These latest economic curveballs are leaving retailers with one viable option: deep markdowns to clear their warehouses – or what Macy’s CFO Adrian Mitchell termed “an elevated promotional environment.” While rock-bottom discounts may be attractive to consumers, particularly following a costly fill-up at the corner gas pump, margins and profits across the retail sector are set to take a wallop. For example:
On a June 6, 2022 Q1 earnings call, Target warned investors that an aggressive discount strategy—coupled with cancelling new orders from suppliers— will result in a lowered EBITDA forecast from 5.3% to 2%, triggering a sharp decline in its stock price, which arguably rippled across Wall Street.
Days earlier, Walmart conceded that fully resolving its Q1 backup of inventory – a 32% spike – would likely take “another couple quarters,” following up on the previous month’s similarly disappointing earnings report, which abruptly plunged its share price to a 35-year low.
These somber projections from the big-box giants have been a bellwether across the retail sector—particularly among specialty apparel retailers like Gap, Abercrombie & Fitch, and American Eagle Outfitters, who’ve likewise reported revenue challenges stemming from over-inventory. Across the board, syncing quantity, demand and margins has become harder than ever.
The problem, simply put, is wrong merchandise piling up at the wrong places at the wrong time, and what customers were expected to have wanted a few months ago isn’t what they’re actually buying today. How can retailers compensate—and de-risk their inventory management?
The knee-jerk response is to broadly markdown categories of goods that aren’t moving. But such broad-brush discounting is a “blunt instrument” that rarely finds the ideal “sweet spot” between fastest sell-through and optimized margin—as illustrated in my previous blog post.
The ideal solutions leverage granular-level data:
Which SKUs are and aren’t selling—and where?
How quickly can we assess shifting customer demand?
What lower price points will move lingering merchandise now—without squandering critical margin?
Can we fine-tune markdown/sell-through for specific items that won’t require a rock-bottom discount?
What else can we learn to avoid excess inventory all but pre-destined for the clearance rack?
Wrangling all that essential data “from scratch” – even in the best of times – would be a colossal effort. Retailers of all sizes are looking to gain a competitive edge from single-source, AI-powered applications for demand planning and forecasting and lifecycle pricing to prevent or quickly resolve costly over-inventory – before they’re staring at 200 immobile pallets of shorts and bathing suits in November.