BM4342: ZARA is a Spanish apparel retailer based in Arteixo, Galicia, Spain The Company specializes in fast fashion: Warehouse and Inventory Management Assignment, NYP

Part A Qualitative Analysis

Answer all the following questions:

(A)For students whose administrative number ends with an odd number, please attempt the Zara Case below:

Case 1: Retailer ZARA

ZARA is a Spanish apparel retailer based in Arteixo, Galicia, Spain. The Company specializes in fast fashion, and its products include clothing, accessories, shoes, swimwear, beauty, and perfumes. There are 2,259 Zara stores in 96 countries.

The company can design a new product and has the finished goods in its stores in four to five weeks. It can modify its existing items in as little as two weeks. Shortening the product life cycle means greater success in meeting
consumer preferences. If a design does not sell well within a week, it will be withdrawn from the shops, further orders are cancelled and a new design is pursued.

Zara monitors the rapidly changing fashion trends very closely. While Zara has a range of basic designs that are carried over from year to year, there are also some fashion-forward designs that stay on the shelves for less than four weeks. This encourages Zara fans to make repeat visits to their stores. An average high-street store in Spain expects customers to visit three times a year. For Zara, the number goes up to 17 times a year.

Case is adapted and compiled from various internet sources.

i. Explain why demand forecasting is a critical function of any business, regardless of the stage of the supply chain the company is operating in or the types (push and pull) of supply chain it is practicing.

ii. Based on the information provided in the Zara case, evaluate the following qualitative forecasting methods. With reference to your evaluation, suggest and support with justifications, the most appropriate method to decide on the demand for “design to order” of clothings for Zara.
• Delphi method
• Survey of sales force
• Historical analogy

(B) For students whose administrative number ends with zero or an even
number, please attempt the Nintendo Case below:

Case 2: Nintendo

Nintendo Co., Ltd is a Japanese multinational consumer electronics and video game company headquartered in Kyoto. Nintendo distributed its first video game console, the Color TV-Game, in 1977. It gained international recognition with the release of Donkey Kong in 1981 and the Nintendo Entertainment System and Super Mario Bros. in 1985.

Since then, Nintendo has produced some of the most successful consoles in the video game industry, such as the Game Boy, the Super Nintendo Entertainment System, the Nintendo DS, the Wii, and the Nintendo Switch.

It has created numerous major franchises, including Mario, Donkey Kong, The Legend of Zelda, Pokémon, Kirby, Metroid, Fire Emblem, Animal Crossing, Splatoon, Star Fox, Xenoblade Chronicles, and Super Smash Bros.

However, not all of Nintendo products are successful. The Wii U caused huge financial losses. This was partly due to the success of its competitors. Sony’s strategy to release its video games to other platforms such as smart TVs is one major factor.

Case is adapted and compiled from various internet sources.
i. Explain why demand forecasting is a critical function of any business, regardless of the stage of the supply chain the company is operating in or the types (push and pull) of supply chain it is practicing.

ii. Based on the information provided in the Nintendo case, evaluate the following qualitative forecasting methods. With reference to your evaluation, suggest and support with justifications, the most appropriate method that Nintendo should use to decide on the demand of the design for the next “big” game device.
• Delphi method
• Survey of sales force
• Historical analogy

5. Part B Quantitative Analysis

Perform the following forecasts:

(A) For students whose administrative number ends with the alphabet A to O, use the data set in Appendix 1. Please answer the following questions:

i. Perform the following forecast with same data set using:

Static Winter method and determine the most appropriate periodicity in your analysis.
Simple Exponential Smoothing and determine the most appropriate α (alpha) value in your analysis.

ii. From your forecast above, analyze and suggest with justifications the most suitable technique to forecast the demand for bicycle.

(B) For students whose administrative number ends with the alphabet P to Z, use the data set in Appendix 2. Please answer the following questions:

i. Perform the following forecast with same data set using:
• Static Winter method and determine the most appropriate periodicity in your analysis.

• Simple Moving Average and determine the most appropriate “averaging period”.

ii. From your forecast above, analyze and suggest with justifications the most suitable technique to forecast the demand for mobile phones.

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