Ekonomski pregled, Vol. 56 No. 7-8, 2005.
Prethodno priopćenje
FORECASTING AND MONITORING PROFIT (LOSS) IN COMMERCIAL COMPANIES
Berislav Bolfek
Sažetak
Sometimes in commercial companies the management receives the information about profit and loss amounts with delay what creates difficulties to management in managing business results. So, the purpose of this work is to elaborate and check the model for forecasting and monitoring profit (loss) in commercial companies that will enable the management monthly forecasting and monitoring business results. Among known forecasting methods, the exponential smoothing method and exponential smoothing method with trend were possible choices. Checking the accuracy of forecasting methods by applying mean absolute prognostic error (MAE) exponential smoothing method was chosen because in processing business results of municipal trading company it showed more accuracy in forecasting than exponential smoothing method with trend. The model has been set in a way that each month of financial year it forecasts profit or loss at yearly level, i.e. on 31 December of forecasting year. So in January it gives the forecast for all twelve months of the year, while in February the model gives the forecast for the period February – December, while for January it takes into account achieved results. The same forecasting and monitoring sequence is repeated for the period March – December and all up to the end of financial year. Testing the model for forecasting and monitoring profit (loss) with data from municipal commercial company proved applicability of the model to commercial companies, but the model has to be integrated in commercial company information system. This model enables the management to take timely preventive corrective actions to obtain planned goals of business policy, i.e. achieve the principle of managing business result.
Ključne riječi
business forecasting; exponential smoothing; mean absolute error; profit and loss; company
Hrčak ID:
10296
URI
Datum izdavanja:
25.8.2005.
Posjeta: 4.831 *