Retail Analytics to mitigate fashion risk

An article in the Wall Street Journal, on September 8, 2013, titled “Fashion Industry Meets Big Data” ( describes the increasing use of analytics in the fashion industry to forecast trends. These forecasts provide estimates of demand by color, fabric and cut. The forecasters claim to use social network comments, fashion shows worldwide to generate the data. Retailers claim to use this data to be in sync with current trends, with such matching of products to current styles enabling profit benefits. As more retailers access the same data, will retailers continue to see similar benefits ? How can individual retailers maintain their unique styles even if industry consensus information is widely available ? As retailers move towards use of more current data, will manufacturers with domestic locations and thus fast delivery, become more competitive ?

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20 Responses to Retail Analytics to mitigate fashion risk

  1. Yuntao Guo says:

    The data collected by the forecasts can only serve as a reference not a guideline for the retailers. My assumption is that the data might only reflect some regions in the world with wider coverage of social network comments and fashion shows. And developing countries with large market might not follow these trends. So I think the local companies might have the advantage of understanding their market better.
    And for the link provided, I can not open the link without subscribe the Wall Street Journal. I used Purdue Library website to assess the article. Is it possible that Dr. Iyer can provide the name of the article? Thank you.

  2. aviyer2010 says:

    Yuntao – see the title in the revised post.

  3. Debjit Mukherjee says:

    As we gather and break down significantly more information about individuals’ associations, singular inclinations will turn out to be vastly improved known, more exhaustively and in more noteworthy point of interest than any other time in recent memory. That gives valuable insights of knowledge to the style business, from what items may perform best, all in all, down to what will probably offer well in which store areas, what items are effective when put alongside one another and how to improve retail encounters. In spite of the fact that there’s not a viable alternative for instinct in an innovative industry, enormous information unquestionably has its place in controlling youthful designers and real design houses alike in the right course for their next huge show.
    Inventory and price is going to turn out to be more straightforward, retailers won’t survive just by being “go through” dealers of brands. The more important challenge is to give purchasers motivation to pick their stores over rivals. Buyers will search out retailers that give esteem in new and diverse ways. The retailers have to offer profound item expertise and a remarkable item instruction. It will help the purchasers to understand how to utilize the items better. Also, it is important for retailers to be experimental such as providing the customers an opportunity to see how the garments look on them.This will also help in bringing more orders. Retailers should also make it easier for buyers to connect with when and how they need from their cell phones while they are at home or progressing. They can position themselves as the champions of style or interest in specific portions, for populace amasses that will drive retail spending. Crowd sourcing can be utilized for betterment of items allowing the shoppers to cocreate items with retailers. Competition is escalating and moving to new enclosures, and buyers are quickly developing their way to deal with buy choices.Quite clearly, manufacturers with domestic locations and faster delivery will become competitive.

  4. aniketgarg90 says:

    In short term in will boost the profits for retailers however for long term retailers need to make an effort to differentiate themselves. Fashion industry often involves creating fresh designs that may not be possible to predict using the Big Data.
    This opens us market for new players which can tap this market. One such way could be Crowd sourcing as done by threadless. In this context it will ensure fresh flow of ideas and a differentiating factor for the retailers.

  5. Rupesh Kumar says:

    Different industries are today taking the help of Big Data to increase their business by providing better product and service to the customers. Analytics being used currently to find out the needs of the customer and serve them accordingly. Fashion industry is about differentiating yourself from the others. In such a scenario its also important for the retailers to differentiate themselves in order to have a sustainable growth. Delivery is a very important aspect today for deciding customer satisfaction and the retailers which provides faster delivery are more relevant to customers, hence manufactures having domestic locations will become more competitive.

  6. Sarath Suresh says:

    The question we need to think before we get carried away with this Big Data current is to see as to how many of the population that shops are very active in social sites which enables these analytics firm to predict their shopping behaviour. I.I do not support the view that the individual retailers wont be able to maintain their unique styles once the data becomes public.It actually will make them more competitive in the kind of designs and styles they come out with which cannot be imitated and fabricated so easily.Shopping is all about the personal touch and if the individual retailers are able to maintain it in a good way,i dont see any reason as to why they should feel wary of the analytics in the background.They must take on the advantage of the availability of data and do a mixed strategy of using the data available online and what their designers feel and come out with the best of the products in the least possible time.

  7. deepakregu says:

    Analytics in the fashion industry definitely will help the supply chain become more agile, allowing them to take emerging trends live form the consumers as the season progresses, rather than follow industry consensus information. It gives dynamic insights on whether a particular product must be scaled up, discontinued or what should be the next variant to be made for sale. Individual firms can maintain their unique styles y deploying analytics at a local level with their own customer segment.

  8. Abhishek Lohiya says:

    This is nothing new. Information Innovations and operational superiority is available in every industry, but only a few are able to leverage it to have a sharp competitive edge. why?
    2 things are crucial here:
    1. i think in today’s world, its not data but its use that is more crucial here. In order to leverage this to the maximum potential, companies need to make sure the outcome of analytics flows across the supply chain and the commensurate steps are also visible to the entire chain. Only then the smooth coordination can be achieved in the entire play that shall
    2. Execution is the key. In execution its neither the speed nor the precision, but both. The ones who execute with speed and precision will make it difficult for others to catch up and, with heijunka they can beat the markets in this chase.

