Tools for Merchandise Forecasting
Merchandise forecasting systems exist in a world unto themselves. And yet they’re basic tools that any mid-to-large-sized cataloger needs to compete successfully. Still, few catalog executives choose to make the investment in such solutions. In most cases, this reluctance is caused by two factors.
On the one hand, no one in the company may “own” the issue of making strategic inventory decisions. Merchants may make product selections, buyers decide whom to purchase from, marketers determine price points, and inventory managers must find a place to store the items or arrange for drop shipment. Yet no one takes full responsibility for determining exactly how much and when to buy each item. Merchants recommend, marketers advise, inventory managers warn and complain, and somehow everyone muddles through. Meanwhile, fill rates bounce around willy-nilly, and both backorders and overstocks become a fact of life.
On the other hand, when someone does actually try to impose order on this chaos, spreadsheets are most often the tool of choice. Why? Because they’re cheap, if not virtually free, since Microsoft’s Excel is ubiquitous. And they’re functional enough as planning tools to be considered sufficient to get the job done.
It seems that most direct commerce companies that invest in a formal merchandise forecasting system cross that bridge only when a trained merchandise professional joins the management team. Armed with knowledge of the merchandise management discipline, and experienced in its implementation, such a professional imposes order by using the appropriate tool — that is, a merchandise forecasting solution.
A Matter of Perspective
Essentially there are three views of demand forecasting: supply chain, retail and direct commerce. The latter can be divided further into two distinct groups: catalog and Web.
Most merchandise forecasting systems on the market are designed for the supply chain or retail worlds. In the supply chain environment forecasts of demand are used to plan production and distribution. At its most sophisticated, distributors and retailers work closely with manufacturers and producers in a formal, collaborative planning, forecasting and replenishment (CPFR) environment. While this holds significant promise as a future supply chain management platform, such systems are not our concern here.
Supply Chain Perspective
Production Planning Requirements Plng. Demand Forecasting
Collaborative Planning, Forecasting & Replenishment (CPFR)
While you may participate in a CPFR effort, you also must track and forecast demand in a customer-facing way. Many forecasting tools are designed to do exactly that. Note, however, that the typical demand curve for retail, as shown in the chart “Demand by Channel” (right), is a sell-through model. Sales start off immediately upon introduction of the stock into the stores and continue (ideally) until the inventory is exhausted. A run-away bestseller may be restocked repeatedly, but the typical challenge is developing a mark-down plan that strategically lowers prices until the product sells out, while preserving as much margin as possible. Again, a whole category of price management software systems support that effort.
Challenges Unique to Direct Commerce
But the direct merchant faces an entirely different set of challenges. In the catalog world, demand typically rises from zero when the catalog is mailed and peaks in the first two or three weeks as customers get the book and respond to it. While 60 percent to 80 percent of total demand may be experienced in those initial weeks, there may be a bump at the end of the season (e.g., for the fourth-quarter holidays). And some products trail off more quickly than others. It’s also critical to factor in the number of resalable returns you’re likely to get during the season.
Since orders generally are fulfilled from one or two warehouses, and space there is at a premium, knowing which items to have in stock in what quantities, and which to reorder and which not to, comprise critical data useful to your bottom line. When you’re managing hundreds or even thousands of SKUs, each with different demand profiles or curves, you can see why a system is required.
Moreover, such systems are based on statistical-analysis functions that are far more accurate than rule-of-thumb measurements.
The e-commerce demand model is much more opportunistic, offer-driven and instantaneous, on the one hand, and more unpredictable on the other. But since the immediacy of the Web allows you to easily remove sold-out items from your site or to engage in aggressive, short-term discounting to off-load overstocks, forecasting tools per se are somewhat less critical in the e-commerce space.
To be sure, there’s more to merchandise forecasting than predicting demand for any item or category. George Mollo, president of GJM Associates, a catalog consultancy, notes:
You can’t plan any item in the abstract. This business is all about relationships: of items to their categories, of new to carry-over items, price points offered, perhaps fabrications offered, number of appearances (catalog drops), as well as the internal and external competition each item might encounter.
