Reformation’s COO on Scaling Smarter Buys with AI

Merchants and planners today juggle enormous complexity. They’re planning future seasons, managing the present one, and reconciling the past — often with Excel spreadsheets and averages of averages as their primary tools.

As James Theuerkauf, CEO of Syrup, explained: “In the age of AI, this is a completely outdated process. We have orders of magnitude more data and compute power than ever before.”

The stakes are high. Overbuying means costly markdowns, wasted logistics, and unsold stock. Underbuying creates stockouts, lost revenue, and disappointed customers. Either way, the margin hit is real.

Lessons from Reformation

Ivan Tchakarov, COO of Reformation, put it bluntly: “The most costly element of retail is the promotional markdown.” Reformation has built agility into its supply chain, sometimes producing in as little as 30 days. This speed reduces reliance on long-range prediction and creates room for flexibility.

But speed alone isn’t enough. As Ivan emphasized, success requires two tracks:

• Process innovation – ensuring nimbleness and flexibility aren’t lost as the company scales.
• Technology adoption – layering AI and automation to extend human capability.

Reformation sells more than 95% of its product at full price, but Ivan admitted the current way of doing so isn’t scalable. That’s where algorithmic buying comes in.

Inventory as a Portfolio

James likens buying decisions to portfolio management:

• Diversification – avoid overcommitting to one product.
• Risk vs. return – balance steady sellers (“blue chips”) with higher-upside bets.
• Capital allocation – weigh the cash tied up in inventory against expected returns.
• Portfolio optimization – maximize total sell-through and margin while minimizing markdown risk.

This mindset shift turns open-to-buy from a blunt tool into a dynamic, risk-aware inventory engine.

The Human + AI Balance

Both speakers stressed: algorithmic buying doesn’t replace human creativity. Merchants and designers still provide the intuition and inspiration behind newness. AI takes over where decisions become repeatable, data-heavy, and risk-based.

As Ivan put it: “AI will be a force multiplier, not a replacement. We want algorithms to scale the mundane, so our teams can keep creating the magic.”

James added that human involvement is critical in “setting the rules of the game” — the strategic parameters within which algorithms operate.

How to Get Started with AI Inventory Optimization

The advice was simple: start small. Don’t attempt an all-at-once AI transformation. Instead, test algorithmic buying in one workflow, one category, or with one enthusiastic “power user.” Early wins in replenishment, allocation, or markdown planning build momentum and cultural buy-in.

Ivan reinforced this with Reformation’s experience partnering with Syrup: beginning with allocation pain points, proving results, and then expanding to buying. Change management, not just technology, was the hardest part.

Looking Ahead to the Future of Algorithmic Buying

Within five years, James expects buying, allocation, and supplier processes to be unified, enabling reductions in lost sales, overstocks, and markdowns. Merchants’ roles will shift away from spreadsheets toward strategy and creativity.

For Ivan, the goal is clear: “I want our teams to focus on creating newness, while algorithms take over repeatable rebuy decisions. The result will be happier customers, stronger financials, and less waste.”

Algorithmic buying is about more than automation — it’s about smarter capital allocation, fewer markdowns, and more full-price sales. As both speakers agreed, the right path forward isn’t boiling the ocean. It’s starting somewhere, proving impact, and letting both process and technology scale together.