Intermittent product demand patterns challenge inventory planners across the capital goods and service parts inventory spectrum, where millions of dollars in inventory costs and lost business can result from inaccurate planning. Traditional statistical forecasting methods have failed with this data because they assume a "normal" distribution of product demand over a lead time. A new bootstrapping methodology that accurately forecasts intermittent demand data promises to strike the right balance between minimum levels of required inventory and maximum levels of customer service.
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