Integrating Systems to Right-Size Inventory

A tight economy is forcing apparel manufacturers and retailers to operate more efficiently if they want to uphold customer service and retain a loyal customer base. Eager to achieve this goal, The Haggar Clothing Co. recently transitioned from manual planning and forecasting processes to a centralized, integrated solution that will optimize inventory based on shopper demand — a move that also will help the manufacturer lower its inventory levels and increase turns.

Dallas-based Haggar has spent 86-plus years building its reputation as a leading men’s apparel brand, and those efforts continued even when the company went private five years ago. The manufacturer most recently reported revenues of $300 million. To sustain this growth, especially in the wake of a volatile economy, Haggar began taking stock of how to streamline operations.

Embarking on corporate-wide restructuring
“Two years ago, we embarked on a corporate-wide restructuring,” explained Jean Nelson, the manufacturer’s senior vice president and CFO. “We decided to shutter a variety of under-performing operations and divisions, and refocus efforts on our core business of men’s apparel. This was the basis we needed to drive more efficiency and best serve our shoppers.”

To deliver this service, Haggar began looking internally at how it merchandises product to retail partners. Being a “heavy replenishment-based business,” according to Nelson, the company was ready to re-engineer its planning and forecasting processes.
The first step in its transition focused on sourcing. While it procured a lot of materials from the Western Hemisphere, rising costs pushed the company to establish more cost-effective sourcing partnerships in the Eastern Hemisphere. Simultaneously, the company began evaluating the complexity of its planning functionality as it relates to creating and storing inventory.

“Since all manufacturing is outsourced and we are dealing with a variety of partners and long lead times, we have a level of complexity to our planning,” she explained.

Non-integrated technology was exacerbating the complexities of the operation further. Planning and forecasting were manually conducted on a combination of Excel spread sheets and homegrown systems. “We created a demand plan in Excel, then fed that information into our proprietary inventory planning solution, then another homegrown system completed time-phased analysis which was fed into sourcing and supply chain solutions,” she recalled. “The systems were not integrated and disjointed, which caused a huge disconnect.”

Besides supporting a complicated inventory management process, Haggar was also subject to high inventory levels — levels that at times could be higher than industry standards. “Managing inventory was becoming more complicated and we also knew there were opportunities if we could optimize product levels based on shopper demand,” she said. “We knew we needed the right tools and skill sets enterprise-wide to better manage these operations.”

Seeking connectivity
Before hitting the marketplace, Haggar explored how to centralize planning and forecasting processes. The company knew “connectivity” was imperative to reaching its goals, so it made sense to find a supporting solution — a comprehensive, integrated option that could act as a bridge between supplier partners and its end shoppers. It also wanted the new solution to be cost-effective. For Haggar, the Voyager Inventory Planning solution from Atlanta-based Logility fit the bill.

The centralized solution is integrated within the manufacturer’s financials system, as well as its enterprise resource planning suite so all information between the technologies will be shared. Planners and buyers are the main users of the solution, however a streamlined planning process makes it easy for other company divisions to view data as well.

Users start the process by importing historic information about previously placed orders and shipments, point-of-sale movement data, and supplier information — all details that provide the Logility Voyager solution suite a baseline to analyze and predict future demand, seasonality trends and a variety of other factors. Next, the system allows users to manage inventory and set specific time-phased policies. The configuration also allows companies to analyze inventory levels based on specific factors, such as investment, desired customer service levels, the addition of new retail channels or store locations, a new product line and even potential or estimated changes in consumer demand.

Then, Voyager’s replenishment planning software provides visibility of future demand, corresponding product and material requirements, and the actions needed by suppliers to satisfy demand. Built-in performance management capabilities analyze the data against the initial benchmarks and desired corporate goals to give the company full visibility of demand, inventory and supply across your supply chain network.

These inventory plans are updated weekly based on new information such as orders and shipments, and the technology continually creates new plans based on the new data imported.

Companies can also set safety stock levels and replenishment quantities, either by individual item, or by allocation for specific retail locations. A predictive engine analyzes the data against the initial benchmarks, and creates demand plans that give the company full visibility of inventory from demand through delivery to retail partners.

These inventory plans are updated weekly based on new information on placed orders and shipments, and the technology continually creates new plans based on the new data imported.

“In the past, we managed this entire process on spreadsheets,” Nelson explained. “With Logility, we have an integrated solution that uses information from demand and inventory planning, and communicates this directly to the supply chain, all within the centralized system.”

Smaller inventories, more turns
After choosing the solution in the summer, Haggar hired Jian Zhu as its vice president of planning and forecasting, who spearheaded the implementation of the solution. Logility was slated to go live last month.

“Once the solution is in place, we expect to lower our inventory levels, which will increase our turns,” said Nelson. “First, we expect to lower on-hand inventory by 50 percent. By carrying product that will turn based on demand, we can increase our sell through. Currently our inventory turns twice a year. With the new solution, we expect turns to rise to the four-plus range.”

Haggar expects to achieve these levels within six and 12 months, respectively, she added.

The new solution also promises to help the manufacturer get a stronger handle on margin expectations. “Because the software is integrated with our financials and ERP systems, we expect to get better control over financial forecasts, and translate this information to gain better control over margins,” she said.

Once Haggar has a handle on the solution internally, the company plans to apply its functionality to vendor managed inventory operations. In a typical VMI scenario, retailers and suppliers collaborate on merchandise demand. By applying solutions, such as Logility, to the mix, Haggar will be able to use retailer demand information to forecast and maintain correct inventory in the supply chain, and deliver optimal inventory levels across retail partners’ business channels, both in-store and online. It is considered a “shared risk” proposition because both parties are sharing sell-through information, and want optimal levels available at the store level.

By creating sales forecasts based on more accurate product movement information, there is less chance of out-of-stock or over-stock situations at the retail level. The process also reduces inventory levels across the supply chain, which frees up capital on both the retailer and supplier sides that is often tied up in non-moving merchandise.

“We consider VMI to be a competitive advantage, and we expect our retail partners to be open to this option,” Nelson said, adding that Haggar hopes to embark on the project in early 2012.

Deena M. Amato-McCoy is a New York-based journalist who covers retail technology.

systems at a glance

 • Enterprise Resource Planning: BlueCherry (Computer Generated Solutions)
 • Forecasting and Demand Planning: Logility
 • Financials: Solomon Software
 • Business Intelligence: QlikView
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