New Look Makes Fast Fashion Even Faster

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New Look Makes Fast Fashion Even Faster

By Masha Zager - 07/01/2014
Starting from a single store in 1969, the British firm New Look has become a $2.5 billion retail powerhouse specializing in fast fashion. With nearly 600 stores in the UK (about half its total store count), the company is the No. 1 value retailer for under-35 women’s clothing and accessories in that country and holds leading positions in other categories. It operates internationally in 23 countries and is expanding rapidly into China, Poland, Russia and Germany. Its e-commerce division, which serves 120 countries, is in hockey-stick-growth mode, with sales more than doubling in the past two years.

New Look prides itself on responding instantly to fashion trends, boasting a typical 10-week turnaround from design to shop floor — an achievement made possible by a global supply chain and a deep understanding of what its customers are looking for.

In terms of getting the right merchandise to the right stores at the right time, New Look is leading the trend. For seven years, the company has used Quantum Retail’s Q platform for allocation and replenishment, and over that period it has continued to find new ways to use Q to boost its profits.

Carolyn Mackenzie, New Look’s buying, merchandising and design director for women’s clothing, explains that New Look originally used a simple replenishment system. Essentially, she says, the system operated on a “one-in-one-out” rule: Whenever a store sold an item, it would receive another item irrespective of how quickly it sold or the need of other stores. This system worked well enough when the New Look stores were all similar in size (small) and type of location (downtown shopping streets in British towns).

In 2005, New Look purchased 33 stores from the distressed retailer Littlewoods — the first of several acquisitions — and suddenly found itself with much more store variety. Littlewoods stores were several times larger, on average, than New Look stores, and they were typically located in malls rather than downtowns. The old, one-in-one-out replenishment rule no longer made sense when stores varied so widely. “That’s where replenishment became a massive deal,” Mackenzie says. “Part of what we changed was how we optimized stock.”

Trusting the black box
New Look began seeking an allocation and replenishment system that could serve a growing, changing company, and it decided to take a chance with Quantum Retail’s Q. At that time, Quantum Retail was best known for its work with guitar distributor Guitar Center, and its system had never been used in the apparel industry. “There was some nervousness about whether clothing would be like the other industries,” Mackenzie says, “but we loved their demand forecasting model. It’s much more efficient — it didn’t just overallocate and allowed much less user intervention.” The model allocates inventory based on each store’s historical performance — for example, certain items might be more likely to sell in a large store or a large market.

With help from Quantum Retail, New Look divided its products into categories, each of which had a different demand model. High-fashion items are bought in small quantities and minimally replenished. Continuity products are expected to sell for six to nine months and must be continually replenished with minimum stock holding quantities. Seasonal fashion products are expected to have a life expectancy of eight to 16 weeks. Q is able to apply different rules to each type of product.

The biggest challenge in implementation, according to Mackenzie, was a cultural one — learning to “trust the black box.” Previously, teams of buyers, merchandisers and assistant merchandisers developed their product ranges each season and made a financial plan and allocation plan for each product. Each team had an optimizer who made adjustments to the original allocations as needed. The teams had an intuitive sense of how different products sold in different stores, and they were surprised when Q disagreed with their judgments. “They would ask, ‘Why is Q telling me this?’” Mackenzie says. “But every time we dug in, we found the analysis proved to be correct.”

The company decided to “take the emotion out of” allocation decisions and moved all the optimizers to a centralized group to make them independent of buyers and merchandisers. Interestingly, the optimizers haven’t been made redundant by the new allocation and replenishment system; in fact, as they mastered the intricacies of Q, their jobs became more highly skilled. For example, they can temporarily override the system, to allow extra orders for special events, and then bring it back in to do its allocation job. Optimizers can also explain to buyers and merchandisers why a store may be out of stock for a particular product. (Answer: another store could sell that product faster.)

Changing business practices
Analyses from the system allowed New Look to change its business practices and improve its profitability. One example involves poorly performing items. Rather than pushing these items out to all the stores, forcing them to keep marking the items down, New Look now allocates these items to its e-commerce site —which has a wider range of customers — and to a few large stores where customers are more likely to look for bargains.

The traditional small stores no longer have to keep sale racks crowded with unwanted merchandise, and they have more room for new, full-priced merchandise. “Visually, these stores are better, and we’re getting through the reduced-price stock more effectively,” Mackenzie says. Overall, discounts are less steep than they were (in the future, New Look may improve discounting even further by using the system for markdown optimization), and the lifecycle of marked-down merchandise has been reduced by three to four weeks. In addition, the company saves the cost of shipping merchandise to stores that can’t sell it effectively.

Even more significant, New Look reduced its initial orders, cutting back the value of its inventory by £70 million to £80 million. Instead of overstocking its stores in its initial allocation and waiting for a week to see which stores needed to be replenished, the company now sends smaller quantities in the initial allocation and waits only three to five days to make replenishment decisions. The system can learn in a very short time how the individual stores are performing and replenish different stores at different frequencies.

Mackenzie explains, “Our model now is to be quicker and take the stock out — it’s more profitable and effective.” Selling out of a line quickly is no longer considered a problem, she says, “as long as I have a new line to replace it with.”
She adds, “That’s what’s great about this — you can react and change. That’s why Q has lasted seven years for us.”

Masha Zager is a New York-based Apparel contributing writer specializing in business and technology.

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