Estimating New Product Success with the Use of Intelligent Systems

Abstract

The paper presents identifying success factors in new product development and selecting new product portfolio. The critical success factors are identified on the basis of an enterprise system, including the fields of project management, marketing and customer's comments concerning the previous products. The model of measuring the success of a product includes the indicators such as duration and cost of product development, and net profit from a product. The proposed methodology is based on identification of the relationships between product success and project environment parameters with the use of artificial neural networks and fuzzy neural system that is compared with the results from linear model. The presented method contains the stages of knowledge discovery process such as data selection, data preprocessing, and data mining in the context of an enterprise resource planning system database. The illustrative example enhances a performance comparison of intelligent systems in the context of data preprocessing.Keywords: project management, new product development, knowledge acquisition, data mining, ERP system. IntroductionNew product development (NPD) is one of the most important processes in maintaining a company's competitive position and continuing business success. New products and innovations impact on sales volume, employment, technological process, and economic progress. Contribution of NPD to the growth of the companies, its influence on profit performance, and its role as a key factor in business planning has been widely considered [e.g. 1-3]. Nevertheless, it is still reported that the success rate of product development projects is unsatisfactory, with more cost and time than expected having been consumed to achieve the project goals.The main reasons why most companies have failed in the development of new products derive from extrinsic and intrinsic problems. Extrinsic problems include flops in the market, changes in regulations or simply competition develops product first [4]. Intrinsic problems concern the limited resource constraints (e.g. temporal, financial, and human) and result in the difficulties to meet the project goals, including product innovativeness. Unsatisfactory success rate of product development projects can also be considered from the perspective of inherent feature of NPD, that is, it is a relatively risky activity [5], as market competition and product technology advancement are often intense [6].Although the success of a new product depends on the environmental uncertainties that are beyond a firm's control, companies should take into account both external and internal indices that can impact on the product success. Internal indices can be acquired from company's databases, including Enterprise Resource Planning (ERP) system, project management software, customer relationship management system, etc.The proper choice of critical success factors and metrics can improve the accuracy of new product evaluation, determine an optimal set of new products for development, m...

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