SPSS Analytics Partner | Case Study – Elie Tahari

Case Study – Elie Tahari

Solution Components

  • IBM SPSS Modeler
  • IBM Cognos
  • Other IBM Software

“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 combines fashion savvy with powerful analytics



To ensure that they have the right mix of products on the floor at any given time, apparel manufacturers and retailers have to not only sense changes in selling patterns, but quickly translate that intelligence into a series of co-ordinated decisions that go right up the supply chain. This means knowing when and how much to ramp up or cut back on the production of some styles, and for which sizes and colors. It means choosing the right mix of transport modes to balance the urgency of delivery against cost.


Business need

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.


To move data from its core applications to its data warehouse, Elie Tahari relies on a combination of IBM WebSphere® MQ, IBM InfoSphere® DataStage® ETL and remote journaling, a data replication function of the IBM Power Systems™ servers that run its core platforms. As an additional safeguard to ensure its transactional systems and data warehouse are in complete alignment, Nihad Aytaman and his team created integrity checking programs that compare key information elements between the data warehouse and the transactional systems on a nightly basis.



Ability 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. Both Elie Tahari and Tahari ASL benefit from faster and more intelligent decision-making through the availability of real-time sales, inventory and logistics information enabled by a “near-real-time” data warehouse design where all transactional data is updated within five minutes or less. Reduction in reporting cycle from two days to a few minutes.

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