Verslo analizės metodų taikymas mažų įmonių informacinėse sistemose

• Main Author: Reipas, Artūras
• Other Authors: Kiauleikis, Valentinas
• Format: Dissertation
• Language: Lithuanian
• Published: Lithuanian Academic Libraries Network (LABT) 2007
• Subjects: Informatics; Information technologies; UML; Informacinės technologijos; Duomenų analizė; Data mining
• Online Access: http://vddb.library.lt/fedora/get/LT-eLABa-0001:E.02~2007~D_20070115_092850-31887/DS.005.0.02.ETD

In current work problems and requirements for demand forecasting in commercial or manufacturing enterprises are analyzed and suitable forecasting algorithms are proposed. In enterprises with multidimensional and heterogeneous demand it is advisable to use different algorithms for different demand constituents and to readjust parameters used for forecasting. Existing forecasting packages are not practical as they are not integrated with commodities or materials supply orders management activities and business processes of enterprise. The orders management system is developed with forecasting component using adopted time series forecasting techniques such as moving average, exponential smoothing, double exponential smoothing. These techniques ensure reliable forecasting results for different time series models: random, trend and are integrated with other business management activities. It is possible to calculate deviations of forecasted demand from factual values, to select algorithms giving minimal perсentage error, and to adjust algorithms parameters to changing demand. The system can help managers to choose forecasting algorithms and to adapt their parameters in the course of time. The system is designed using UML CASE tool and implemented in Microsoft .Net environment using MS SQL Server 2005 for data storage.