Improving new product development using big data: a case study of an electronics company - Tan, Kim Hua; Zhan, YuanZhu (Wiley, 2016)
Big data is becoming more important to the new product development (NPD) efforts of global firms. Although the term of big data is not new, very few studies have investigated how firms can harvest big data to facilitate NPD. The purpose of this article is to present the means by which big data can be used to assist firms in NPD to shorten the time to market, improving customers’ product adoption and reducing costs. This research is based on a two-step approach. First, we identified and analysed three world-leading firms that have successfully integrated big data in supporting their NPD. Then, the observations from the firms were used to determine the principle involved in leveraging big data to reduce product development lead times and costs. Given the exploratory nature of the research objective, a participant-observation case study is adopted in which during a 6-month period a NPD project in a fast moving high-tech industry was investigated. This study provides empirical confirmation for the three principles to big data supported NPD: (a) Autonomy; (b) Connection; and (c) Ecosystem. It is termed the ACE principles which we believe represent a paradigm shift to help firms unlock the power of big data and make NPD faster and less costly. This article provides guideline to firms in harvesting big data to better support their NPD: it allows organisations to launch new products to market as quickly as possible; it helps organisations to determine the weaknesses of the product earlier in the development cycle; it allows functionalities to be added to a product that customers are willing to pay a premium for, while eliminating features they do not want; and it identifies and then prioritises customer needs for specific markets.