Merchandising, Planning, Allocation: New Recipes for Success

— April 01, 2003

Throw in a cup of point-of-sale (POS) data, add a pinch of optimization, stir with some collaboration, and what do you have?

If you've done everything right, you probably have a recipe that has greatly improved your traditional methods of determining what apparel products and how many to purchase, where to allocate them and when to mark them down. Most likely, your recipe takes advantage of one of the many software solutions on the market that enables retailers to crunch billions of points of data to make detailed decisions on a store- and style-wide level, rather than generalized assessments about chain-wide performance.

Indeed, apparel retailers and brands are challenged more than ever in today's competitive environment to take advantage of their historical sales information and process it into useable chunks of data to improve such business practices as forecasting and inventory planning - and ultimately the company's bottom line.

Moreover, apparel firms are being challenged to cater to their customers on an individualized basis while still operating from centralized systems and processes that are more efficient but have distanced the merchants from learning about who their customer is and what she wants. The need to drill down to the store level and serve the individual customer has led some retailers to rethink their business practices and the way that they approach their planning processes, while new software solutions have enabled new philosophical approaches to become reality.

The Birth of a Plan

Traditionally, apparel retailers have approached the planning process from different perspectives. Some don't go much farther than establishing a basic merchandising plan that meets the budget set forth by the company's financial plan. Others drill down to assortment planning, allocation planning and classification planning, while others have taken things to store planning, space planning and even style/SKU planning levels.

Typically, merchandisers have made decisions based on a combination of intuition and a generalized use of the company's historical sales data. Most merchandisers work in averages, using chain-wide POS data to make determinations about purchases, allocations and assortments for upcoming seasons. For example, merchandisers typically make assortment plans based on store clustering strategies, which identify groups of stores based on such factors as demographics, highest sales and store size, without being able to look at the particular quirks of individual stores and how their markets may respond differently to product assortments.

Why? Simply put, it is not humanly possible for a merchandiser to keep track of and process the millions and billions of points of data that are produced from the sale of each item in each store. The merchandiser is "only one person and can really only look at [planning] in a very broad way, and not get very granular with store-level decisions or even clustering decisions," says Carrie Johnson, retail analyst with Forrester Research.

But with the aid of new technology solutions on the market, retailers have begun to take greater advantage of the repositories of extremely detailed data they have at their fingertips.

Drilling Down: Store and Space Planning

Take Gadzooks, for instance. The trendy juniors retailer was stocking inventory based on sales receipts, without forecasting for each store based on its individual needs, explains Tim Wenzel, director of store planning and allocation. While Wenzel is quick to assert that the company wants "to make sure that our merchants are still merchants" and that technology cannot predict what's going to be hot, he said he has found that technology can go a long way in the area of allocation and store planning.

In fact, during the past year, Gadzooks has established a store planning department and has focused on bridging the gap between planning and allocation through the use of STS' suite of solutions, which include Connected Retailer Merchandise Planning and Connected Retailer Allocation.

The system has given the company more flexibility to allocate using its storehouse of POS data. For instance, the company can look at sales by time frames or styles - store wide or an individual store level. To determine the viability of a new style of jacket, says Wenzel, the company can review the sales data from a similar jacket during a particular period. "Not everything is driven at a higher classification level," he explains. Moreover, the ability to drill down to "lower levels" on a weekly basis has allowed Gadzooks to react early and quickly, which is particularly important for styles that have shorter life spans, he acknowledges.

Gadzooks' foray into store planning also has provided more flexibility to consider stores on an individual basis with respect to space planning and presentation. The company can now plan for faster merchandise turns in some stores over others, or add square footage or density standards into the variable mix. "What we've been trying to do is visit some of these subjective questions and objectify them a little bit. Then we can almost go back and prove what may have done a better job of predicting future sales," he explains.

From an industry-wide perspective, store and space planning are becoming increasingly popular components of the overall planning process. Big M Inc., the parent of juniors specialty chain Mandees, off-price designer Annie Sez and accessories chain Afaze, is evolving into this area with a passion. The company, which uses JDA Software Group solutions, including Arthur Allocation, and also has several of its own home-grown solutions for planning, has created a module within Arthur to take space planning to the next level.

Frank Zarrello, director of planning and allocation, explains: "Just because a store can house 10,000 units doesn't mean that 10,000 units is what we need to have there. Unfortunately, in the real estate world, real estate space does not equal volume, meaning that just because you have 'X' amount of square footage, it doesn't mean you're going to do 'X' amount of volume."

In other words, a small store may far outpace a larger store in terms of sales volume, and it's important that "you don't just fill shelves for the sake of filling shelves," says Zarrello. Looking at space in terms of productivity, rather than square footage, means the company places inventory where it will produce the greatest gross margin.

Consequently, display space has also taken on new significance. By utilizing its space differently, the company can impact the number of units that will fit into a store by as much as 20 percent. "We can use different types of fixtures to give us the desired number of units in the store without affecting the presentation," says Zarrello.

"We could actually have two identical stores [in square footage] that have totally different amounts of inventory. One could have 20 percent more than the other, but it has different types of fixtures," he says. And that all goes back to the fact that one store produces faster turns and better returns than the other.

Big M approaches all of its planning processes with the same philosophy. As Zarrello puts it: "Everything supports the sales plan." One plan doesn't dictate the other, and all plans integrate with each other to form the basis of the overall plan. "This integration is key to the planning process," he adds.

Another great example of this integration can be seen in the company's payroll plan, which uses Arthur and, like its space plan, is linked to sales. In other words, labor hours are scheduled at the same time that sales are expected. "We've broken down the sales plan by day and by week for each store, coupled with hours-needed, to support the plan," he says.

Optimization Evolution

Such intense efforts to maximize resources and gross margins while minimizing costs and inventory can be summed up in one word that has recently taken the industry by storm: Optimization.