If these basic factors aren’t considered in a formal planning process and, in turn, methodically applied to item forecasts, even the most sophisticated formal forecasting system won’t improve your inventory accuracy.
At the very least, you should have an “average item index” score that shows how each carry-over item performed compared to the average revenue per square inch for all items [during] the same season last year. The score permits assortment planning from a top-down perspective, while forecasting is used to revise plans from the bottom up (based on future projections).
Mollo also warns that if you project an expensive item to sell well on a unit basis, don’t let that revenue skew your planning. False averages can distort projected quantities on all other items in an assortment.
Now I think you can begin to see why doing this right requires a tool that can guide you through this thicket of variables.
Solutions to Try
Three major direct commerce merchandise forecasting systems, plus three other solutions are worth mentioning:
* The Galvin System from Galvin Associates, Marstons Mills, Mass., (www.galvinassociates.com) is the grand-daddy of direct commerce forecasting systems. Used by more than two-dozen major catalogers (including J.Jill and The Company Store), it’s available in a standard version and a less costly GalvinExpress version. The latter includes the basic merchandising module but not the modules for marketing, time-phased open-to-buy, item planning, material requirements planning or purchase order management.
* IF/SO from Forerunner Systems, Sausalito, Calif., (www.forerunnersystems.com) is a PC-based system that’s one of the least expensive and easiest to use, yet one of the most powerful merchandise management and forecasting platforms. It includes a module especially designed for e-commerce sales. Even catalogers with less than $10 million in sales may find IF/SO economical, particularly when kits, seasonality, or colors and sizes are involved. More importantly, Forerunner Systems doesn’t just sell a product; it trains, educates, supports and advises users on an ongoing basis, which is critical to success.
* Forecast*21 from Direct Tech, Omaha, Neb., (www.direct-tech.com) is a comprehensive suite of tools. Direct Tech’s client list includes Coldwater Creek, Hammacher Schlemmer and other catalogers. Forecast*21 offers: unique versioning capabilities to compare forecasts for different variations of the same offer (plus “what-if” version analysis); top-down/bottom-up planning at the level of offer/category/subcategory/product/descriptor/SKU; elaborate color/size planning and analysis; merchandise assortment planning; graphical page analysis; and open-to-buy planning. Direct Tech also emphasizes training as an essential aspect of systems implementation, working closely with clients to ensure they not only get everything set up properly but that they continue to use the system for maximum impact season after season.
* One unusual and specialized solution is Connectrix from Connectrix Systems, Yardley, Pa., (www.connectrix.com). First developed for J. Crew, this is a comprehensive, truly multichannel brand management application for “cradle-to-grave” inventory planning and management for soft goods (particularly housebranded merchandise) — that is, from product development and manufacturing through assortment planning, forecasting, purchasing, stocking, distribution, and supply chain management.
* The Direct Integration Marketing Suite from Direct Logic Solutions, Peoria, Ill., (www.directlogicsolutions.com) supports multichannel product forecasting, inventory management, and analysis within a full suite of direct commerce budgeting and planning tools.
* Finally, the new Commerce Management Solution (CMS) from Quark, Denver, Colo., (www.quark.com) includes a sophisticated marketing relationship management module for analyzing merchandise, customers and campaigns to determine buying behavior. And it includes a set of data mining, analysis and OLAP tools to track promotions, assortments, and to perform forecasting functions. An outgrowth of Quark’s original Mirim solution, these promotion planning and forecasting tools are available separately from the order management, inventory management, and customer database modules in CMS.
In short, by using the right tools, you can bring calming order to your inventory management chaos.
Ernie Schell is author of “The Guide to Catalog Management Software” and the president of Marketing Systems Analysis in Southampton, Pa., which helps catalogers specify and select order management, database marketing, and forecasting solutions. He wrote this article at the request of the Catalog Success editors. To reach him, call (215) 396-0660.