Justificación

It will be increasingly difficult to forecast trends in the future as they become more diverse. In the past, a forecasting company could make a profit by identifying the one major trend; now it is hard to identify all of the diverse trends that develop (Lee, 2009). A shorter fashion cycle makes forecasting even harder. However, trend analysis and forecasting will be just as important because there will be a need to guide the development of continuously evolving products. With the proliferation of new products and shorter product life cycles, it may be impossible to obtain as much history as a forecast analyst needs for good model building. In personal com- puters and consumer electronics, for example, product life cycles are typically three to eighteen months. Fashion apparel items sell for just one season. On the other hand, with the development of new technology, the quantity and quality of data will continue to increase. For example, retail point-of-sale (POS) data is now widely available, making product consumption patterns available to consumer product manufacturers. Web site traffic is another new data point, and several services now provide weather-related data, economic indicators, and other types of information that forecasting models can readily use.

In the future, more companies that produce various fashion products such as cars, electronics, and interiors will depend on trend services than ever before. In the past, apparel and accessories companies were the trend services’ major cli- ents. However, the trend service firms will face a challenge because consumers will increasingly have access to more and more information over the Internet. For example, consumers can now see, in real time, fashion shows for the next season as they take place in Europe. Consumers have become more refined and savvy. With increased access to information, anyone can analyze trends to some extent. There- fore, forecasting firms will do consulting for planning, execution of line develop- ments, and branding in conjunction with trending, which will differentiate them as experts (Lee, 2009).

Chapter summary

Fashion forecasting process begins about two years in advance of the retailing season •

for new products. Broadly, this process encompasses three components: environment, market, and product. First, the environment is scanned to search for current and near future trends in the economic, political, social, and cultural arenas. Understanding the long-term direction of the society can also benefit fashion professionals. Second, mar- ket research on consumers, competing companies, and sales records is conducted. In the final step, the transition of previous products over time is analyzed and the color, textile, and styles of new products for the next season are forecasted.

Two types of fashion forecasting are used: short-term forecasting, which envisions •

trends one to two years in the future and focuses on new product features such as color, textile, and style, and long-term forecasting, which predicts trends five or more years out and focuses on the directions of the fashion industry with regard to materials, design, production, and retailing. Long-term forecasts contribute to a fashion firm’s development strategies and help it make decisions related to repo- sitioning or extending product lines, initiating new businesses, and reviving brand images.

In developing a new collection of apparel products, fashion professionals first •

select the color palette. Color forecasting is conducted from two to two and a half years in advance of the retailing season for new products. The decision about a seasonal color palette is the basis for dyeing yarns and fabric design for all styles in the line.

Fiber producers and mills start projecting fabric trends eighteen months ahead of the •

retailing season. The task of researching seasonal fabrics goes on simultaneously with color research and the determination of a color story. Many services that provide color forecasts also offer fabric forecasts. These sources alert a product developer to new technology, fibers, blends, and finishes by providing descriptions, swatches, and sketches of possible applications.

Forecasters and product developers begin forecasting apparel styles about one year •

ahead of the retailing season. For them, inspiration for silhouettes and style details comes from a variety of sources. They gather information and research by attending fashion shows and trade events and by reviewing fashion news from online or print materials and from broadcasting sources. They also subscribe to trend services and design resources and shop the stores in fashion centers.

Analysis • Awareness • Color • Environment • Faith Popcorn •

Fashion forecasting methods •

Fashion forecasting process • First View • Information gathering • Interpretation • John Naisbitt • Long-term forecasting • Megatrend • Observation • Product development • Product evolution • Recognizing patterns • Short-term forecasting • Sociocultural context • Style • Synthesis • Textiles • Trade show • Trend analysis • Trend service •

Zeitgeist: the spirit of the time •

Questions for review and discussion

1. What demographic changes do you expect in the consumer market in the next five to ten years? What demographic groups will be dominant in the market? How will the demo- graphic factors influence future trends in the fashion industry, including apparel styles and consumption behaviors? How can the industry respond to these changes effectively? 2. Color has been identified as the most important design factor when consumers choose an

apparel style. Discuss the differences in color preferences across continents in the world (e.g., North America, Europe, and Asia). You can choose specific countries to compare if you prefer. In addition, compare the differences in preference across areas within the United States (e.g., the East, Northeast, West, South, Pacific Northwest, and Midwest). Provide some examples from your observations or experiences.

3. What will be the future of fashion forecasting? Will it be needed more or less in the future? Why? What will influence the level of need? How will the shorter fashion cycle affect fore- casting? Are there any factors that will make forecasting activities more or less difficult? Will the development of technology affect forecasting activities in the future? How? Do you envi- sion any changes in the trend forecasting business in the future?

Suggested Readings

Diane, T., & Cassidy, T. (2005). Color forecasting. Oxford, UK: Blackwell Publishing.

Kim, E., & Johnson, K. K. P. (2007). The U.S. apparel industry: Futuring with undergraduate apparel majors. Clothing & Textiles Research Journal, 25(4), 283–306.

Kim, E., & Johnson, K. K. P. (2009). Forecasting the U.S. fashion industry with industry professionals. Part 1: Materials and design. Journal of Fashion Marketing and Management, 13(2), 256–267. Kim, E., & Johnson, K. K. P. (2009). Forecasting the U.S. fashion industry with industry professionals.

Part 2: Production and retailing. Journal of Fashion Marketing and Management, 13(2), 268–278. Linton, H. (1994). Color forecasting. New York: Van Nostrand Reinhold.

References

Brannon, E. L. (2005). Fashion forecasting (2nd ed.). New York: Fairchild Publications. Diane, T., & Cassidy, T. (2005). Color forecasting. Oxford, UK: Blackwell Publishing.

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Lauer, D. A., & Pentak, S. (2008). Design basics (7th ed.). Belmont, CA: Thomson Wadsworth. Lee, C. (2009). An interview with Chungmin Lee, the CEO of First View Korea—PFIN by Eundeok Kim

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Szustek, A. (2009, February 4). J. Crew’s uptick: The “Obama factor” or recession-conscious fashion? Finding Dulcinea. Retrieved from http://www.findingdulcinea.com/news/business/2009/feb/ J--Crew-s-Uptick--The--Obama-Factor--or-Recession-Conscious-Fashion-.html

Urban Outfitters: Fashion victim. (2006, July 17). Bloomberg Businessweek. Retrieved from http:// www.businessweek.com/magazine/content/06_29/b3993067.htm

Wickett, J. L., Gaskill, L. R., & Damhorst, M. L. (1999). Apparel retail product development: Model testing and expansion. Clothing & Textiles Research Journal, 17(1), 21–35.

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