Top Apparel Companies Transform Their Processes with Business Intelligence

What’s very much in fashion these days? Diving deep into Big Data to extract actionable insights and make smarter decisions — faster. Top retailers are turning to business intelligence and analytics solutions from software leaders to streamline business processes and serve the customer in our very digital world.

Women’s intimate apparel brand Maidenform made a serious investment in business intelligence in 2012, laying the groundwork for SAP HANA in October and going live in January 2013. CIO Bob Russo says the company looked for a solution that focused on information visibility, speed of delivery and access from any device, as mobility plays a greater role in employees’ professional lives. Providing targeted information at the right place and time is central to improving the decision-making process, according to Russo.

“This would allow us to gain a competitive advantage in the marketplace as well as increase retail customer, shopper and shareholder value,” he explains. “We want to make sure that we are able to deliver ‘one version of the truth’ and deliver information that is actionable. We do not want to just deliver data.”

In addition to SAP’s robust business intelligence toolset that includes dashboards, Explorer, Crystal reports, Web Intelligence and OLAP tools, HANA gives Maidenform the super-fast speed it sought. “We are accessing 2 billion records of POS data in less than three seconds from our databases via our SAP BI tools,” explains Russo.

What’s more, Maidenform selected a platform that would help to create structure through a corporate governance model, thus enabling the company to reengineer processes, organizational roles, policies, and to offer the enhanced benefit of focusing on teamwork across the enterprise. “The idea is that the whole is much greater than the sum of the parts,” Russo says.

Instead of merely delivering reports, Maidenform initially identified the key questions that the business needed to ask and subsequently designed the data, information structure and relationships required to answer those business questions. For example, one of the most challenging questions — “In order to adjust our supply chain in a timely fashion, what is the relationship of our supply and demand at the SKU level for our retailers who send us POS data?” —  requires Maidenform to scan and compare massive amounts of retail POS data from retail customers to information from its supply chain flow of product at a SKU level.

“With the speed of SAP HANA and BI software, we will be able to point out discrepancies between our supply and demand at a SKU level,” Russo says. “This allows us to adjust our supply chain at the earliest possible time and react quickly to changes in consumer demand. It also will result in reduced inventory levels and higher-quality customer service.”

Maidenform’s business intelligence initiative also focused on building a streamlined, targeted dashboard structure for its executive team, identifying the most significant KPIs that reveal how the business is running — or will be running in the future. After creating a vertical and horizontal dashboard structure to deliver that information, Maidenform also outlined the measurements and acceptable ranges of performance, with unacceptable ranges designed to trigger alerts. “Measurements are extremely important in order to continuously improve,” explains Russo. “How do you know where you are and how far you have to go if you don’t measure?”

The company deployed SAP BI-HANA enterprise-wide but started its initial “Stand Up BI-HANA” project with building supply chain reports. Next, the company created four cross-functional teams within the business: the executive team, which primarily needed access to dashboards; supply chain; finance; and sales. Each of these groups focused on one holistic set of cohesive information flows and definitions throughout the company.

While Maidenform still is in the very early stages of leveraging the BI platform, the company has made some progress to transform its decision-making processes. Russo points to the brand’s suite of “shipping information” reporting as a prime example. Using data from BI-HANA, Russo’s team built the suite for the executive team’s weekly shipping meeting. In the future, he says, the meeting could be run using BI-HANA interactively in place of just looking at reports.

Today, employees spend less time generating reports and more time productively engaged with their core responsibilities. And according to Russo, Maidenform now has increased visibility into information that was “hidden” to the business prior to the BI-HANA dpeloyment.

Russo believes in-memory platforms hold the potential to revolutionize the information flow throughout the world. “With this technology, speed is no longer an issue and many pieces of information — past, present and predicted future — can be connected together to enable computer systems to deliver information and shape the world’s information flow like nothing anyone has seen before,” he says.

As omnichannel retailing becomes a greater business focus, Russo says SAP BI-HANA will help Maidenform improve its relationship with always-on customers. “The ability to proactively communicate and market to our mobile consumers — wherever they are located — and direct them to ‘On the spot, best path, best quality, and best price to purchase’ can only be accomplished with the speed of HANA,” he explains. “There are many points of huge data and information volumes that need to be scanned from all our channels in order to meet the true omnichannel view.

“The speed of In-Memory with HANA will give us the ability to deliver this capability to the business in the future,” adds Russo.