  9. Rohit Singh says:

    It is a quick dose of profits for the retailers but is not sustainable. They will have to have a point of differentiation in the future. New players coupled with a sound application of IT can enter this market.

  10. The huge amount of data will help the retailers in a better way to find their target customers and forecast more accurately. The apparel industry largely runs on marketing expense and cost of inventory is huge since the salvage value is very less compared to the original sale value of the product. Any information which helps in reducing the forecast error is a prized possession in this industry. As far as general consensus is concerned, every retailer will use their unique set of analytical capability to analyse these data to match their design. Most retailers are aware of their target customer group and repeat purchasers of their products, BIGDATA will help them in understanding their daily habit and purchase tendency and this will also help them better understanding the reason of purchase which may allow retailers to customize the deals for individual customers. Integration of Retailers sales data with manufacturers production planning will build capability in the manufacturer to adjust to the demand swing, more importantly, stopped producing no performing products.

  11. Shiv Kamat says:

    Fashion industry has already been using data such as which color sells more in which location and lining up their inventory accordingly, although it still remains to seen how much more can big data help in a industry which is not rules by mathematics but art, appreciation,design.

  12. Debajyoti Biswas says:

    One of the biggest needs for having a short design to sales cycle for apparel brands is the brisk rate at which designs become obsolete.Hence it is imperative to deploy analytics effectively to understand consumer tastes and stay ahead of the curve by re-inventing its offerings continuously.Also to insulate itself from supplier risks it is essential to have a spread out supplier base geographically in order to hedge against supply uncertainties.

  13. Kevin Morrisroe says:

    I do believe retrailers will continue to see benefits as this data is ever changing; styles are always changing, as well as demand. As time goes on, forecasting will only improve which will increase profitability. Retailers will maintain their unique styles by securing their own brands. It doesn’t matter if the industry has the same information as long as your unique brand in the store is following the trends. Consumers are very loyal to the fashion industry brands so it is securing a personal brand that will keep retailers profitable.

  14. Rahul Srinivas Sucharitha says:

    By accessing the same data, the retailers can use the data obtained as a means of reference and consider taking the necessary steps keeping in mind the area in which they are located and the current exposure of fashion which the location is following. Because, it could be possible that some locations do not follow the trend which the majority of the population around the world follow. Individual retailers can maintain their unique styles by localizing their branches to those locations where they experience better demands and higher profits. I do not think that the manufacturers with domestic locations would become more competitive anytime soon as the domestic areas follow a particular fashion trend and would take some time to get used to new fashion ideas and hence getting current data would not be so beneficial in improving the competitiveness of these companies.

  15. Qidi Cao says:

    In my opinion, in short term, it will be a huge profits for the retailers. However, in long term, this profits will not last if they continue with current styles. If they want to get profits in the future, they need to make a differentiation of their products and others. There are more aspects which are important to fashion industry other than the mathematics data.

  16. Greg Nichter says:

    I think the data collected through various media sites such as facebook and twitter can be valuable to fashion retailers. In particular, it would be interesting to see if the data can be categorized by location. Not all styles are the same across the country, so if forecasters were able to separate the data geographically, they could provide individual forecasts for each region. Big data could potentially lead to less product differentiation. To mitigate this, retailers could offer more products online, thereby requiring less products to be held in stores. Overall, big data could allow for better forecasts, while increasing the use of online shopping could prevent the loss of product diversity.

  17. Trey Christner says:

    As more retailers access the same data, retailers should see similar benefits if they use the data correctly and efficiently. Retailers that move toward current data will make manufacturers with domestic locations more competitive. Everyone will need to have short lead times or they will lose in the market.

  18. Tanuja B says:

    We have always seen a partcular fashion trend is in vogue for a particular period of time.For example there was a time when bellbottom pants were in style and then skinny jeans came into style. The difference now is that manufacturers can realise the various trends faster with the help of technology and can accordingly react to it. No matter what data they have in hand, the way of interpreting and implementing it is different for every manufacturer and herein lies their uniqueness.The material used or the brand name is also something that consumers keep in mind when they are purchasing clothes. So the common set of data wont prevent different retail stores from being unique.
    Zara for example always follows the latest trends and they change their collection every 2 or 3 weeks unlike other retailers. Other retailers launch their new collection only twice or thrice a year which keeps them behind in the competition.

  19. Amanda Dyson says:

    Retailers will continue to benefit from the use of analytics to better match supply with demand. Even though the information is readily available industry-wide, retailers typically serve different markets within the same industry. Different customers are looking for different types of clothing, so demands will be different in separate markets (i.e., Nordstrom and Forever 21 target different customers). I would anticipate that as retailers move towards use of more current data, manufacturers with domestic locations will start to have the capability to offer quicker delivery times. This could lead to a competitive advantage for domestic apparel companies, depending on what their business’s core competencies are. Perhaps some companies, such as Zara, are not concerned with long lead times and the ability to meet demand. They offer such a wide variety of products that customers expect a lot of variety in small quantities to be available. Therefore, Zara would not be as concerned as other companies might be with current/real time data being available.

  20. Yuwa Sun says:

    Instead of “forecast the trend”, I would say applying data into fashion industry is more of “catch the trend”. However, I don’t agree with Amanda’s comment on Zara. I interned with Zara, and actually the stores fill up their inventory every hour. In that, lead time plays an important role in fast fashion. Though Zara has many complimentary goods within its store, the nature of fashion is the unique elements. So, having domestic locations will result in a more concentrated and flexible chain model.

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