With retail data more abundant and accessible than ever, using data intelligence to align inventory with demand is no longer optional—it’s essential. The real opportunity lies in closing the profit gaps created by inaccurate buying decisions.
According to research firm IHL, inventory distortion cost the retail industry an estimated $1.7 trillion in 2024 alone—$1.2 trillion due to out-of-stocks and $554 billion from overstocks. Their Fixing Inventory Distortion report predicts that retailers who fully leverage intelligent data platforms and machine learning could improve gross margins by 25% or more by 2029.
Accessing the hidden profit
What I’ve learned from my experience as a merchandising director, and as CEO of Style Arcade, is that a 25% uplift has always been within reach—retailers just lacked the tools to access it. With booming revenues and bullish growth in past years, many fashion businesses were never forced to pursue that extra profit. But in today’s climate of high data scrutiny and AI accessibility, the answer is finally within reach. It lives in the many facets of your product data.
Much of the problem lies in manual order qualification. Most inventory distortion stems from inaccurate purchase order quantities, driven by skewed sales data due to out-of-stocks at the store and size level. Merchandising teams are often ordering manually, using spreadsheets to plan product, store, and size breakdowns. That process is not only complex—it reinforces existing inaccuracies in the data.
I estimate that manual buying using spreadsheets typically accesses only half of the data points available, and only a subset of those are fully accurate.
Closing profit gaps with demand accuracy
This is where AI steps in. With platforms like Style Arcade, retailers can unify and cleanse all available data to generate accurate order recommendations at a precision that spreadsheets simply can’t match.
One major player already making the shift is 187-year-old department store David Jones. In partnership with Style Arcade, they’re tackling inventory challenges head-on—refining stock allocation, minimizing markdowns, and unlocking greater profitability.
“While it’s still early days, industry research suggests that intelligent data platforms like Style Arcade can improve gross margins by up to 25% over time,” said Bridget Veals, Executive GM of Womenswear, Footwear & Accessories at David Jones, in an interview with Ragtrader.
“Given the scale of our operations, we expect to see meaningful efficiencies in profitability and inventory turnover—while continuing to deliver exceptional service to our customers.”
With access to all product and customer data points with Style Arcade, retailers can harness:
- True Rate of Sale based on when the product was in stock
- Rich product attribution to automatically tag category, subcategories, sleeve length, neckline, silhouette, colourway, and deeper
- Like-style performance to get accurate product recommendations based on aligned attributes and features
- Like-store performance modeling to get accurate size profiling by channel, by store, and by category
- Data correlations to discover patterns in your range as well as white space
IHL’s report echoes AI’s positive impact on inventory management optimization stating, “By automating this process and considering real-time data, AI can minimize stockouts and overstocks, manage safety stocks, consider sellable and non-sellable supply buckets and reduce the likelihood of further inventory distortion.”
With the potential for price increases under US tariffs, consumer uncertainty, and slowed growth, the time is now for retailers and brands to dig deep into their product data with intelligent systems and close those profit gaps.
