In a largely seasonal and fashiondriven business such as Kellwood’s, traditional forecasting and replenishment methods don’t always apply.

 

The St. Louis-based maker of Sag Harbor, Phat Farm and other midprice apparel labels had been working with 7thOnline Assortment Planning for three and half years to help maximize sales at first price.

 

But the amount of data and quantitative analysis involved in determining the optimal size allocation by style by store is complex. The calculations of the size distribution are often oversimplified, not taking into account the price, revenue and margin impact of missed opportunities, stockouts in particular sizes.

 

Prior to adding 7thOnline size optimization technology, Kellwood didn’t have the tools to fully analyze the enormous amount of POS data now available at retail to be able to tailor assortments by door.

 

“We didn’t have a sophisticated means to take large amounts of data by retailer door or SKU and come up with the best size optimized recommendations for our retailers,” states John Davis, director of retail analysis and planning systems at Kellwood.

 

“Not all retailers have these systems,” he adds. “I think it’s moving in that direction, but somewhat slowly.”

 

FAST FACTS

Headquarters: St. Louis, MO

Number of Brands: 30+, including owned and licensed brands

Brand Names: Baby Phat, Democracy, Hanna Andersson, Koret, My Michelle, Phat Farm, Prophecy, Sag Harbor and many more

2006 Sales: $1.96 billion

2006 Net Earnings: $31.4 million

 

Getting to POS data at the local level
Before 7thOnline, Kellwood’s sizing process essentially consisted of buyers’ determining the size ratio and purchase quantities of sizes by groups of stores. This strategy did not incorporate size differences by geographic location or local demand.

 

As a result, Kellwood often missed sales opportunities due to early size breaks in hot styles. On the other hand, Kellwood would incur excessive markdowns due to overstocked sizes in styles seeing weaker demand.

 

“We felt we could improve so we looked for a way to do that,” says Davis, speaking at a session at the recent NRF convention.

 

Through historical POS analysis and proprietary optimization algorithms, 7thOnline size optimization determines lost sales by store to create “corrected size ratios” by door. The algorithm then uses these corrected size ratios to create unique “size profiles” for each door, and then assigns each door the optimal size profile based on the client’s preferences. Finally, it creates a recommendation to allocate the assortments by size by door.

 

For case pack styles, the algorithm determines the optimal size mix for each pack size and the optimal distribution of available case packs to each store.

 

“Kellwood’s challenges are not too different from [those of] any manufacturer or retailer today that must deal in size-based assortments,” says Ben Lentini, director of implementation services at 7thOnline. “The issues of reducing size breaks and high end of season markdowns have led all manufacturers and retailers to the same objective: Maximizing sales and gross margin.”

 

Setting size strategies
Data cleansing and developing size strategies, according to Lentini, are some of the most important steps in the process. In developing size strategies, the algorithm assigns a predetermined number of size profiles to each door based on the door’s deviation from their original size profile.

 

A client can then explore “what if?” scenarios to see which lead to maximum sales at regular price. For instance, to determine what works best, the client may test using three unique size profiles across its stores; it may use five.

 

“Depending on the scope of the project, engagements can be accomplished within six to eight weeks of the receipt of the data,” says Lentini. “Once completed, a series of reports is developed to analyze and interpret the optimization results.”

 

7thOnline finds that its clients can reduce size breaks up to 15 percentage points and increase full-price sell-through up to 14 percentage points — leading to higher revenue and gross margin contribution.

 

Bob Copeland, principal at Kurt Salmon Associates (KSA), who also spoke as part of the NRF presentation, believes size optimization is a “valuable part” of KSA’s ACT Vertical model that calls for retailers to optimize across the supply chain and integrate functions rather than focusing on traditional supply chain areas.

 

For retailers, according to KSA, getting more involved in design, development, manufacturing and distribution of goods is necessary to meet the needs of a more demanding consumer whose tastes are changing faster than ever.

 

Managing inventory flow optimally
But while the calculation of the optimal sizes is a critical piece to size optimization, Copeland says it is equally important to decide how to flow and manage that inventory throughout the chain.

 

“How am I going to handle the order management?” asks Copeland. “How do I get that into the retailer’s system and how do I communicate that to the factory? So from a [purchase order] perspective, you have to look at both the initial order and then later that distribution order as they come into the process. All those need to be considered as you execute the size optimization.”

 

Copeland says this has become somewhat trickier because some larger retailers continue to increase crossdocking, in which seasonal assortments are packed at the factory, and pass through the warehouse without being unpacked before being shipped to the store. Procedures also have to be set up for the standard pack and ship model, whereby either pre-pack or open stock is flowed to the retailer.

 

KSA feels the optimal model is a hybrid one where packing is done by door for the initial assortment push at the factory that is crossdocked to the store. Then a buffer of open stock is shipped to fill in missing sizes, with either the retailer or branded supplier holding back the inventory. Finally, the remaining inventory is flowed using optimal sizing technologies by store in what Copeland calls a “push pull push model.”

 

Copeland elaborates: “So what happens is the initial order is pushed and then sizes are optimized, and then that hold back is used to fill in based on the actual local selling by size. And then as you get to the end of the season and you’re getting ready to do price breaks, you’re doing an optimal push of that last remaining inventory if you have any left.”

 

Encouraging retail reaction
Davis says Kellwood is enhancing its systems to take full advantage of size optimization to improve handling of pre-packs, and working with retailers to help them execute size-optimized assortments in their processes and systems. The initial response from retailers has been encouraging, he says.

 

“During market when we presented our assortment plans to several large retailers it was received very positively,” says Davis. “One large retailer indicated that they in fact were developing new planning systems to take advantage of size optimize technologies themselves. Another retailer gave us what you could consider a backhand compliment — but a compliment nevertheless — and indicated that they were surprised that we were that sophisticated.”

 

Concludes Davis: “We feel in-stock and markdown optimization will become the norm in developing assortment plans for fashion items.”