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首页> 外文期刊>International journal of production economics >Investigating the added value of integrating human judgement into statistical demand forecasting systems
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Investigating the added value of integrating human judgement into statistical demand forecasting systems

机译：研究将人为判断纳入统计需求预测系统的附加值

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Whilst the research literature points towards the benefits of a statistical approach, business practice continues in many cases to rely on judgmental approaches for demand forecasting. In today's dynamic environment, it is especially relevant to consider a combination of both approaches. However, the question remains as to how this combination should occur. This study compares two different ways of combining statistical and judgmental forecasting, employing real-life data from an international publishing company that produces weekly forecasts on regular and exceptional products. Two forecasting methodologies that are able to include human judgment are compared. In a 'restrictive judgement' model, expert predictions are incorporated as restrictions on the forecasting model. In an 'integrative judgment' model, this information is taken into account as a predictive variable in the demand forecasting process. The proposed models are compared on error metrics and analysed with regard to the properties of the adjustments (direction, size) and of the forecast itself (volatility, periodicity). The integrative approach has a positive effect on accuracy in all scenarios. However, in those cases where the restrictive approach proved to be beneficial, the integrative approach limited these beneficial effects. The study links with demand planning by using the forecasts as input for an optimization model to determine the ideal number of SKUs per Point of Sale (PoS), making a distinction between SKU forecasts and SKU per PoS forecasts. Importantly, this enables performance to be expressed as a measure of profitability, which proves to be higher for the integrative approach than for the restrictive approach.
机译：尽管研究文献指出了统计方法的好处，但在许多情况下，业务实践仍继续依靠判断方法进行需求预测。在当今的动态环境中，考虑两种方法的组合尤其重要。然而，问题仍然在于如何结合。这项研究比较了两种不同的统计和判断预测相结合的方法，它们采用了一家国际出版公司的实时数据，该公司每周对常规和特殊产品进行预测。比较了能够​​包含人类判断力的两种预测方法。在“限制性判断”模型中，将专家预测作为对预测模型的约束。在“综合判断”模型中，该信息在需求预测过程中被视为预测变量。所提出的模型在误差度量上进行了比较，并针对调整的属性（方向，大小）和预测本身（波动性，周期性）进行了分析。在所有情况下，集成方法都会对准确性产生积极影响。但是，在限制性方法被证明是有益的情况下，综合方法限制了这些有益效果。通过使用预测作为优化模型的输入来确定每个销售点（PoS）的理想SKU数量，从而将SKU预测与每个PoS预测的SKU进行区分，该研究与需求计划相关联。重要的是，这使绩效可以表示为衡量获利能力的方法，事实证明，综合方法要比限制性方法要高。

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