Data analysis in the fashion industry

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Moda es analisis de datos-gabrielfariasiribarren.com

Big data and analytics in fashion.

I finished the previous post with these questions to which I have added the answers we will analyze in this new article.

What competitive advantage does an online sales platform have over traditional brands to “produce fashion” and be successful?

Their competitive advantage is mainly the large volume of business information and the results they can arrive at in the subsequent data analysis.

Why will this new model alter the cycle of fashion and change forever product creation and its supply?

Because it changes the fashion cycle from an “offer-based demand” to a “demand-based offer” model and the product creation goes from a “prospective design” perspective to the “predictive data analysis”.

Why will a large portion of the fashion industry –most likely—focus on trends defined by these platforms and their brands?

Because they are creating and manufacturing what is being sold today, at this very moment; they satisfy the consumer’s needs instantly. That is the goal of each and every fashion label today.

Moda es analisis de datos-gabrielfariasiribarren.com

Data Analysis.

As we analyzed in the previous post, the digital client is shrewd and intelligent, demanding a greater effort when it comes to keeping up; by being “always on”, they have become more technological, more sophisticated and more unpredictable.

This is how the textile fashion industry, in pursue of the goal of immediacy to satisfy the desires of the “new digital consumer”, has created and developed the process of predictive data analysis. Using this process plus breakthroughs in demand forecasting, by extrapolating current sales, we can predict what will sell tomorrow. It makes it possible to predictively create and manufacture different styles and to efficiently move stock through the business network.

Using business data analysis and customer profiling it is possible to make wise, fast and agile decisions regarding current, specific needs in terms of products and services, such as models, types of washing, colors and delivery and return options; as well as to improve the efficiency of inventory and distribution, reduce lost sales and improve profit margin. Data is also used to identify problems and develop adequate solutions and improvements.

These prediction tools have reached a high level of maturity and they will change the traditional way of designing, purchasing, distributing and registering clothing and fashion items.

The new model of demand-based offer.

Data analysis creates a shift in conception and manufacturing from an “offer-based demand” to a “demand-based offer” perspective where brands and retail reduce the volumes of initial purchases and their inventories and instead create season production cycles based on real sales at the stores and through the online channel.

This new model gains greater significance when we see the trend of current fashion consumers of “see now, buy now” which involves being able to instantly purchase the designs seen during a runway show.

We are talking about a change in the fashion cycle that seeks to meet expectations created by a much faster pace that provides “immediacy”, instant gratification of the customers’ wishes.

With data analysis, it is highly possible that creativity will be circumscribed essentially to the creation of trends. From that point forward, the contribution of data analysis is used to react to what is selling today instead of defining what will sell in the future through prospective design.

More value in the supply chain.

Moda es analisis de datos-gabrielfariasiribarren.com

We can then deduct that emphasis is placed on the entire supply chain, from design to manufacturing, through shipping and, finally, the purchase experience. This process requires a strong commitment from all stakeholders, from one end to the other of the chain, in order to defy what is already established, to manage, change and execute.

In detail, there is a strong dependence on efficient, collaborative partnerships with usual suppliers, who are under increasing pressure to develop designs and prototypes with tighter deadlines and to improve their manufacturing processes to manage smaller initial orders as well as to respond faster to short-notice reorders. The shift will be towards a more versatile, agile development model to achieve the necessary swiftness.

In order to make this new model successful, textile labels and companies need to strategically invest in innovation and technology in their internal processes, and especially in their supply chain.

This is the topic we will discuss in the next article.

Until next time! Thank you!

This article was also posted in my blog at Modaes.es

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