Big data concepts and applications

Big data is a new frontier in innovation, characterized by vast data sets that require extensive computer processing to spot trends, and improve productivity. The ability to gather such data sets and effectively translate them in to strategy is seen as a new way of competing and innovating (Manyika et al., 2011). My area of interest is fashion, an area where creativity remains more important than data processing. Yet, big data is having an impact on the mainstream fringes of the fashion business.

For example, mainstream retailers are seeking to acquire more data points from their customers about a variety of different variables, and use those data points to more accurately meet the market's needs. Each season, millions of dollars' worth of merchandise goes unsold, to be sent to discounters at a fraction of the expected cost. This creates waste in the economic system of both the producers and retailers. Hence, many companies have begun to turn to big data in order to reduce this waste.

Social networks are one of the most important gathering points for the data used in the fashion industry, with designers and retailers gathering public opinion about clothes almost instantly, and using that information to change the cycle of clothing development. Whereas the old cycle would begin with a runway show seen by relatively few, with clothes that would be developed into ready-to-wear, by adding feedback from consumers, fashion companies have much more feedback to work with. This can help them to shape their designs for the coming season, and alter production plans accordingly. The result is that production is better aligned with the demands of the marketplace (Trites, 2013).

Other startup companies are seeking to gain a niche in the fashion world by using big data in order to develop clothing such as bras that have a better fit than conventional bras. Again, the competitive advantage derives from having more feedback data points that would normally be used in something like bra development. But by learning more about the needs of women, the designer is capable of developing bras that fit more women better than the current designers in the market (Deamicis, 2013).

Only in the past couple of years has this drive to use big data as a source of competitive advantage existed in fashion, but its impacts are already being felt, as large firms like Burberry and Oscar de le Renta are using big data to enhance their offerings (Trites, 2013). The more companies seek to utilize data in design, the more they will be attractive to consumers, by meeting their design needs. In addition, the use of data to improve the production function is something that will help all designers eliminate waste. By making fashion companies more profitable, there will be more money available to invest in more data, creating a cycle of competitive advantage. Furthermore, by gathering immediate feedback on runway exhibits -- or taking exhibits off the runway altogether and going straight to social media, fashion companies put themselves in a position of being seen as more fashion forward than their competitors, because they have fewer poor performing items.