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TechUPDATE Ganesh Subramanian, founder and CEO, Stylumia Why just relying on our memory in fashion Business can impact revenues and profits adversely? Fashion business is one of the most challenging businesses, where there are lots of moving objects and one is expected to hit the target, in fact, hit it most of the time, that too trying to predict the target well ahead of time. This is like hitting a moving target with the target not in sight. 84 January 2017 APPAREL&Fashion
TechUPDATE In our interactions with many buyers and merchandisers in the industry, both in <strong>India</strong> and abroad, we have found a very practical challenge in placing bets on the fashion products. Typically, a brand or retailer reviews the past data to look at at a higher level what worked and what did not. These insights are in terms of fitting, price, washes, style, etc and that goes as an input to future buys. A very important thing to note is that buying is finally initiated on a product, which is a set of aesthetic values which the consumer would perceive. Here is one of the many cases we have encountered. You can try on yourself or you may ask the same question to people in your organization. We asked one of the members What colours work? What colours do not work ? What works in t-shirts? The person responded “Dark colors like black and blue”. Note: Image from Stylumia Insights Platform Great. We then asked, what in dark colors worked? He said “Bold prints ” We then asked what in black and blue does not work? There was a bit of silence. There is a genuine problem here all of us face, we remember what works most of the time at a fine level. When we search for what does not work at that same level, we do not necessarily remember. You can try this with any category and set of attribute combinations. When we studied the data of the organization using our capabilities of computer vision, machine learning, what we found was for every set of products that worked in an attribute combination almost equal amount of products that did not work. If this reality is not alive in the people who make buying decisions that too at real time, we will continue to make the same pattern of error. As you can see in the picture above we can see same hues of colours sitting in working and not working. Unless insights come with this contra view, we will keep drawing narrow conclusions. Another challenge in fashion is interpretation of what we see. We describe fashion products using attributes. Let us take for an example one of the key attributes i.e colour. If through normal analytics one has to come up with what works in colour, we would say dark blue contributes to x% of business and does well and light pink which is y% and does not do well. This is an insight which is not at all actionable. Colours at RGB level are only actionable. There is a short coming of traditional analytics and also practical difficulty of a human to remember at the aesthetic level that too combinations of attributes what works and what does not. We see an incomplete knowledge chain. Today’s advances in technology like Computer Vision enables us to see the data in fashion like human eye and capture all of this in a form which is easy to take decision which is relevant and also real time. Imagine you can see insights of your brand by product category, with multiple attribute combinations over seasons, store, region and with aesthetic intelligence all in a single page so intuitive that from a store sales person to CEO will have same ease of access and knowledge becomes democratized for decision making. All this for what? Keep making products your consumers love always!! Embracing technology to enable decisions which take us close to customers will set us ahead of the pack in this ever competitive marketplace. The article is contributed by Ganesh Subramanian Founder & CEO Stylumia Intelligence Technology Private Limited. He was also the CEO of Myntra.com APPAREL&Fashion January 2017 85
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