Executive summary

For more than four decades, New York-based fashion house Elie Tahari has become a prominent global fashion brand, with hundreds of millions of dollars in revenues across 40 countries.

Its experience illustrates the hobbling effect process silos can have on agile and coordinated decision making—an effect amplified by the growing complexity of its supply chain. That chain begins with suppliers in Asia, from which Elie Tahari sources the majority of its clothing, and extends to a large network of retailers that includes Macy’s, Saks Fifth Avenue, Neiman Marcus, Bergdorf Goodman and others, in addition to its own chain of 35 stores and over 600 boutiques around the globe.

“With the real-time insights enabled by IBM business analytics software, we’re better able to translate our fashion market savvy into smart practices at every level of our business.”

Nihad Aytaman
Director of Business Applications, Elie Tahari


Elie Tahari needed to unify their primary sources of data into a single, coherent, and complete sytem.

Elie Tahari found assembling the information needed to make key decisions an arduous and time-consuming task. The primary sources of data were the five separate systems that the company relied on to run its business, as well as standardized product activity transaction reports it received from its wholesale channel.

To unify these sources into a coherent and complete picture of the situation, employees in various departments had to manually collate and analyze the data using spreadsheets. Only then could managers make such basic decisions as which products to ship to each store, which items to order from suppliers, and how best to bring new shipments in from overseas – to name just a few.


Elie Tahari needed to extrapolate historical sales patterns to predict customers’ future demand for each product – right down to the sizes and colors required.

To enhance decision-making and keep pace with customer demand, Elie Tahari needed faster access to more actionable information – not only about current production and inventory, but also about future demand.


“Tahari ASL was running a special program for one of the largest department stores in the US. They wanted to be able to keep a full size range of women’s business suits in-store, so that they would never be out of stock. To help them achieve this, we had to be able to supply them any item in any size or color, whenever they asked for it. Initially, we tried to manage this using spreadsheets, but it was just too complicated – so we began to think about how analytics could help.”

Nihad Aytaman
Director of Business Applications, Elie Tahari


Elie Tahari used a suite of business analytics software from IBM to create a seamless real-time reporting framework and introduce highly accurate, predictive demand planning capabilities.

Real-time insights on sell-through rates and predictive management of production planning and inventory enabled Elie Tahari to optimize store-level merchandising decisions, ensuring that the most popular stock-keeping units (SKUs) are available in the right place, at the right time.

“From the predictive analytics point of view, there were various ‘canned solutions’ on the market that might have helped us with this specific project,” said Aytaman. “But we were keen to invest in a platform that would give us the flexibility to meet other needs in the future. SPSS Modeler, combined with IBM’s pre-built solution blueprints, gave us the freedom and rapid development capabilities we were looking for.”

Solution Components


  • IBM® Cognos® Business Intelligence
  • IBM Cognos TM1®
  • IBM SPSS® Modeler
  • IBM DB2® for i
  • IBM InfoSphere® DataStage®
  • IBM WebSphere® MQ


  • IBM Global Business Services®

IBM Business Partner

  • Adaptive Solutions
  • ITS, Inc. (NY)


“ What jumped out from the Cognos reports were the differences in the distribution of sizes we sold by region and by store. By seeing a pattern we couldn’t see before, we were able to modify the size spread for each of our stores. ”

Tiffany Tankersley
Divisional Manager, Elie Tahari


Elie Tahari enhanced decision-making and managed to keep pace with customer demand.

After implementing the IBM solution, Elie Tahari was able to predict customer orders for the Tahari ASL women’s suits business four months in advance with better than 97 percent annual accuracy, enabling Tahari ASL to optimize production and guarantee full availability of its products while maintaining very lean inventory levels.

The company also managed a reduction in the reporting cycle from two days to a few minutes, as well as ensures a 30 percent reduction in supply chain and logistics costs. The solution also helped reduce the proportion of shipments sent by airfreight from 80 percent to less than 50 percent through improved visibility of production schedules and customer orders.

This all added to Elie Tahari’s increased sales and stronger margins due to an optimized mix of products on the shop floor.

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