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, seasonal etc. These techniques ensure reliable forecasting results for different time series models: random, trend, seasonal and cycling, 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 for data storage.

Vyšniauskas, K., UAB “Fazer kepyklos” paklausos prognozavimo ir gamybos planavimo analizė [Rankraštis]: Bakalauro baigiamasis darbas. Vadyba ir verslo administravimas. Kaunas, ISM Vadybos ir ekonomikos universitetas, 2009. Darbo tema – UAB „ Fazer kepyklos“ gamybos planavimas nestabilios paklausos sąlygomis. Darbo tikslas - pateikti pasiūlymą, kaip prognozuojant paklausą ir planuojant gamybą sumažinti perteklinės produkcijos kiekį, tuo pačiu, įmonės gamybinius kaštus. Darbo uždaviniai: išaiškinti esamą paklausos prognozavimo bei gamybos planavimo situaciją įmonėje; parinkti tinkamus duomenis įmonės paklausos prognozavimui ir gamybos planavimui; prognozuoti paklausą bei patikrinti jos tikslumą; parinkti tinkamą sprendimą nagrinėjamai problemai spręsti. Tyrimo metodika: antrinių duomenų analizė; istorinė analogija, nestruktūruotas interviu. Darbo rezultatai: parengtas bendras, adaptuotas prie konkrečios situacijos, paklausos prognozavimo ir gamybos planavimo modelis, kuris preliminariais skaičiavimais, sumažintų įmonės gamybinius kaštus iki 7,5%. / Vyšniauskas, K., UAB “Fazer kepyklos” forecast of demand and production planning analysis [Manuscript]: conclusive bachelor performance. Management and business administration. Kaunas, ISM University of management and economics, 2009. Topic – UAB “Fazer kepyklos” production planning in unstable demand environment. Perrformance target – make a suggestion how to improve demand forecasting and production planning process which will be able to reduce level of excess production also company’s production costs. Tasks – analyze current situation of demand forecasting and production planning; choose proper theoretic models of demand forecasting and production planning; make demand forecast and evaluate it’s accuracy; choose one of possible alternatives as right decisions to solve analyzing problem. Survey methodology: secondary data analysis; historical analogy; non structured interview. Performance results: made united demand forecasting and production planning model, which is adaptive for current situation and which could reduce production costs to 7,5 percent.