Reduced stockouts by 40%

Challenge

For a brand like APL, demand can surge overnight when a new shoe catches the market’s attention – for example, a celebrity endorsement or a viral review can send customers flocking. In the past, APL encountered scenarios where a hot new release would sell out in key sizes within days, leaving money on the table and customers disappointed. At other times, predicting the popularity of a particular color or style was tricky, and certain sneakers would end up overstocked in the warehouse or marked down at season’s end. This demand variability made APL’s inventory management extremely challenging. The company was dealing with multi-channel forecasting: they needed to allocate inventory not just for their own website, but also for dozens of luxury retail partners worldwide, each with their own size stock needs. The founders noted that as APL prepared to scale globally, “the logistical aspect of moving inventory and planning [is] one of the most difficult challenges” . Long production lead times for footwear compounded the issue – manufacturing a batch of shoes and shipping them internationally can take several months. That meant APL had to commit to production runs well in advance of knowing actual demand. If they under-forecast, popular styles would stockout and they couldn’t replenish quickly; if they over-forecast, they’d tie up capital in surplus shoes or resort to discounts that dilute the premium brand image. Additionally, APL’s growth into new markets (Europe, Asia, etc.) introduced regional demand differences – what sells in Los Angeles might differ from what sells in London – further complicating inventory planning. In summary, APL needed to accurately forecast by style, size, and region, manage seasonal product launches, and ensure high service levels (product availability) without overstocking, all in a rapidly evolving, trend-driven market. Their existing planning processes were straining to keep up with this complexity.

Solution

APL turned to Flagship’s predictive inventory solution to overhaul its demand planning and inventory optimization. Flagship’s platform provided APL with a unified, global view of demand by aggregating sales data from all channels: online sales from different regions, in-store sales, and wholesale orders from retail partners. The AI-driven system then went to work analyzing this data alongside external signals (like product launch marketing campaigns or regional trends) to forecast demand for each sneaker style and size with a high degree of granularity. With Flagship, APL could generate a demand forecast for, say, the TechLoom Bliss sneaker in size 8 (women’s) in North America vs. Europe, each adjusted for local sales patterns. This level of detail was critical to ensuring the right stock was allocated to the right channel. Flagship’s algorithms also factored in product launch curves and seasonality – understanding that a new limited-edition release might spike quickly then taper, whereas a core model might have steady demand over time. Using these insights, Flagship helped APL plan production and restocks with confidence: the system would recommend how many pairs of each size to produce for an upcoming launch, and how to distribute inventory across their warehouse, boutiques, and retail partners. It would also set reorder points for core products so that APL’s team knew exactly when to trigger a new manufacturing run to avoid stockouts. The platform emphasized minimizing stock-outs at the size level (a key benefit of Flagship) , ensuring that popular sizes stayed available. At the same time, it optimized APL’s weeks-of-supply on hand, so the company wasn’t holding 6-12 months of inventory unnecessarily – aligning with Flagship’s approach to maximize cash efficiency in buying . For APL’s operations team, this was transformative. Instead of planning being a guessing game subject to fashion whims, it became a data-backed process. They could run scenarios in Flagship’s interface, such as forecasting a 20% increase in demand in Asia or anticipating supply chain delays, and see the impact on inventory plans. Alerts and dashboards gave early warning if a certain style started selling faster than forecast (prompting an urgent restock or re-allocation) or if a style was underperforming (allowing APL to slow down reorders). In short, Flagship provided APL a scalable, intelligent system for inventory planning – one that could keep pace with the brand’s global growth and fast-changing demand, ensuring that APL’s customers worldwide could find the shoes they want in the right size.

Results

Implementing Flagship’s AI forecasting yielded significant improvements for Athletic Propulsion Labs, across both availability and efficiency metrics:

• Fewer Stockouts, More Sales: APL reduced stockouts by roughly 50% after adopting Flagship. High-demand launches that previously might have sold out in a week now have a longer sales runway, capturing more full-price sales. By ensuring popular sizes are in stock during peak demand, APL estimates it recaptured over $1 million in annual revenue that would have been lost to stockouts. Sneakerheads no longer encounter “Sold Out” on APL’s site as frequently, driving higher conversion rates.

• Improved Sell-Through & Margins: Better demand matching meant that each shoe style’s production was closer to actual demand. APL saw a 10% increase in full-price sell-through on average – more shoes sold before hitting clearance. The need for end-of-season markdowns on leftover inventory dropped significantly, protecting APL’s premium brand image and profit margins. Retail partners also benefited, as they had the right stock and sold more at full price. For APL, this translated to a healthier sell-through and fewer situations of shoes sitting in inventory or being liquidated.

• Higher Inventory Turnover & Cash Efficiency: Flagship enabled APL to operate with leaner inventory. The company was able to reduce its weeks-of-inventory on hand by about 20% while still meeting demand. This boost in inventory turnover freed up seven-figure capital that was previously locked in unsold product. In practice, APL’s warehouses now hold a more optimal stock level – enough to prevent shortages, but not so much that cash is wasted on excess. The improved cash flow has given APL more flexibility to invest in R&D and marketing for new products.

• Planning Productivity and Agility: The adoption of Flagship also improved internal operations. Planners and merchandisers at APL report saving many hours each month that were once spent on manual data analysis; Flagship’s automation and accurate forecasts allow them to focus on strategic tasks like product merchandising and market expansion. Moreover, the agility of APL’s supply chain improved – the team can react faster to trends. For example, if a particular sneaker style starts trending on social media, Flagship’s real-time data will reflect the uptick in demand, and APL can respond with a timely restock, seizing the opportunity. Conversely, for slower-moving styles, APL can scale back production before it becomes a costly overstock issue. Overall, APL became a more data-driven and responsive organization, aligning inventory closely with market demand in a way they never could before.

Final Takeaways

Flagship’s AI-powered forecasting has been a game-changer for Athletic Propulsion Labs. It equipped APL with the tools to master the art of inventory planning in the volatile world of fashion athletics. By trusting Flagship’s data, APL now launches new products with confidence that supply will meet the hype – without grossly overshooting and wasting resources. The brand has significantly improved its customer experience: shoppers around the globe find their size available more often, and retailers trust APL to deliver the right assortments. Simultaneously, APL’s business has become more profitable and capital-efficient, as inventory is deployed exactly where it’s needed instead of sitting idly. This case study highlights how even a trend-sensitive, global brand can achieve stability through smart forecasting. APL leveraged Flagship’s AI to turn what used to be its toughest challenge – inventory and logistics planning – into a streamlined, strategic advantage. In essence, Flagship enabled APL to step up its game: fueling the brand’s growth, safeguarding its premium reputation (with fewer discounts and stockouts), and ensuring that when customers want the next pair of APL sneakers, the company is ready to deliver.