All of that doesn’t even account for the fickle customer, who is evermore careful about shopping choices in difficult economic times. Fickle goes especially with retail fashion, which is where upscale retailer Elie Tahari serves the market with ready-to-wear designs and fashion accessories for men and women. The privately-held company operates 17 retail stores and outlets and also sells its brand through high-end department store chains including Saks.
Retooling the Warehouse
Merchandisers, buyers and retailers all need to keep a close eye on what products are moving at which locations and why. So, faced with the usual business penalties of batch updates and slow, cumbersome reporting cycles, Elie Tahari has instituted a data warehouse that updates information every five minutes.
The solution is based on IBM Cognos business intelligence products running DB2, with an operational data store (ODS) and data warehouse running in a separate logical partition of the company’s M50 model iSeries server. The data warehouse employs DB2's relational database with star schema and dimension tables, and serves to aggregate data from four disparate transactional applications used to run the business.
“Extracting those systems to one area lets us control what goes in and gives us that single version of the truth across all areas of the business,” says Nihad Aytaman, director of business applications at Elie Tahari.
Aytaman attributes the response time to the dimensional modeling, which he says the Cognos business intelligence platform works well against. In fact, the same system is accessed in retail stores by a Web interface to perform lookups for customers whose size or style might be out of stock at a given location.
Organizational Benefits
The greater intent of the IBM Cognos platform is to provide a more timely and proactive view of performance across all the divisions in the company. “It is completely rolled out and heavily used by finance, production, customer service, sales, merchandising, accounts receivable and payable, you name it,” Aytaman says.
For example, regional sales managers are able to see what’s selling on the floor and adjust their buys based on very current data. “One of our regional managers told me that as soon as the system went up she realized we were not buying correctly across size levels per store,” says Aytaman. “Before, they had ordered the same size breakdown for all stores.” While the customer would not notice, they’re now more likely to find the sizes and styles they prefer at their location. This is a great improvement for stocking and logistics that also reduces returns.
The data warehouse is also accessed to support a variety of management meetings where sell throughs for different styles are calculated. These reports are accompanied by visualizations of what is making its way into and out of the stores.
“Because we’re in the fashion business, there are a lot of pictures in the reports and sales especially likes to see different views based on their need,” says Aytaman.
Merchandising runs what are called line sheets almost every day with different versions showing availability of styles by size. These can be exported to Excel or PDF.
John Hagerty, an analyst at AMR Research says his retail clients face separate challenges in the back office and front office of the business. “The back-office issue is around merchandising, what products are selling, where are they selling, what are the price points and what they need to order.” Hagerty says this has become “a really big requirement” for retailers who are desperate to optimize their products for demographics and tight economic times. “Retailers have always done this but it’s very tough right now, so they are pushing the envelope.”
The front-office challenge is store operations, labor-oriented work derived from point-of-sale-type information. “There is a lot of verifying of metrics at the store level to see the effectiveness of different locations and how to raise revenue per store per square foot to support your overall mission,” says Hagerty. “As such, a multi-mode retailer like Elie Tahari has much more control over what happens in their own facilities than in the channels.”
As it turns out, this is precisely the case at Elie Tahari, where data on channel sales through department stores is also rolled up for reporting. But, less than optimally, the channel partners provide this via electronic data interchange (EDI) 852 data, which is batch updated on a weekly rather than a daily basis.
Customer Interactions
At Elie Tahari, all Cognos inquiries, including those at the store level on an internal network, run only against the data warehouse. As mentioned, the IBM Cognos system is also tapped to support customer relationships at the point of interaction, perhaps to look up a store location stocking a style or size not available locally. Where this process used to take several minutes, Aytaman says results are now returned in five to 10 seconds.
Customer service using a data warehouse is a use case that different analysts see as more or less unusual. Hagerty says he’s come across very few businesses using a data warehouse for discrete retail interactions. “Then again, when you haven’t unified your systems on the back end, this is a place where you can do it.”
Analyst James Kobielus of Forrester Research has seen businesses accessing the data warehouse in this manner. “It makes sense from the point of view that they don’t have to invest in dimensional databases and build cubes and maintain them,” he says, and also requires less hardware and software spending and fewer DBAs with better lifecycle TCO.
