Elie Tahari combines fashion savvy with powerful analytics

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1 Elie Tahari combines fashion savvy with powerful analytics Harnessing predictive technologies to match production with customer demand Smart is... Extrapolating 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. 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 enable 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. 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. It can even mean ordering scarce fabrics months in advance to ensure there s enough on hand when it counts. The fabric of decision-making Since its foundation in 1973, New York-based 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. 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.

2 Business Benefits 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 decisionmaking 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. 30 percent reduction in supply chain and logistics costs. Reduction in the proportion of shipments sent by air freight from 80 percent to less than 50 percent through improved visibility of production schedules and customer orders. Increased sales and stronger margins due to an optimized mix of products on the shop-floor. Time the enemy The inherent inefficiency of this spreadsheet-based approach was only the beginning of the problem. The broader issue was the limitations it placed on Elie Tahari s decision-making. Data generated by the company s core systems could take as long as two days to analyze and present in a format that managers could easily understand and act on. In addition to timeliness and transparency, these reports were mostly static, high-level overviews, which lacked the granularity managers needed to make optimizing decisions. Nevertheless, meeting commitments to retailers, and doing so on time, every time, was a challenge of overwhelming importance for Elie Tahari, especially when retailers were running special offers or promotions. To minimize the risk of late deliveries, managers often decided to transport new stock into the country by air freight which is around three times the cost of standard shipping just to be safe. For store replenishment decisions, the lack of granularity in the reports made it impractical for managers to fine-tune the product and size mix they shipped to each customer or outlet based on differences in sales patterns from store to store or region to region. That all changed when Elie Tahari implemented IBM Cognos Business Intelligence for realtime reporting. A close look at TREND Inside the company, the reporting solution is known as TREND (Tahari Real-Time Environment for Data). For Tiffany Tankersley, a divisional manager in charge of sales through Elie Tahari retailer stores, it didn t take very long to see the benefits of TREND. Tankersley had previously followed the practice of ordering the same distribution of Smarter Predictive analytics boosts product availability Instrumented Interconnected Intelligent Real-time information on sales, inventory and shipments is captured directly from Elie Tahari s core transactional systems, and combined with historical data from the company s data warehouse. Transactional information from five core platforms is integrated into a single reporting framework. A suite of business analytics tools provide real-time insight, predictive analysis, and detailed planning capabilities. Real-time visibility into store-level sell-through and inventory data enables optimized replenishment and merchandising practices, while predictive analytics enable highly accurate production planning, lower-cost logistics and more efficient inventory management.

3 Solution Components Software IBM Cognos Business Intelligence IBM Cognos TM1 IBM SPSS Modeler IBM DB2 for i IBM InfoSphere DataStage IBM WebSphere MQ Servers IBM Power 550 Express Services 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 clothing sizes for all stores less by choice than by practical necessity and was delighted by the new degree of insight provided by TREND. What jumped out from the Cognos reports were the differences in the distribution of sizes we sold by region and by store, explains Tankersley. By seeing a pattern we couldn t see before, we were able to modify the size spread for each of our stores. In addition to ensuring that the hottest products are on the shelves when customers want them, such smart replenishment practices have a big impact on the bottom line. Stocking the right mix of products right down to the size reduces requests from retailers to discount slower moving products within the line, thereby maintaining margin strength. By the same token, reducing the volume of returns cuts the considerable costs associated with reverse logistics. Elie Tahari is also making smarter decisions further up the supply chain. With visibility into production, inventory and location becoming more transparent and up-to-date, logistics managers have the information they need to optimize their shipping strategies. Since Elie Tahari began using TREND to support its logistics decisions, the share of shipments sent by air has fallen from 80 percent to under 50 percent all without impacting its ability to fulfill its on-time delivery commitments to retailers. Adopting predictive analytics With the success of the TREND solution, the company decided to extend its use of analytics further, and introduce a new predictive analytics solution for a key area of its business the Tahari ASL women s business suit product line. Nihad Aytaman, Director of Business Applications, explains: 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. Aytaman s team realized that a combination of predictive analytics and demand planning technologies could provide an ideal way of meeting this challenge. As a result, Tahari ASL decided to build a new solution based on IBM SPSS Modeler and IBM Cognos TM1. From the predictive analytics point of view, there were various canned solutions on the market that might have helped us with this specific project, says 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.

