In my opinion: manage the innovation leap to fast fashion, says Intelligence Node

How can retailers deliver what customers want as quickly as possible? For Sanjeev Sularia of data analytics leader Intelligence Node, the prize of fast fashion can only be won by better use of technology


Sularia: pricing and data hold key to getting fast fashion right

Fast fashion: the way brands like Zara, H&M and Forever 21 can get the latest super-desirable catwalk goodies to their shelves faster than their competitors.

Fast fashion is a term that came to prominence about 10 years ago but which is only now coming to (profitable) reality. “Fast fashion may be the most important disrupter in the retail industry today,” says one vendor that claims to help brands do just this, Chainge Capital, while Tommy Hilfiger claims it can make catwalk fashion instantly available to buy online.

The idea of moving merchandise to the retail space as quickly as possible has galvanised the entire global retail industry. Consumers love the idea, as they see it as a way to get the latest in fashion without waiting for months – a love shared by retailers, as it helps the bottom line (for example, self-proclaimed fast fashion leader Zara reports much reduced use of markdowns since items arrive “just in time,” and with a speed guaranteeing demand and quick turnover).

But fast fashion’s actually quite a challenge to deliver. That’s because of the stress it puts on what can often be global, highly extended, supply chains, the obligation on manufacturing to be as lean and hyper-efficient as possible, and the retailer to be as nimble as possible to pull it all off.

Lag is only acceptable if you like slow fashion

So while Zara and other fast fashion Leaders have co-ordinated production and streamlined the supply chain in order to capitalise on the trend, the rest of the retailer community is playing catch up.

Let’s consider the bottlenecks we need to get rid of to help the retailer community reap the same benefits. First is the fact it’s taking too long to change pricing structures (what does pricing structure refer to here). Our insights into the US retail ecosystem – based on real-time, comprehensive data feeds – reveals that the average e-commerce site takes an astonishing 43,000 minutes to make a price change. That’s just under a month – roughly 29.9 days – on average. It’s even worse in offline, where the average is more like an astonishing 270 days, a factor of 10 times slower.

Clearly, though, no matter how fast you might get a designer item on your site off the runway, if you can’t keep your pricing relevant to market and consumer expectations you are still one step behind. Today’s consumer highly values availability and price comparison, making them ‘hyper aware’ of the wider state of the market. That’s why Amazon has invested in technology to make it highly responsive to price fluctuation, investment that means it can make a pricing change to counter competitor or consumer movement in two minutes, thanks to superior, but not magical or unattainable, technology.

The first fast fashion lesson has to be if technology can make you as competitive and faster than anyone else in the market, it will help you get to the fast fashion destination. The next lesson is around getting a proper handle on your inventory.

The issue here is that the price optimisation and retail analytics industry hasn’t serviced the fashion world as well as it has the grocery sector. Data analytics is weaker in our sector than others, due to lack of standardised product taxonomy for SKUs, hobbling attempts to better classify and sort items across sizes, colours and design elements across all the fashion categories our users (consumers) want to work with. To make things worse, when the same product – say a white shirt – has different product IDs, brands, shades of white/colour, fit, size, and so on, in the system, or the job’s been made even more complicated by retailer-specific Unique Product Codes instead of brand SKU ids, then the database is even more cluttered and opaque than before.

Let’s take one innocuous looking word: ‘beige’. A lot of items people buy are in this colour – but did you know there are actually multiple definitions of beige? Last time I checked, I counted 30 in supplier systems, from ‘fawn’ to ‘creme’ to ‘nude’ to ‘camel.’ Your system needs to be granular enough to be able to work with this complexity, but in ways that make it very simple to manipulate the data to get the results you want.

Omni-channel is a major part of this story too

Putting that together, the second lesson is that we need better, sharper ways of understanding our own data if we want to get any chance at all of working at the speed fast fashion demands. The third and final obstacle, I think is the need for a single view of inventory, something I think is all-important in retail.

Especially if we are sincere and in earnest about delivering omni-channel. A single view of inventory would at a stroke give you the power to serve the same customer across any and all of the channels they choose to buy from you, giving them the option to buy the same product, in a variant of their choice, at a consistent price, across all those channels.

Fast fashion is a powerful, compelling way to work with your consumer. But to manage the powerful, disruptive forces it unleashes, as a switched-on retailer you need to take a close look at the way you work with your pricing and data strategy if you want to get there.

The author is founder and CEO of Intelligence Node, Inc (, a New York and Mumbai-based retail analytics leader that is highly active in the global fashion sector.

(A Retail Times’ sponsored article)