Mee Tyng Yoo
Arden University Berlin Campus, 10963, Berlin, Germany
*Corresponding e-mail: firstname.lastname@example.org
Sales forecasting is the methodology of predicting future values from a known time series data. The preference methodology of sales forecast is selected based on the minimum of the forecast errors given. Knowing that we are persevering in the VUCA realm now, it becomes a challenge for the business to improve the forecast accuracy. The leaders not only focus on agility and resilience in the VUCA environments, but also ensure that all insights, intelligence, and data feed innovation processes continuously. New skills and tools should be used to design and predict in an organisation. Hence, sales forecasting is essential nowadays to ensure our business resilience to the VUCA environment and continuous sustain in this competitive global marketplace. This study aims to identify the preference quantitative methodology: exponential smoothing (ES) or autoregressive integrated moving average (ARIMA) provide more accurate of sales forecasting compared with current practice – judgmental approach for the organisation in this VUCA environment.
Keywords: VUCA, VUCA prime, sales forecasting, exponential smoothing (ES), autoregressive integrated moving average (ARIMA), judgmental forecasting