Fashion oriented analysis and business intelligence: how to keep the clothing business leading?


Fashion oriented analysis and business intelligence: how to keep the clothing business leading?

In a connected digital world, unprecedented access to information and data has changed the way fashion and clothing companies do business. Companies that do not use technology to improve processes, streamline operations and generate the analytics and reporting necessary to run data-driven businesses have fallen behind. In companies that recognize the value of using analytics and business intelligence (BI) to make decisions, the competitive advantage is attributed to organizations that do not have the opportunity to refine their business into precise science.

When the digital paradigm shifts, the fashion industry is not behind. Many companies have responded well by adopting new technologies, seizing new opportunities, reaching well-informed customers and improving business at all levels. But the influx of information will only intensify competition, as brands fight to share in an increasingly busy world.

New technologies proved to be only half the battle. Understanding how to apply new data is becoming a new battleground. In fact, on average, fashion companies lag behind relatively similar industries in using business analytics tools. In addition, on average, companies that use the most business intelligence have a 54 percent higher operating margin than those with lower adoption rates. [1]

Today is an essential tool for gaining competitive advantage is the correct analysis and business intelligence, learn how to convert data into information can be used to improve business operational, fashion and clothing leaders how to maintain its leading position in the competition.

Analyze data and measure key performance indicators.

Business analysis has become an absolute necessity for today’s fashion and clothing companies. Without analysis, companies in this industry simply cannot remain competitive. Fashion is an industry that constantly changes itself, different styles, changing colors and materials. Keep the top, rapid change and the changing trends and fashion need to understand how to use the data and analysis, strategic KPI and how to convert it into actionable intelligence to promote better business.

How to obtain accurate and applicable data from ERP technology?

Electronic forms or basic traditional enterprise resource planning (ERP) software will not generate the valuable information needed for fashion or clothing business to remain competitive in today’s digital economy. The next generation ERP technology can handle a large amount of data and can be used in a centralized system, thus providing a complete version of the truth. In addition to the various aspects of supply chain and organization, ERP software should be able to enhance the visibility of styles, colors and dimensional parameters. Other enterprise clothing technologies, such as product life cycle management (PLM), manufacturing workshop control and EDI (electronic data interchange), further realize the large-scale management of key data and analysis.

Actionable consumer data.

Modern ERP software data can help companies better understand their consumers and markets than ever before. Manufacturers, importers, buyers and retailers now have the opportunity to really understand the market through in-depth understanding of consumer demand and buying behavior. In addition to ERP data, companies should also focus on social networks to gain insight into the market response to specific products, trends, brands, and general business strategies.

Predict and analyze trends in fashion.

The analysis and understanding of the science behind the trend is a valuable asset in a trend style and fashion driven industry. As business intelligence and analytics continue to advance, they have created new ways and tools for the industry to better determine which clothing should be produced. They also provide opportunities for fashion and clothing companies to create, support or promote trends. But predicting sales and market reaction and demand for certain styles or SKU can reduce waste and increase revenue.

Business intelligence data can also inform smarter product development. By using data driven understanding of historical trend data, and integrating current data of popular clothing, we can design and develop products that will attract more consumers over a longer period of time.

Fast fashion

Some trends may continue, and some styles will have more staying power than others. However, some trends will come and go in the blink of an eye. However, these fleeting trends are sometimes more valuable if companies know how to use analytics to exploit peak demand, which can be very powerful.

Fast fashion, a design quickly transformed into a number of channels, continues to become more and more important in the industry. In addition to adapting to popular demand, fast fashion has introduced a convenience that is popular among consumers. Zara, one of the leaders in the field of ready-to-wear, is able to keep its latest models at a reasonable price by rapidly moving popular clothing to the supply chain. According to Forbes, technology, production coordination and streamlining of the supply chain enable brands to shorten the procurement cycle and provide fashionable clothing at the right time. [3] prediction analysis, historical data analysis, well-organized production, centralized operating procedures and efficient information exchange make fast fashion possible.

How to stay ahead

Whether using the fashion business intelligence and analysis to predict and forecast trends, or use of the existing trend, data and intelligence to change the style to remain competitive in the industry are indispensable. In order to keep the fashion trends change constantly, fashion and clothing companies have to take additional steps to determine how best to apply their consumers, are now available to business and business data. This is the key to increasing operating margins, increasing revenues and staying ahead.


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