Shuzworld Task 2
Charlene Taylor
WGU 000345193

Shuzworld Task 2
I was asked to provide a distribution pattern that minimizes shipping costs and provides adequate availability and demand. I used transportation modeling to solve this problem. Transportation modeling is “an interactive procedure that finds the least costly means of moving products from a series of sources to a series of destinations” (Heizer & Render, 2011). This tool is used to determine the best distribution pattern for multiple locations. It is best for this problem because it allows for us to determine how many products can be held at each location to give Shuzworld the lowest shipping costs. The original setup had an optimal shipping cost of $13,600. It had 1300 …show more content…
There is typically a customer being services every 5 minutes, so the service rate is 12 customers per hour. One server is typically busy 0.5 of the time. There is usually 0.5 customers in the queue at any given time. There is 1 customer in the system at one time. This means that a customer spends 0.08 hours (5 minutes) in the store waiting to be serviced. A customer spends 0.17 hours (10 minutes) in the store making their complete purchase. This is too much time for a customer to wait and be serviced. This long wait time may dissuade sales, as customers do not want to wait to be helped or pay for their purchases. Using a two-cashier system is a more efficient option of Shuzworld. The average server utilization is 0.25, meaning that 75% of the time, there is a server available to help customers. There is 0.03 customers in the queue at any given time, with 0.53 customers being served at one time. This means that the customer spends 0.01 hours (.33 minutes) waiting to be served, and 0.09 hours (5.33 minutes) in the store completing their purchase. This system allows the customers to get into the store, pick out their items, and pay in less than 6 minutes. This will definitely encourage future business with the company. Customers want to have the least amount of time spent in a store, and waiting for service may cause some to leave without making a purchase. This analysis tool allowed us to