Big Data-driven Innovation: The role of big data in new product development

Abstract

Abstract The outcome of the Big Data hype is a widespread delusion that applying Big Data will instinctively enhance and improve current business activities. Organizations have identified the benefits and disruptive potential of Big Data such as; value creation, business idea generation, and innovation. Yet, most organizations do not understand the key factors that go into a successful Big Data implementation or Big Data’s role for specific objectives. Previous studies show that unsuccessful implementation of Big Data across organizations is immense, only 27% of the companies being investigated described their Big Data actions as successful (Capgemini, 2015). Nevertheless, exponentially increasing data streams enable novelty in methods and processes for New Product Development. Making Big Data an important enabling element of innovation and sustainability. The purpose of this study is to explore and understand what role Big Data holds in the New Product Development and what factors influence a successful implementation in New Product Development processes. A qualitative investigation through multiple case studies of diverse companies in the Netherlands was executed to explore and compare key elements of Big Data in the context of innovation, and more specifically in the pre-development and formal development phases of New Product Development. In summary, the empirical findings show that the role of Big Data in the New Product Development is highly dependent on the ability to understand the specific objective or problem, and examine if using Big Data is the right approach for solving that problem. There is a prerequisite for securing distinct resources and organizational capabilities to succeed with implementing Big Data into the New Product Development. Other important factors that need to be well considered by organizations when forming an implementation strategy is organization’s data maturity and effective change management, especially if the organization is utilizing more traditional innovation processes. However, novel methods rely heavily on extensive and varied data which translates in an adoption urgency to sustain competitive advantage and secure responsive innovation.