Case study – super fun toys qnt/561 version 9 university of phoenix

Case Study – Super Fun Toys QNT/561 Version 9

 

University of Phoenix Material                      

 

Case Study – SuperFun Toys

 

SuperFun Toys, Inc., sells a variety of new and innovative children’s toys. Management learned the pre-holiday season is the best time to introduce a new toy because many families use this time to look for new ideas for December holiday gifts. When SuperFun discovers a new toy with good market potential, it chooses an October market entry date. To get toys in its stores by October, SuperFun places one-time orders with its manufacturers in June or July of each year.

Demand for children’s toys can be highly volatile. If a new toy catches on, a sense of shortage in the marketplace often increases the demand to high levels and large profits can be realized. However, new toys can also flop, leaving SuperFun stuck with high levels of inventory that must be sold at reduced prices. The most important question the company faces is deciding how many units of a new toy should be purchased to meet anticipated sales demand. If too few are purchased, sales will be lost; if too many are purchased, profits will be reduced because of low prices realized in clearance sales.

This is where SuperFun feels that you, as an MBA student, can bring value.

For the coming season, SuperFun plans to introduce a new product called Weather Teddy. This variation of a talking teddy bear is made by a company in Taiwan. When a child presses Teddy’s hand, the bear begins to talk. A built-in barometer selects one of five responses predicting the weather conditions. The responses range from “It looks to be a very nice day! Have fun” to “I think it may rain today. Don’t forget your umbrella.” Tests with the product show even though it is not a perfect weather predictor, its predictions are surprisingly good. Several of SuperFun’s managers claimed Teddy gave predictions of the weather that were as good as many local television weather forecasters.

As with other products, SuperFun faces the decision of how many Weather Teddy units to order for the coming holiday season. Members of the management team suggested order quantities of 15,000, 18,000, 24,000, or 28,000 units. The wide range of order quantities suggested indicates considerable disagreement concerning the market potential.

Having a sound background in statistics and business, you are required to perform statistical analysis and the profit projections which is typically done by the product management group. You want to provide management with an analysis of the stock-out probabilities for various order quantities, an estimate of the profit potential, and to help make an order quantity recommendation.

SuperFun expects to sell Weather Teddy for $24 based on a cost of $16 per unit. If inventory remains after the holiday season, SuperFun will sell all surplus inventories for $5 per unit. After reviewing the sales history of similar products, SuperFun’s senior sales forecaster predicted an expected demand of 20,000 units with a 95% probability that demand would be between 10,000 units and 30,000 units.

 

Order Quantity      15,000            
Purchase Cost per unit  $    16.00            
               
  Sales Order Quantity Total Cost Total Revenue Profit
        @ $24.00 @ $5.00  
  Pessimistic   10,000             15,000        
  Likely   20,000             15,000        
  Optimistic   30,000             15,000        
               
Order Quantity      18,000            
Purchase Cost per unit  $    16.00            
               
  Sales Order Quantity Total Cost Total Revenue Profit
        @ $24.00 @ $5.00  
  Pessimistic   10,000             18,000        
  Likely   20,000             18,000        
  Optimistic   30,000             18,000        
               
Order Quantity      20,000            
Purchase Cost per unit  $    16.00            
               
  Sales Order Quantity Total Cost Total Revenue Profit
        @ $24.00 @ $5.00  
  Pessimistic   10,000             20,000        
  Likely   20,000             20,000        
  Optimistic   30,000             20,000        
               
Order Quantity      24,000            
Purchase Cost per unit  $    16.00            
               
  Sales Order Quantity Total Cost Total Revenue Profit
        @ $24.00 @ $5.00  
  Pessimistic   10,000             24,000        
  Likely   20,000             24,000        
  Optimistic   30,000             24,000        
               
Order Quantity      28,000            
Purchase Cost per unit  $    16.00            
               
  Sales Order Quantity Total Cost Total Revenue Profit
        @ $24.00 @ $5.00  
  Pessimistic   10,000             28,000        
  Likely   20,000             28,000        
  Optimistic   30,000             28,000        
               

 

Order Quantity              
Purchase Cost per unit  $     16.00            
               
  Sales Order Quantity Total Cost Total Revenue Profit
        @ $24.00 @ $5.00  
  Pessimistic   10,000          
  Likely   20,000          
  Optimistic   30,000          

 

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