Using a Software Tool in Forecasting: a Case Study of Sales Forecasting Taking into Account Data Uncertainty

• Main Authors: Fabianová Jana, Kačmáry Peter, Molnár Vieroslav, Michalik Peter
• Format: Article
• Language: English
• Published: De Gruyter 2016-10-01
• Series: Open Engineering
• Subjects: Forecasting; ARIMA; multiple linear regression; Monte Carlo simulation
• Online Access: http://www.degruyter.com/view/j/eng.2016.6.issue-1/eng-2016-0033/eng-2016-0033.xml?format=INT

Forecasting is one of the logistics activities and a sales forecast is the starting point for the elaboration of business plans. Forecast accuracy affects the business outcomes and ultimately may significantly affect the economic stability of the company. The accuracy of the prediction depends on the suitability of the use of forecasting methods, experience, quality of input data, time period and other factors. The input data are usually not deterministic but they are often of random nature. They are affected by uncertainties of the market environment, and many other factors. Taking into account the input data uncertainty, the forecast error can by reduced. This article deals with the use of the software tool for incorporating data uncertainty into forecasting. Proposals are presented of a forecasting approach and simulation of the impact of uncertain input parameters to the target forecasted value by this case study model. The statistical analysis and risk analysis of the forecast results is carried out including sensitivity analysis and variables impact analysis.