DescriptionTraditionally, companies forecast based on company internal historical time-series data and qualitative signals from the market. In times of volatile markets, this leads to a myopic view that is not capable of anticipating demand shocks or trading cycles. This paper presents a forecasting method that matches macroeconomic trends with microeconomic performance indicators to obtain a more robust data basis. After calculating the rates of change of monthly sales data, a correlation analysis with predictable macroeconomic trend indicators like the purchasing manager index is conducted in order to accomplish a business forecast based on leading indicators. The resulting forecasts can be used for tactical and strategic supply chain decisions reaching from the extension of supplier basis and human resource decisions to investments in production facilities. Using practical examples of an US based global player in the oil and gas industry as well as a market leader in the formwork industry it is shown that the application of this method leads to better investment decisions both in case the trend points upwards and in case the trend points downwards. In either case, companies applying this kind of forecasting method are vested with a competitive advantage compared to companies who conduct yearly forecasts based on internal data only.
|Period||23 Jun 2019 → 26 Jun 2019|
|Event title||EURO 2019 Dublin|
|Degree of Recognition||International|
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Project: Research funding