Michael Stanek, CFO of Northern Group Retail, a $225 million Canadian retailer of women's and kids' apparel, likens the retail industry of today to the manufacturing industry of the late '70s and early '80s, which "was really focusing on efficiencies and increased productivity and gross margins and quality management and all of those great acronyms that [helped] to increase profitability."

In that vein, while Forrester's Johnson notes a big trend toward networking systems and automating spreadsheet-intensive processes, she adds: "What's much more exciting is what's going on in the optimization space, [where] you're building plans and assortment at the SKU/store level . making much better use of the data that retailers have from POS and transaction logs, that a human simply can't sort through."

Particularly popular of late in the optimization arena is markdown optimization, which has brought about a "dramatic shift in the way retailers conduct their business," she says.

Stanek concurs. The private branded retailer, which used to be owned by Footlocker, has undergone a major "mindset change" since its September 2001 change in ownership. "Gross margin is really what creates value and pays the bills," says Stanek, noting that there are many opportunities within the framework of the company's business to create additional efficiencies and profitability - "to optimize our current operation," as he puts it - before taking investment dollars to go after additional growth.

"It's not just about merchandise anymore," says Stanek. "If you add an analytical or scientific component to your merchandising process, you can do two things. You can minimize risks in the event of a bad buy or economic downturn, and you can also maximize potentials if you're hitting everything head on."

Putting this philosophy to work, the company implemented ProfitLogic's Pricing4Profit solution. To hone its operations so that the markdown optimization software wasn't a "radical change," Stanek explains, the company first adopted a new motto within its planning and allocation departments: Out means out.

This new strategy has made it possible to use the solution effectively - Pricing4Profit makes recommendations based upon fixed out dates that the company uploads into the system - and has brought new discipline to the company's planning processes. The company no longer does "packaways" (storing unsold inventory to bring out the next year), nor does it extend its out dates.

Moreover, "big wins" have come in the form of greater accountability for buyers - they buy what they're relatively sure they can sell - and substantially lighter inventories, says Stanek.

He elaborates: "When we look at a buy - as opposed to just saying: 'I bought $100,000 worth of this product last year and I want to have a 5 percent comp so I'll buy $105,000 [worth]' - we'll actually look at that and say: 'How much was sold at full price? How much at a deep discounted price?' Maybe the optimal buy isn't the $105,000. Maybe you'll generate more gross margin dollars by only buying $80,000, because you had to give the last 20 percent away."

As part of its strategy to maximize operations, Northern is also about 15 percent of the way through the process of upgrading its CRM and merchandising systems, putting in new platforms from STS for both. The company has a "pretty significant loyalty program," but while it knows how much its customers spend, it's not really sure what they buy," Stanek notes.

"We want to know that a customer came in and bought blue pants at full price," he says, adding that ultimately, the company hopes that its new systems will enable it to move into SKU planning by cluster.

Like Stanek, Big M's Zarrello says he believes that price optimization is an important part of the entire planning process. Currently, the company makes markdown decisions based on its own study of historical data, but the company is looking into solutions such as those offered by ProfitLogic and Spotlight Solutions, he remarks.

Markdown optimization is tricky business, and taking a scientific approach can be enlightening, says Zarrello. Historically, buyers have had full charge of markdowns, and because of their tendency to have an emotional connection to the apparel, "they don't really want to mark something down until they see it slow down." But this reactionary approach is often too late to be effective, explains Zarrello. By the time the markdown goes into effect, the hype has already passed.

"Markdown optimization teaches you where you are on the lifecycle [of a product] and allows you to become more proactive in achieving desired sell-throughs," says Zarrello. "Sometimes you have to give the merchandise a little push when it's in the peak demand period." This allows you to end the season with cleaner inventories, while protecting gross margins, he explains.

Collaboration: Taking It Up a Notch

There's another area that's ripe for optimization, and that is the relationships that retailers have with their supply partners.

After all, if the information is available, why not push it as far back into the supply chain as possible? Why not let your data work for you?

That's just what American Pacific thought. The company, a wholesale distributor in the home textiles market, is in the process of implementing 4R's software into its business structure to help better analyze large amounts of POS data from its retail customers, which include Linens 'n Things and Saks Department Store Group.

"We identified a business need to improve forecast accuracy," says Gary Gleckner, director of information services. Realizing that the company was not taking the best advantage of POS data, it turned to 4R's suite of solutions - RightTestT, RightBuyT, RightPlanT and RightDataT - which utilize POS data for much of their algorithms and mathematical computations, Gleckner explains.

"The 4R tool allows us to better analyze larger amounts of point-of-sale data, and their software provides an easy-to-navigate user interface that allows us to look at summary information, or drill down to more closely analyze specific stores or product performance," he notes. Using the solution in conjunction with its own information allows the company to generate meaningful data for itself and its customers.

"When you aggregate everything up to a chain level, you can miss key things," says Gleckner. "Being able to analyze information at the store level can be really enlightening."

In fact, the solution has been so helpful that American Pacific was able to convince Linens 'n Things to adopt it as well. The two companies now work collaboratively to more closely plan product introductions, ongoing sales and replenishment and also product phaseouts.

"We closely monitor all the information that our [retail customers] provide, and then we can help them meet their goals. ... We understand what [the product] looks like and how it behaves better than anyone," says Gleckner.

Which is important. Because if you want to sell product, it's a good idea to know what will appeal to whom. After all, in the end, it's all about the customer.

As Gadzook's Wenzel puts it: "The customer really wants an environment where they can go that speaks to them. They want . a place that understands their needs, as complicated and varied as they may be. . [And that has to] come across not only in the assortment, but the people. . You've really got to make a connection with your customer," he concludes. 


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