How Retailers Can Improve an Out-of-Style Inventory Model

Using data to meet market demand in brick-and-mortar fashion retail

Michael Casey and Gregory Serrago

Spring may feel like an overnight shift to consumers—they wake up one day to find leaves on trees and pastel hues in shop windows—but to retailers it can represent a year’s worth of inventory planning.

In fashion retail, that planning is essentially a gamble on how many of which style, in what color and what sizes shoppers will buy in the new season. The constraints of an inflexible, slow-moving supply chain created in the middle of the last century force retailers to put an epic amount of work into forecasting and projecting their inventory orders 9 to 12 months into the future.

And still their predictions are usually wrong. Retail industry veterans will tell you that inventory forecasts are never right. We are left with inaccurate inventory projections baked into the industry’s business model.

In the e-commerce age, what was once merely a common inefficiency has become a potentially fatal flaw. When apparel retailers make guesses about what will sell in their store 12 months in advance, with no opportunity to tweak and change orders to respond to real-time demand, it practically ensures that the mix of goods in the store won’t match up with consumer demand in two important ways: either customers will not find the item that they want in store or retailers will have to mark down larger numbers of items that didn’t sell.

Michael Casey and Gregory Serrago, Cracking the Code – Managing Fashion Apparel In-Stocks, BRG Retail (March 12, 2019), available at: https://www.thinkbrg.com/newsroom-publications-retail-cracking-code.html

Both scenarios can swallow a retailer’s profits, but the first is particularly damaging to the relationship with the customer and can trigger ill effects. A sale is lost in the moment, and the customer leaves feeling disappointed—and associates that disappointment with the store itself. While in the past a shopper may have continued shopping at the next storefront, today’s in-store failures frequently lead consumers to abandon brick-and-mortar shopping altogether.

How to Move Past a (Very) Dated Approach

Conditioned to expect bottomless inventory, one-click purchasing and fast, free delivery, today’s consumers bring an entirely new set of expectations to the shopping experience. Brick-and-mortar retailers have to evolve to meet the demands of a retail environment where time to market has been slashed and the pace of delivery runs on hyperdrive.

Retailers must update the old forecasting model, adopting a mindset of active in-store inventory management with the goal of ensuring that what every customer wants will be in stock when each customer is in the store. Achieving that will improve the customer experience, build loyalty over time and protect retail profit margins from flawed predictions.

It starts with borrowing a few tricks from shopkeepers’ digital nemeses. They should adopt the e-commerce approach to data collection and real-time responsiveness; that will bring their business closer in line with the ways their customers are actually behaving in stores. They should start by determining which metrics are important and how often they will be reviewed, then look for ways to shorten ordering and fulfillment cycles in accordance with the specific needs of each store's location. The goal is to give the customer the best of both worlds: the familiarity and tactile pleasure of in-store shopping with the on-demand inventory expectations of the online experience.

How Fashion Retailers Can Modernize Inventory Management

Getting there isn’t simple, but it is possible. Retailers can follow these basic steps to modernize their in-store inventory management:

1. Track lost sales metrics using attributes like style, season, size and color in an executive-level dashboard.

2. Incorporate the collected data into the seasonal planning process. Identify which sizes are most often out of stock and which wind up unsold; use that data to adjust orders up or down.

3. Eliminate allocation shortcuts, such as equating a number of units broadly to a number of weeks’ supply or dividing items equally across many locations without regard to specific regional demand. Each unit decision should be based on store-specific customer data and have additional focus on replenishment speed.

4. Examine the full spectrum of business inputs: store labor, markdowns, lost sales, freight and supply chain. In many cases, revisiting supply chain strategies to shift costs upstream pays dividends at the point of sale. For example, if you’re optimizing for replenishment speed in response to customer demand, that might increase freight costs. But that increase will be more than offset by the additional sales recorded when customers find the right mix of goods in the store, which also helps ensure customer satisfaction and prevent additional markdowns. 

5. Assess and act on the additional insights derived from more rigorous, frequent inventory analysis. More and better information about seasonal trends, day-of-week sales and characteristics of the most profitable customers can feed smarter business decisions that allocate more effectively not only inventory but also labor and marketing dollars.

These lessons are important, because if a retailer is out of stock, especially when it comes to fashion basics or key seasonal items, shoppers will quickly look for other options. Whether that means finding another store or going online, the result is a lost sale—or worse, a lost customer.