Practical License Revenue Forecasting

Tim Gossett
Don Ladwig
Greg Speno

Like many managers with profit and loss responsibilities, licensing professionals are often responsible for making forecasts concerning the financial performance of active license agreements within their portfolio. However, unlike managers of existing products or services that enjoy historic sales and marketing data, the licensing professional typically has no such data, especially for new licenses. Statistical tools normally available for financial forecasting such as multivariate time series analysis or econometric methods are impractical to apply under these circumstances [1]. In addition, the very nature of intellectual property licensing implies new business partners, new products and new markets; consequently making any attempt to model the complex and interrelated underpinning factors useless [2]. If traditional quantitative methods have been judged inadequate at the commencement of the forecasting activity, the most often used alternate is a class of forecasting methods involving a judgmental approach [1]. This paper will present a hybrid forecasting method based on the synthesis of a time-honored judgmental forecasting technique for structured group analysis with the use of fuzzy numbers as its modeling construct. Finally, the practical application of the method in license revenue forecasting will be explored and a particular implementation of the method will be presented.


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