Call it the quantum theory of fashion. “Inventory intelligence” simultaneously intertwines the past (historical data), the present (dashboard readings) and the future (selling predictions), helping companies make smarter decisions—while there’s still time to change course.
“Inventory intelligence needs to talk about a decision framework,” Daren Hull, CEO of CreateOne, an end-on-end, on-demand apparel design and manufacturing platform by Resonance Companies, said during a panel at Sourcing by Informa at MAGIC in Las Vegas. “What are the decisions that I have to make today? What are the economic impacts? What is the optionality—the open doors that I still have open to change things, and what’s the timeline before that window closes?”
It’s a delicate balance. Brands need enough inventory to satisfy demand, but carrying inventory has procurement, production, logistics and financing costs. At the same time, stagnant inventory guzzles cash that could be invested in marketing, product development or growth. The goal isn’t to simply maximize availability or minimize unit cost, but to optimize the economics of the entire business. And like the Butterfly Effect, each decision branches off with rippling repercussions.
Alex Albert, vice president of supply chain and procurement for Xponential Health & Wellness Brands, which includes Club Pilates, Pure Barre, StretchLab and more, stressed that inventory management falls under the trifecta of service, cost and cash. “Service being how much inventory you want to hold to service your customer based upon those demand signals; the costs of facilitating that including procurement costs, MOQs, etc.; and the cash involved for the actual costs on the balance sheet,” he said.
But despite having access to more technology and data than ever before, brands still constantly overproduce, inevitably leading to markdowns and shrinking margins. Hull blames “overly optimistic forecasts,” driven by finance and sales teams excited about the new season. Additionally, he said, “everyone is so afraid of being out of stock that they optimize for availability, and that can be very disjointed from changes happening in the market.”
And while a planning decision is very cheap to change, most people are hesitant to change their forecasts. “That’s all well and good, but there’s a moment when commitment occurs. You need to go back and look at demand, and if you don’t adjust for demand, you’re just pushing the problems all the way down the chute,” he said, adding that AI connects three essential pieces at play: the demand cycle, the physical goods cycle and the financial cycle. By the time a product reaches the warehouse, many opportunities to change the outcome have already disappeared.
Staying Flexible
Flexibility also comes from making intelligent decisions early enough. Maybe a 10,000-unit forecast can be broken down into less risky pieces: 4,000 units produced immediately, 3,000 units reserved in factory capacity, and the balance put on hold until demand becomes clearer. Or maybe a brand lines up its hoodie orders back to back so as not to require swapping out the machines in between.
Factory relationships are critical in this model, especially as trends happen faster than ever and factories are essential to helping brands be ready when the time comes. “That may mean talking with your factory about keeping that fabric for an upcoming quarter,” said Hull. “Give yourself optionality.”
Albert agreed. “If the standard lead time of a particular product category is 140 days, you know the first 40, 50, 60 days of that build is fabric. [So with deferment] you can develop greige material and defer when you need to make the decision around what color you’re going to add to it.”
Assemble-to-order models follow a similar strategy. A brand might pre-position materials or unfinished products and complete them only after demand signals sharpen, or a product suddenly goes viral. The trick is to delay irreversible decisions for as long as economically practical.
Hull recommends that when uncertainty does increase, brands should “coil outward, not inward.” That means leaning into relationships with factories, logistics providers, sourcing experts and other industry participants, and using that network when decisions become difficult.
Warehousing and transportation are other major sources of optionality.
Bonded warehouses and foreign trade zones can help defer duties and maintain flexibility, although the economics and compliance requirements need to be evaluated carefully.
Robert Krieger, president of Krieger Worldwide, highlighted the range of tools that brands can use when problems arise, including different ocean services, ocean-air combinations and varying levels of air freight. Brands and retailers must look at the full picture when choosing between standard ocean freight and air options, as more expensive transit can save money down the road if that product can be sold for full price. “It all comes down to math,” he said.
Albert illustrated this in action. “When I worked for Stance socks during the pandemic, the cost for a high cube container was like $30,000. Crazy. But after doing the math, we found the cost differential between delivering our product via vessel or chartering a jumbo jet was actually within 10 to 15 cents when you roll it all up. So during the heat of the whole disaster where vessels were waiting to get into port, we flew in our socks on the jumbo jet and got to market ahead of everybody else,” he said. “It was an amazing opportunity, and we saved our revenue plan for that year.”
Hull agreed: “Speed is one of the best currencies in today’s supply chain.”
While artificial intelligence is invaluable in inventory and merchandising calculations, gathering and analyzing enormous quantities of information across sales, social trends and other demand signals, it still can’t replace human judgment that has to make the final decision.
“The cheapest product is not necessarily the most profitable product,” said Edward Hertzman, founder of Hertzman Global Intelligence. “People are maniacal about getting the cheapest price but that doesn’t mean you sell it for the highest price. A $2 T-shirt that retails for $49.99 but ultimately sells for $9.99 may be far less attractive than a $6 T-shirt that sells at $49.99.”
