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Supply Chain Management at World Co., Ltd. : 

Supply Chain Management at World Co., Ltd.

World Co., Ltd. : 

World Co., Ltd. From your review of World Co. website, what did you learn about the company? Markets? Where are the stores? Strategic focus?

World’s Inventory Performance : 

World’s Inventory Performance What explains World’s great inventory performance?

SPARCS – What does this stand for? : 

SPARCS – What does this stand for? Super, Production, Apparel, Retail, Customer Satisfaction

Slide 5: 

Product Timeline for Style No. 15122

Some interesting features of World Co merchandising… typical brand “Untitled” : 

Some interesting features of World Co merchandising… typical brand “Untitled” Japanese women – approx. 25-29 years old Bottoms frequently offered in only two or three sizes, tops and dresses in only a single size. Japan is a smaller geographic area  much less climate variation. Very fast changing fashion trends. Try to impart a sense that the customer was purchasing a “one of a kind” garment Minimal store inventory – only one unit of a product on the shelf  necessitating more frequent restocking by sales staff.

Information System Features : 

Information System Features Realtime information SKU (item/size/color by store) Shipments to the stores Shipments between stores Shipments back to the distribution center Accuracy close to 100% during the selling season Semi-annual sales at a few larger department stores where items returned to the distribution center are marked 50% off.

How does World achieve such quick response times? : 

How does World achieve such quick response times? Note that the typical U.S. department store lead time often exceeds six months, while World achieves a two-week response time.

Manufacturing System Features – “Untitled” Brand : 

Manufacturing System Features – “Untitled” Brand Domestic factories (20 vendors)  focus on quick response rather than low cost. Reserves capacity each season without having actual purchase orders or even actual styles finalized Measurement and patterns sent electronically from headquarter to factories. Include specific instructions for the line workers. Fabrics, due to the long lead time, are purchased in advanced. Much of the fabrics are undyed (dying takes approximately one week).

Store Sales for World “Untitled” Brand : 

Store Sales for World “Untitled” Brand $2.2 million given an average floor space of 870 square feet, $2,500 per sq ft. Compared to $155 per sq ft in U.S. specialty stores. Ranges from $750,000 -- $7.5 million.

Forecasting Aggregate Demand : 

Forecasting Aggregate Demand Distribution Side Forecast Store sales plan for category in the sales period Average unit price in the category Number of stores in the chain Example: store sales = $200,000, average unit price = $100, number of stores = 110 ($200,000/store x 110 stores)/ $100/unit = 220,000 units Category Side Forecast Aggregate demand for category (per week) Duration of sales period Example: 45,000 units/week, 4 weeks 45,000/week x 4 weeks = 180,000 units Choose larger of “Distribution” and “Category” forecast Max (220,000, 180,000) = 220,000

Deriving SKU Level Forecasts : 

Deriving SKU Level Forecasts Derived from the “Aggregate” forecasts. Meeting of approx 20 store managers and assistants (all women aged 25-29) twice each for Autumn-Winter (June and August) and Spring-Summer (December and February) collections Room set just like the stores, price tags are affixed to finished samples. Can try on the clothes (just like a customer would). Managers record their thoughts on “ballots”, judge overall rank (1-7), and ranks of fabrics and colors. 4 (noncommittal) are not permitted This allowes the rank of the fabrics/colors as well as the styles, often find better matches of fabrics/colors and styles. Weighted mean and standard deviation of rank derived. Use an ABCD analysis. “A” SKUs are the top 10% and expected to produce 40% of sales, “B” next 20% of SKUs represent 30% of sales, “C” next 30% produce 20% of sales, and “D” 40% of SKUs that produce 10% of sales. So if there are 400 SKUs in the category: (220,000 x 40%)/(10% x 400) = 2,200 units/A-SKU

Slide 13: 

Why does World, in spite of great inventory management and supply chain management, fail to generate good ROA or ROE? (only about 2.5% vs. 40-50% for the GAP and Limited) So many smallish brands, economies of scale are not great…

Can World’s supply chain processes be replicated at other apparel companies?What about non-apparel supply chains?What are some potential barriers? : 

Can World’s supply chain processes be replicated at other apparel companies?What about non-apparel supply chains?What are some potential barriers?

SCM at World Co. – Key Points : 

SCM at World Co. – Key Points Fashion Retailing – factors for success Having the right product, at the right store, at the right time. Need to minimize the need to discount. Maximize sales per square foot. Amazingly responsive process Merchandisers working directly with the factory Very flexible ordering of products Very short order to delivery lead time Notable features of the process Forecasting new product demand Initial product ordering logic Reservation of factory capacity without committing to production of specific product Material ordering – staged for use when and if needed Great product focus 25-29 year old female customers Very homogeneous target group Limited sizes needed Predictable preferences and demand characteristics from year to year

Time-Series Forecasting Models : 

Time-Series Forecasting Models Moving Average Model Given a number of periods (N) Forecast = Average demand of the past “N” periods Exponential Smoothing Model Given an “Alpha” value (smoothing constant) Forecast = Alpha x Current Demand + (1 – Alpha) x Past Forecast Mean Absolute Deviation (MAD) error measure Average past absolute error Similar to Standard Deviation (Std Dev = 1.25 MAD) Bias Average past actual error