Charming Charlie tackles data
With more than 250 stores around the United States, Charming Charlie has become a staple in many malls, offering a staggering breadth of women’s accessories and apparel organized by color to facilitate the shopping experience. In early 2013, the company deployed Manthan Systems’ Retail Analytics software to help manage and provide insights about its 25,000 active SKUs. It launched a phased rollout in the spring, beginning with planning, merchandising, store operations, corporate and merchants, adding allocators and district managers to the on-premise platform by the end of summer. Charming Charlie uses the product essentially out of the box, with a few unique configurations specific to its business processes, according to director of IT applications Jay Nayak.

Like many retailers, Charming Charlie left behind a complicated system that relied on Excel spreadsheets in favor of Manthan’s easy-to-use analytics platform. The retailer manages products at the color and attribute level, and Nayak says the SKUs are maintained by both the merchants and the sourcing team. “Our biggest challenge was creating consistent rules at the class and department level so everyone across the board has all of the same information,” she says. “We were very particular about naming conventions.”

Whereas team leaders previously looked at 50 or more reports on a regular basis, with Manthan’s platform, Charming Charlie needs just 10 to 12 key reports. According to Nayak, users now create one view of the data that begins at the department level and then drill down to SKU level to find what they’re looking for, so instead of creating three separate reports, they need just one. That kind of “ad hoc analysis” saves considerable time, she says.

The transition to Retail Analytics already is accelerating business processes. Users have reported finishing marketing analysis in just a few hours that previously would have taken three weeks. And instead of having to research an issue for a CMO following a team meeting, one employee was able to pull up the BI tool and address it on the spot.

What’s more, the Retail Analytics implementation has created positive effects in other areas of the business. “Improved inventory management comes as a byproduct of being able to make better decisions, access to mobile reporting and having consistency in the data,” Nayak explains.

With SAS analytics, leads marketing across the enterprise
In the three years that has been using SAS’ analytics platform, the retailer has seen its email unsubscribe rate plunge by 20 percent year over year. “That shows us that we’re on the right path,” says Kerem Tomak, vice president of marketing analytics and CRM for “The unsubscribe rate essentially tells us we’re oversending emails, or we’re not relevant enough, or we’re not capturing the right propensity for the customer to purchase.”

As such, has emerged as the digital marketing and promotional arm of Macy’s, Inc., running a wide variety of segmented and targeted email promotions on a daily and weekly basis. “SAS is helping us on many different fronts, from data preparation and manipulation to data processing to the modeling and optimization techniques that we’re using,” Tomak adds. uses SAS not only to build models that score each customer and her likelihood of actually making a purchase but also to ensure that email campaigns are the most relevant to that individual customer, providing the best offer and the best product at the right time.

While has offered free shipping for purchases of $99 or greater, Tomak says his team is testing to see if shoppers would respond to shipping waivers at other price points, based on data. The free shipping initiative is more of a retention policy and less about new customer acquisition, ensuring that shoppers keep coming back for more.

However, free shipping does play a larger role for Macy’s, Inc. “As we get to a more omnichannel strategy — which is one of our most evolved and most important strategies today — in ecommerce, you can return products to the closest store, so free shipping does play a role in supporting traffic to brick and mortar,” Tomak says.

And in the store, Macy’s is interested in learning how customers are using their ever-present mobile devices. “We see a whole different way of interacting with the brand through these devices,” explains Tomak. “A lot of things happening around a store can be influenced by the way the mobile phone is used by the customers to find and buy products while they’re in the vicinity of the store.

“A lot of analytics is driven by understanding what customers are looking for at the geolocation around the store so we can serve the customer while they’re in the vicinity,” Tomak adds.

The retailer sees smartphones and tablets as distinct channels, largely due to how consumers use and travel with the devices. While tablets are used much like laptops — while watching TV on the sofa at home, for example — smartphones go everywhere with consumers these days and are much more critical to product research and purchasing. Tomak says that his team is interested in adding mobile app capabilities beyond allowing customers to scan products to see what other colors or complementary styles exist on the website.

Today’s fashion shoppers often want to build a head-to-toe look for themselves — either by visiting a Macy’s store or a competitor’s shop — and Tomak says giving customers the ability to mix and match the retailer’s styles with those from a competitor will be a compelling feature. “Giving the customer the opportunity to reach into existing inventory through dot-com will be a powerful capability for us,” he says. “It’s empowering the customer to see what we have in whatever channel.”

Jessica Binns is a DC-based Apparel contributing writer.
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