4 The ability to look four months into the future and know what our inventory levels need to be on a weekly basis is absolutely key to our success... It allows us to adjust production to a level that reduces our exposure and still gives us the ability to supply our customer with close to 100 percent of their orders. Nihad Aytaman, Director of Business Applications, Elie Tahari Tahari ASL now feeds three years of historical sales data for each item into SPSS Modeler, which generates a sales pattern curve that smoothes out anomalous demand spikes and can be extrapolated into the future. The company uses the first 12 months of this future projection as a consensus plan, which is input into the company s Cognos TM1 demand planning model. By mapping other inputs including future open orders, current production and current inventory against the consensus plan, and adjusting for any unforeseen factors such as stores opening or closing, TM1 provides target inventory figures to meet anticipated customer demand levels for up to four months in the future. The ability to look four months into the future and know what our inventory levels need to be on a weekly basis is absolutely key to our success, says Aytaman. Our production cycle in the Far East can take three months, and we have a one-month cushion to adjust for any problems. He adds: We were confident the predictive model would work, but what we ve been really surprised by is its accuracy. Although individual weekly predictions showed an occasional swing between 60 percent and 120 percent in accuracy, the aggregate annual predictions were extremely close. To take an example, looking at one of our products, the average variance between our predictions and the actual number of items sold in 2011 was less than 2.5 percent. In raw numbers, we predicted we would sell 175 of the garment in size 18, and we actually sold 174. We predicted we would sell 40 in size 24, and we actually sold 38. If the model was any more accurate, I d be using it to play the stock market! he adds jokingly. Ultimately, this ability to predict demand with such a high degree of accuracy enables Tahari ASL to meet its customer s needs in terms of stock availability while maintaining very lean inventory levels. The future prediction allows us to adjust production to a level that reduces our exposure and still gives us the ability to supply our customer with close to 100 percent of their orders, says Aytaman. Agility in fashion To Aytaman, Elie Tahari s smart retailing practices have been an important factor in the company s consistently strong growth and more recently have been instrumental in its ability to adjust its offerings to suit economy-driven changes in consumer tastes. Elie Tahari has always combined a visionary sense with a keen eye for changes in fashion trends, says Aytaman. 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.

5 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 The Inside Story: Getting There Right the First Time... When Elie Tahari s CIO first proposed using analytics to simplify, unify and speed up the reporting of key metrics, there was little doubt as to the underlying demand for it among employees and the significant potential benefits to the business as a whole. But for all the promise of improved reporting, the Elie Tahari IT team which took on the implementation in-house recognized the risks and took every means to mitigate them. Data integrity was at the top of the list, explains Nihad Aytaman: Together with Sam Gottlieb, our BI manager, we recognized that our success depended on convincing people to accept a whole new foundation for making their most critical decisions, and that the only way to do this was to gain their complete trust in the accuracy of the data from the start. You really have one shot at this; if you put information in front of users and it s not correct, it s very difficult to win them over again. Ensuring Integrity... 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, 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. Pace is Everything... Elie Tahari s decision to roll out dashboards, reporting and analysis capabilities throughout the organization on a department-bydepartment basis was in part a reflection of its lean IT resources. But it also reflected Aytaman s conscious decision to focus time and effort on nurturing adoption on a relatively small (i.e., department or workgroup) scale, thus encouraging a deeper level of buy-in among that group s users. Part and parcel of this approach was the decision to deliver only the most important reports in a preliminary deployment stage, which shortened the time required to make the most important reports available through Cognos company-wide. With this initial footprint established, Aytaman and his team then doubled back to round out the implementation, completing the initial rollout in just six months. By spending as much time as each department needed [in the first phase], we succeeded in making people feel like IT was giving them its full attention, says Aytaman. This really helped adoption to take hold.

6 About IBM Business Analytics IBM Business Analytics software delivers data-driven insights that help organiz ations work smarter and outperform their peers. This comprehensive portfolio includes solutions for business intelligence, predictive analytics and decision management, performance management, and risk management. Business Analytics solutions enable companies to identify and visualize trends and patterns in areas, such as customer analytics, that can have a profound effect on business performance. They can compare scenarios, anticipate potential threats and opportunities, better plan, budget and forecast resources, balance risks against expected returns and work to meet regulatory requirements. By making analytics widely available, organiz ations can align tactical and strategic decision-making to achieve business goals. For more information For further information or to reach a representative please visit ibm.com/business-analytics. Copyright IBM Corporation 2014 IBM Corporation Route 100 Somers, NY Produced in the United States of America April 2014 IBM, the IBM logo, ibm.com, Let s Build A Smarter Planet, Smarter Planet, the planet icons, Cognos, DataStage, DB2, Global Business Services, InfoSphere, Power Systems, SPSS, TM1 and WebSphere are trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at Copyright and trademark information at This document is current as of the initial date of publication and may be changed by IBM at any time. Not all offerings are available in every country in which IBM operates. The client examples cited are presented for illustrative purposes only. Actual performance results may vary depending on specific configurations and operating conditions. It is the user s responsibility to evaluate and verify the operation of any other products or programs with IBM products and programs. THE INFORMATION IN THIS DOCUMENT IS PROVIDED AS IS WITHOUT ANY WARRANTY, EXPRESS OR IMPLIED, INCLUDING WITHOUT ANY WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND ANY WARRANTY OR CONDITION OF NON-INFRINGEMENT. IBM products are warranted according to the terms and conditions of the agreements under which they are provided. Please Recycle YTC03447-USEN-02