Case Study Summary of Zara and Oxford Industries Essay

Zara particularizes in inexpensive musical modes for women and men between the ages of 16 and 35. In keeping with the spirit of that demographic, Zara moves quickly. manage many app arel retail merchants, it has two seasons bowling pin/winter and spring/summer but selections change frequently within those periods. Items transcend no more than than two weeks on the shelf before making poreing for new merchandise, and submits are replenished twice a week.With annual growth of around 20 pct in twain sales and spell of stores, Zara was finding that strategy progressively difficult to execute. Part of the Inditex group of fashion distributors, it currently has more than 1,100 stores in 68 countries. With so very much volume flow rate through the supply chain, the confederation could no longer rely on nip by store managers as to how much product it strikeed to replenish at each location.In the summer of 2005, Zara hear about research being through on mathematical shams for retailing, by professors Jeremie Gallien of the MIT Sloan shoal of Management and Felipe Caro of the UCLA Anderson School of Management. They were invited to Zaras headquarter in La Coruna, Spain.The focus was on making better stock-allocation decisions for Zaras growing network of stores. A prototype of the resulting influence was consumeed between March and July of the spare-time activity year, as part of a six-month internship at Zara by MIT graduate student Juan Correa. in the midst of August and December, researchers ran a live flee involving dissemination of a dozen products to Zaras stores worldwide. An identical selection of products was dispatched to stores under the obsolescent attend, for purposes of comparison.The mathematical model drew on historical sales data confirming available stock in the warehouses to buzz off up with a final material body for each store. Gallien says the task was exceedingly complex. each store carries several thousand items i n up to eight sizes, with exact quantities to be deliberated for twice-weekly shipments. Through use of the model, computers could allow in over the basic number crunching, with reality left to make adjustments based on exceptions such as bad tolerate or unexpected disruptions in the sales channel.The emphasis on fast turnaround motivates consumers to purchase items on the spot. Unlike in many uniform stores, where seasonal lines perch on the shelves for weeks or months, a concomitant style in a Zara store can disappear within a week. Zara speeds up its supply chain by strategically selecting and locating suppliers. A law of proximity model judges not altogether their geographic placement, but their major power to act quickly to production orders. About half(prenominal) of the retailers production meets the proximity threshold, mostly coming from suppliers in Spain, Portugal and Morocco. From a geographic standpoint, nearly 65 percent of production is sourced in Europ e. Zara in any case buys from suppliers in Asia, but because of the need for speed, their number is easily less(prenominal) than the industrys average.The model has yielded additional benefits. Product like a shot spends more time on the sales floor, and less in a back room or warehouse. With a reduction in misallocated inventory, there are fewer returns to the warehouse and transfers between stores. And, as Zaras distribution network continues to grow, the retailer wont need to expand its warehouse squad as fast as the old process required.Summary of Oxford IndustriesOxford Industries began in 1942 as a domestic manufacturer of basic, conventional shirts for mid-level retailers, particularly surgical incision stores. In new-fangled years, however, the participation has shifted its business model to focus on apparel design and marketing, with third-party producers manipulation manufacturing. As part of this shift, the Atlanta-based company embraced a brand-focused busine ss strategy. In 2003, Oxford acquired the island-inspired Tommy Bahama operations, followed by the 2004 learning of Ben Shermana strong-known London-based brand make famous by the popularity of its shirts among British sway stars.Oxfords legacy business units, Lanier tog and Oxford Apparel, also evolved. As one of the conduct suppliers of mens tailored clothing to retailers, Lanier Clothes designs and markets suits, sports coats, suit separates and jell slacks. eon continuing to sell these under insular labels, it also has licensed a number of well-known brands, including Geoffrey Beene, Kenneth Cole and Dockers. These products span a wide price range and are sold at national chains, department stores, specialty stores and discount retailers throughout the coupled States. Oxford Apparels products range from dress shirts and western wear to suit separates and golf game apparel, designed mostly for private-label customers like Lands End, unite Department Stores and Mens Wea rhouse.Oxford Industries also sells through 55 of its own stores. In the late 1980s, early in its transformation process and prior to the acquisition of Tommy Bahama and Ben Sherman, Oxford completed that it needed to bring its business divisions up to speed with more robust teaching technology. After completing the carrying into action of a company-wide enterprise resource devisening system, the company contracted with an independent consulting firm to determine where it should invest time and money to win increase operational efficiencies and performance. The result of that in-depth study ultimately led to Oxford Industries decision to implement two events from JDA Software Demand plan and master Planning.With so many assertable permutations of size, style and color for each of its products, upward(a) forecast accuracy was critical. Prior to implementing JDA Demand, Oxford relied on its retail customers demand forecasts for its private-label products, as well as informat ion provided by the companys own sales associates. If too much or too small product was created based on the retailers or the sales associates forecast, both Oxford Industries and that customer paid the price via disoriented sales or markdowns.JDA Demand enabled the company to better understand consumers evolving requirements and current trends, on with historical buying patterns, resulting in the ability to create more accurate forecasts and contemporise demand for replenished product with sources of supply. Oxford Industries can now compare its forecasts with those of its retail customers to ensure that the function amount of product is manufactured, leading to modify collaboration and service levels with its trading partners.The implementation of JDA Master Planning leveraged the solutions automated functionality to hive up product information and production constraints to return weekly sourcing and inventory plans from style to the SKU level. The solution also simultaneo usly considered factory capacities including special features, raw-material availability, and manufacturing and customer lead-times. Since Master Planning generated a first version of the supply plan by noon each Monday, Oxford Industries planners had quaternary and a half days to fade away any issues to accommodate unplanned demand, which translated to an 85-percent gain in planning efficiency.Although the companys sourcing model has since shifted from a typical manufacturing process to more of a purchase process, manufacturing and customer lead-times, SKU-level decisions and some capacity constraints still need to be factored into the supply planning process. Master Planning provides the tools to let managers manage preferably of serving as data-entry technicians.