Question

A gourmet pizzeria delivered the following quantities (pizzas) over the past 12 months in 2018:

Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
3,300	3,500	3,450	3,600	3,700	3,750	3,700	3,750	3,950	3,950	4,100	4,250

November 4,100

December 4,250

The average monthly operating cost, including delivery, can be categorized as follows:

Direct Labor = $14,500

Material = $4,000

Overhead = $5,500

In the past three 3 months (October through December), the pizzeria collected information regarding customer complaints or returns. In all, 738 pizzas were remade and/or delivered free of charge for the following reasons:

Reason	# of pizzas
Wrong order delivered	82
Pizza was cold	55
Cheap on toppings	90
Wrong crust	122
Undercooked	40
Burnt crust	65
Delivery time too long	182
Other	102

The pizzeria process flow layout with (maximum capacity of pizzas per hour) is as follows:

Take order (60)

Prep (30)

Bake (22)

Package (40)

Deliver (35)

What is the overall productivity per $1 input?

Plot the monthly sales data and forecast the data set including January 2019 demand using the following methods:

Naïve method

Three-month moving average with 50% of weight for latest month and 25% for each of the other

Exponential smoothing forecast using alpha = 0.4

Linear trend equation

Which method would you pick based on mean square error (MSE)?

Use Pareto analysis to prioritize issues (complaints) so that you can tackle the vital few? What issue(s) would you tackle first?

Based on the process layout, what is the capacity of the pizzeria?

If the capacity of one operation could be increased in order to increase throughput, which operation would you target and by how much? Why?

If the pizzeria had re-arranged the layout and improved the process flow using lean methods allowing it to cut the direct labor cost by 5%. Also, and based on initial numbers, complaints related to delivery taking long is expected to decrease by 50%. What would be the resulting overall productivity per $1 input?

Give two recommendations for the pizzeria to improve productivity and profitability? What tools would you use to accomplish these recommendations?

Answer 1

Answer:

1)

Overall productivity of the system = Total output / Total input

Total input = 1 hour

Total output = Output of the bottleneck process = 22 pizzas

Hence, overall productivity = 22/1 = 22 pizzas per hour

2)

3)

Using Pareto Analysis we arrived at the following conclusions as evident of the following:

• 
• As evident of above chart one can deduce that "delivery time too long' intersects with 80% mark. Hence, in accordance to Pareto Rule, this issue needs to be taken care of as soon as possible. As this contributes the most.

4)

Based on capacity layout The capacity of pizzeria is 22, as baking is the bottleneck process which dictates the overall performance.

5)

As mentioned above bottleneck process is baking. So first it needs to be increased by 8 to reach 30 so as to equal Prep. This will make increase the capacity of pizzeria by 8 per hour. Hence, will be sufficient to produce 30 pizza per hour.

6)

Average production during months of Oct - Dec. = 4100

Cost of production per month =24000

Avg rework per month / lost profit in form of free pizzas = 738/3 =246

Total pizzas that resulted in profits =4100-246 = 3854

Cost per pizza = 24000/3854 =6.227

or pizzas made per $1 input = 0.160

New total cost = 14500x0.95+4000+5500 =22800

Total pizzas going for free now = 738-91 =647

Avg monthly free pizzas = 216

Total pizzas that result in profits = 4100-216 = 3884

Pizzas now made per $1 input = 3884/22800 =0.17

change in productivity = .0.17/0.16 = 1.0646

percentage change = 6.46%

7)

Recommendations

(a) Insituting training for the staff in the kitchen to reduce the instances of wrong / uncooked /overcooked / burnt / poorly prepared pizzas which account for large chunk of free orders. Another effort should be for ground staff with better scheduling, faster modes of movement and familarilty with  local geography to avoid the instances of delay. Together, they can reduce the complaints to a minimum.

(b) It can be seen that the baking stage is bottleneck which limit the quantity of pizza to 22 per hour. This can be increased to 30 per hour, if a new baking equipment is installed. Further improvement can be brought about with reduction of preparation time by employing higher number of employees in preparation department. By adding some more delivery members, the output can be increased beyond 35 per hour. However, the cost - benefit analysis needs to be done before making changes.