calculate that adjusted budget, the hours where there was actually sun, were adjusted to the actual amount of 470 hours. Further, the average number of vehicles washed was adjusted to the actual level of 24. In essence, this calculation really focused exclusively on the net effect of increasing the sales
From the two tables given in the case we could extract the following data: Actual revenue earned by Aalst in that quarter = 124,080 Vehicles washed on average per hour during good weather = 24 Average revenue earned per vehicle = € 11 Hours of good weather in that quarter = 470 Hours of good bad in that quarter = 450 Vehicles washed on average per hour during bad weather = unknown variable x Those variables can be put into a mathematical equation where: (470 hours of good weather * 24 vehicles washed per hour * € 11 revenue per vehicle) + (450 hours of bad weather * x vehicles washed per hour * € 11 revenue per vehicle) = 124,080 actual revenue earned by Aalst in that quarter. Solving the equation for x leads to: x = 0. Thus, during bad weather no vehicles were washed at the Aalst location. The fact that no customers visited the Aalst location to get their cars cleaned during bad weather is supposedly reasoned in them not wanting their vehicles to be dirty again right after they leave the car wash. This customer preference is out of control of the Aalst management and therefore is no indicator of their performance at all.
What does the variance report tell you about the managerial performance of the Aalst location?
Price variance The first entry of price variance measures how much more gross profit was generated due to the fact that Aalst increased the sales revenues to € 11 and while assuming that the variable expenses stayed the same, namely € 5 per vehicle serviced. To calculate that adjusted budget, the hours where there was actually sun, were adjusted to the actual amount of 470 hours. Further, the average number of vehicles washed was adjusted to the actual level of 24. In essence, this calculation really focused exclusively on the net effect of increasing the sales