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E-book
Demand Management Replenishment

New opening, grand risk? Why traditional inventory allocation methods fail

Opening a new store is an exciting milestone, but also one of the most operationally risky moments in retail. Empty shelves mean lost sales from day one, while excess inventory ties up capital and hurts profitability. In a world of volatile demand, local differences, and shrinking margins, traditional inventory planning methods are no longer enough.

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Inside you will find:

Why traditional inventory planning creates hidden risks

Planning based on intuition, network averages, or simplified Excel models ignores local demand patterns and real-world dynamics. The result is overstocks in some stores and critical shortages in others – often before the store has even gained traction.

Where Excel and historical data fall short

New store openings and new products come with little or no sales history. External factors like weather, local events, and customer profiles dramatically impact demand, yet traditional forecasting tools simply can’t keep up with this complexity.

How AI enables precise, store-level and SKU-level stocking

Machine learning models analyze hundreds of variables to generate granular forecasts per store and per product.

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Click and download the e-book (PDF) to learn why traditional inventory planning fails—and how AI helps retailers stock new stores with confidence from day one.

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