Forecasting with limited intermittent data: a methodological framework applicable to newly established firms

Nowadays, the motivation for starting a new business in Greece is necessity. As the Greek economy is experiencing the eighth year of recession, there are many newly established SMEs striving to survive. Their main difficulty lies in forecasting demand, while having both limited and intermittent data. Although the literature provides several forecasting techniques for intermittent demand, most of them are not applicable in case of short demand history. This paper provides a methodological framework for intermittent demand forecasting applicable to newly established firms with limited demand data. The proposed quantitative decision support methodology is evaluated empirically and its usage is demonstrated through its application on real data of a newly established SME in Greece. The results demonstrate that the methodology can be used to forecast demand for products with limited intermittent data. Challenges concerning all stages of the methodology are discussed, while sensitivity analyses are conducted and interesting managerial insights are presented.