CFO Paradigm · Example company: Cawan's Shoes
What it means

Applying machine learning and generative AI to demand, personalization, and operations.

Why it matters

Fastest-moving productivity frontier since the internet.

How to calculate — with Cawan's Shoes

Cawan's Shoes 2026 AI use cases (measured, not marketing): • Demand forecasting (running-shoe SKUs, store-week grain): forecast accuracy 71% → 84%. Markdown rate down 3.1 points = $12.5M gross-profit lift on $400M shoe revenue. • Personalized email (Klaviyo + custom LLM copy): open rate 21% → 34%, incremental DTC revenue $8.6M/yr on $1.2M model + infra spend. • Generative-design assist for midsole geometry: cut design iteration from 14 weeks to 5 weeks; enabled 3 extra product launches per year. • Customer-support chatbot: 62% tier-1 ticket deflection, CSAT 4.3/5, $1.4M/yr saved. • Fraud detection on DTC checkout: chargeback rate 0.42% → 0.11%, $2.1M/yr saved. All models run through the AI governance council; PII data never leaves the Cawan's VPC.

What's at stake if you ignore this

Sitting out AI is a strategic choice that competitors will exploit.