Learn · Planning

    Demand Planning

    Demand planning is the loop that turns a sales prediction into stocking and pricing decisions: forecast per product, correct with real-time signals, set buffers and reorder points, plan purchase orders, and measure accuracy. Here's the whole loop and how AI runs it.

    The five-step loop

    1. Forecast — a per-product prediction of upcoming demand (how). Model choice matters: seasonal, trending, and steady products need different math.
    2. Sense — correct the forecast with what's happening right now: velocity shifts, competitor moves, early seasons (demand sensing).
    3. Buffer — recalculate safety stock and reorder points from current volatility and lead times.
    4. Plan orders — convert forecasts into purchase orders sized around lead times, MOQs, and order economics.
    5. Measure — score forecast accuracy (WAPE, bias) and feed the misses back into step 1.

    Where stores actually fail at it

    Rarely at the formulas — at the cadence. The loop gets run once in a January spreadsheet and never again: demand drifts, lead times slip, and by Q4 every number is fiction. The second failure is aggregation: one store-level forecast hides that your top three products behave nothing alike. The loop only works run per product, on a schedule reality can't outrun.

    What the AI version looks like

    Every step above is mechanical once the data flows: Yeer runs the loop continuously — forecasts refreshed up to hourly, buffers recomputed as volatility moves, reorder suggestions drafted with reasoning, accuracy self-scored per product. You review decisions instead of building spreadsheets. Enterprises run the same loop at network scale with Yeer's supply chain agents; the monthly business alignment wrapper around it is S&OP.

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    Frequently asked questions

    What is demand planning?

    Demand planning is the process of predicting what customers will buy and translating that prediction into inventory and purchasing decisions: how much to stock, when to reorder, and how to price. It combines statistical forecasting with judgment about promotions, seasonality, and market shifts.

    What's the difference between demand planning and demand forecasting?

    Forecasting is one step inside planning: the numeric prediction of future sales. Demand planning is the whole loop — generate the forecast, adjust it with real-time signals (demand sensing), convert it into purchase orders and buffers, then measure accuracy and repeat.

    What does a demand planning process look like for a Shopify store?

    A practical monthly loop: (1) forecast per product, (2) check forecast accuracy vs last month, (3) recalculate safety stock and reorder points, (4) plan purchase orders around lead times and MOQs, (5) flag slow movers for markdown. Weekly during Q4. Most of it is automatable.

    What tools are used for demand planning?

    Spreadsheets at the small end; enterprise suites (o9, Blue Yonder, RELEX) at the large end; and a newer middle: AI tools like Yeer that run the forecast-sense-plan loop automatically for ecommerce stores, starting free.

    How is AI changing demand planning?

    Three shifts: models are selected and retrained per product automatically; forecasts update continuously (up to hourly) from live signals instead of monthly cycles; and the output is drafted decisions — reorder X units by Friday — rather than a spreadsheet a human must interpret.

    Run the whole loop automatically

    Forecast, sense, buffer, reorder, measure — Yeer runs it per product from your live Shopify data. Free up to 50 products.

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