Yves R. Sagaert, Nikolaos Kourentzes, Stijn De Vuyst and El-houssaine Aghezzaf, ISf2018, 19th June 2018<\/p>\n
Supply chain management is increasingly performed at a global level. The decision process is often based on tactical sales forecasts, which has been shown to benefit from including relevant exogenous information. Leading indicators that cover different aspects of macroeconomic dynamics are appealing in this context, as macroeconomic dynamics in target countries can affect companies end markets. Even though this information can be beneficial on a tactical level, it remains unclear how this information can impact sales forecasts at Stock-Keeping-Unit (SKU) product level, due to increased levels of noise and products having differing demand patterns and dynamics, masking macro-effects. Nonetheless, hierarchical forecasting can be used to reconcile macroeconomic leading indicators from tactical level forecasts to detailed SKU levels, and vice versa. In this paper, we evaluate the feasibility and benefits of merging tactical and operational forecasting, where higher level forecasts include leading indicators, in contrast to univariate SKU operational predications. We present a framework that identifies automatically the most relevant leading indicators on global sales level, and by exploiting the hierarchical product structure, carries this information to sales forecasts at SKU product level. For our evaluation we rely on inventory metrics obtained from simulation experiments, reflecting the associated supply chain risk.<\/p>\n
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