Created turnover views to flag slow‑moving and deadstock items. Used outputs to support the TLF Color Run distribution plan and local redistribution efforts.
At the time, the company had roughly $10 million in inventory sitting in our Fort Lauderdale warehouse, and leadership began noticing that even after promotional pushes, some products were still not moving. I took the initiative to spearhead a detailed inventory turnover analysis to understand how quickly different SKUs were cycling through the warehouse and to identify items that were tying up working capital and warehouse space.
I built reports that segmented inventory by turnover rate and grouped SKUs into tiers of urgency based on how slowly they were moving. For example, men's and women's products with turnover rates below a set threshold were classified into tiers, with Tier 1 representing the most urgent items that had essentially stalled in the warehouse. This gave us a clear, data-backed view of what products needed to be liquidated first, and allowed us to rank and organize inventory not just by turnover rate but also by product type, collection, and variant.
The analysis revealed that nearly $1M worth of inventory was essentially "dead stock." By surfacing this insight, I was able to help drive a decision to liquidate $350,000 worth of those items, partnering with local events such as the Fort Lauderdale Color Run to both clear inventory and build brand awareness in the South Florida region. This initiative freed up warehouse space just in time for new seasonal product drops, reduced carrying costs, and improved cash flow. It also created an opportunity for employee engagement, as many team members joined in the event activations and community outreach tied to the liquidation.
Overall, the turnover analysis provided a comprehensive overhaul of how the business thought about stagnant inventory. Instead of letting slow-moving SKUs weigh down the warehouse and balance sheet, we were able to convert them into both financial relief and marketing value. It showed the impact of pairing operational data with actionable decision-making, helping to position the company for healthier growth moving forward.