Question

Can all parts to this be answered using excel?

1. Problem 16-11 (Algorithmic)

   In preparing for the upcoming holiday season, Fresh Toy Company (FTC) designed a new doll called The Dougie that teaches children how to dance. The fixed cost to produce the doll is $100,000. The variable cost, which includes material, labor, and shipping costs, is $34 per doll. During the holiday selling season, FTC will sell the dolls for $42 each. If FTC overproduces the dolls, the excess dolls will be sold in January through a distributor who has agreed to pay FTC $10 per doll. Demand for new toys during the holiday selling season is extremely uncertain. Forecasts are for expected sales of 60,000 dolls with a standard deviation of 15,000. The normal probability distribution is assumed to be a good description of the demand. FTC has tentatively decided to produce 60,000 units (the same as average demand), but it wants to conduct an analysis regarding this production quantity before finalizing the decision.

   1. Create a what-if spreadsheet model using a formula that relate the values of production quantity, demand, sales, revenue from sales, amount of surplus, revenue from sales of surplus, total cost, and net profit. What is the profit corresponding to average demand (60,000 units)?
      
      $  
      
   2. Modeling demand as a normal random variable with a mean of 60,000 and a standard deviation of 15,000, simulate the sales of the Dougie doll using a production quantity of 60,000 units. What is the estimate of the average profit associated with the production quantity of 60,000 dolls? Round your answer to the nearest dollar.
      
      $  
      
      How does this compare to the profit corresponding to the average demand (as computed in part (a))?
      
      Average profit is less than  the profit corresponding to average demand.
      
   3. Before making a final decision on the production quantity, management wants an analysis of a more aggressive 70,000-unit production quantity and a more conservative 50,000-unit production quantity. Run your simulation with these two production quantities. What is the mean profit associated with each? Round your answers to the nearest dollar.
      
      50,000-unit production quantity: $  
      
      70,000-unit production quantity: $  
      
   4. In addition to mean profit, what other factors should FTC consider in determining a production quantity?
      
      The input in the box below will not be graded, but may be reviewed and considered by your instructor.
      
      
      
      Compare the three production quantities (50,000, 60,000, and 70,000) using all these factors. What trade-offs occur? Round your answers to 3 decimal places.
      
      50,000 units:
      
      60,000 units:
      
      70,000 units:
      
      What is your recommendation?
      
      The input in the box below will not be graded, but may be reviewed and considered by your instructor.
      

Answer 1

a) What-if spreadsheet model is following:

EXCEL FORMULAS:

E14 =MIN(E12,E10)*E4-E10*E3+(E10-MIN(E12,E10))*E5-E2

Average profit = $ 380,000

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b) Simulation model is following:

EXCEL FORMULAS:

Parameters						Simulation results
Fixed cost			F	100000
Variable cost			c	34		Average Profit	=AVERAGE(H15:H1014)
Selling price			p	42
Discounted price			v	10
Mean Sales Forecast			μ	60000
Std Dev of Sales Forecast			σ	15000
Production Quantity			Q	60000
Simulation
Trial	Demand	Sales	Surplus	Revenue from Sales	Revenue from Sales of Surplus	Total Cost	Net Profit
	D	S=MIN(D,Q)	V=MAX(0,Q-D)	S*p	V*p	Q*c+F	S*p+V*p-(Q*c+F)
1	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B15,$E$10)	=MAX(0,$E$10-B15)	=C15*$E$4	=D15*$E$5	=$E$10*$E$3+$E$2	=E15+F15-G15
2	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B16,$E$10)	=MAX(0,$E$10-B16)	=C16*$E$4	=D16*$E$5	=$E$10*$E$3+$E$2	=E16+F16-G16
3	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B17,$E$10)	=MAX(0,$E$10-B17)	=C17*$E$4	=D17*$E$5	=$E$10*$E$3+$E$2	=E17+F17-G17
4	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B18,$E$10)	=MAX(0,$E$10-B18)	=C18*$E$4	=D18*$E$5	=$E$10*$E$3+$E$2	=E18+F18-G18
5	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B19,$E$10)	=MAX(0,$E$10-B19)	=C19*$E$4	=D19*$E$5	=$E$10*$E$3+$E$2	=E19+F19-G19
6	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B20,$E$10)	=MAX(0,$E$10-B20)	=C20*$E$4	=D20*$E$5	=$E$10*$E$3+$E$2	=E20+F20-G20
7	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B21,$E$10)	=MAX(0,$E$10-B21)	=C21*$E$4	=D21*$E$5	=$E$10*$E$3+$E$2	=E21+F21-G21
8	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B22,$E$10)	=MAX(0,$E$10-B22)	=C22*$E$4	=D22*$E$5	=$E$10*$E$3+$E$2	=E22+F22-G22
9	=NORMINV(RAND(),$E$7,$E$8)	=MIN(B23,$E$10)	=MAX(0,$E$10-B23)	=C23*$E$4	=D23*$E$5	=$E$10*$E$3+$E$2	=E23+F23-G23

Repeat the simulation formulas for 1000 trials

Average profit = $ 172,377

Average profit is less than  the profit corresponding to average demand of 60,000 units.

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c)

Simulation using 50,000 units is following:

Simulation using 70,000 units is following:

50,000-unit production quantity: $ 231,059

70,000-unit production quantity: $ 65,392

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d)

Net profit with production quantity of 50,000 units is the maximum.

Therefore, it is recommended to produce 50,000 units