Open– to– Buy Mastery Retail Planning, Forecasting & AI

What you'll learn

Build the OTB equation from opening, sales, markdowns and closing inventory to set and weekly-revise a full seasonal stock budget from scratch.
Separate trend, seasonality and event effects, then produce consistent demand forecasts using weighted moving averages and seasonality indices.
Connect AI methods like Prophet, LightGBM and the weighted recent sales index to the OTB budget and build reliable forecasts even for sparse SKUs.
Use the cover diagram, a 4-tier store capacity segmentation and a disciplined markdown strategy to reduce aged inventory and lift turn and margin.

Requirements

Basic Excel skills (formulas and pivot tables) are sufficient. One year or more of experience in retail, e-commerce or supply chain is recommended; working in a planning, buying, merchandising or category management role will accelerate the learning. No programming background is required, as the AI sections rely on conceptual explanations and ready-to-use tools.

Description

This course contains the use of artificial intelligence.
Open-to-Buy is one of the most critical disciplines in retail and e-commerce. When done right, it reduces markdown costs, lifts inventory turn and protects gross margin. When done poorly, season-end pile-ups, aggressive discounts and shrinking margins become unavoidable. Industry data shows that roughly half of a retailer's gross profit is eroded by markdown losses linked to the absence of OTB discipline.
This course is designed for professionals who want to build OTB discipline from scratch and elevate existing processes with AI-powered forecasting. We start with the foundations of classical retail planning: top-down and bottom-up planning, hierarchical budgeting, the opening-sales-markdown-closing equation and the cover approach. We then break down the three core components of demand forecasting (trend, seasonality, event effects) and produce consistent forecasts using weighted moving averages, exponential smoothing and seasonality indices.
The second half of the course is dedicated to AI-powered planning. Using methods like Prophet for baseline forecasting, LightGBM for sparse SKU forecasting, the weighted recent sales index (50/30/20) and YoY ratio caps, we move beyond the limits of classical forecasting. We then walk through step by step how AI output connects back to the OTB budget.
The final section covers execution, KPIs and governance: the cover diagram, a 4-tier store capacity segmentation, markdown strategy, weekly and monthly OTB meeting rhythm, the executive KPI dashboard and how to read deviation signals. The course is enriched with publicly available cases from global retailers such as Inditex, Uniqlo and H&M.
Basic Excel skills are sufficient. No programming is required. The course delivers high practical value for planners, buyers, merchandisers, category managers, purchasing managers, supply chain analysts and product managers, as well as any retail professional looking to blend classical planning with modern AI methods.

Who this course is for

This course is designed for professionals responsible for Open-to-Buy, demand forecasting and inventory budgeting in retail and e-commerce companies. The primary audience includes planners, buyers, merchandisers, category managers, purchasing managers, supply chain analysts and product managers. It is also a strong fit for mid- and senior-level retail executives who want to combine classical planning discipline with AI-powered forecasting, for entrepreneurs aiming to establish or improve OTB discipline in their own businesses, and for finance and operations professionals focused on reducing season-end markdown costs.

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