A big data framework for facilitating product innovation processes

大数据 新产品开发 产品(数学) 过程(计算) 产品创新 过程管理 钥匙(锁) 计算机科学 知识管理 创新管理 业务 营销 几何学 数学 计算机安全 操作系统
作者
Yuanzhu Zhan,Kim Hua Tan,Guojun Ji,Leanne Chung,Ming‐Lang Tseng
出处
期刊:Business Process Management Journal [Emerald Publishing Limited]
卷期号:23 (3): 518-536 被引量:90
标识
DOI:10.1108/bpmj-11-2015-0157
摘要

Purpose The purpose of this paper is to suggest how firms could use big data to facilitate product innovation processes, by shortening the time to market, improving customers’ product adoption and reducing costs. Design/methodology/approach The research is based on a two-step approach. First, this research identifies four potential key success factors for organisations to integrate big data in accelerating their product innovation processes. The proposed factors are further examined and developed by conducting interviews with different organisation experts and academic researchers. Then a framework is developed based on the interview outputs. The framework sets out the key success factors involved in leveraging big data to reduce lead times and costs in product innovation processes. Findings The three determined key success factors are: accelerated innovation process; customer connection; and an ecosystem of innovation. The authors believe that the developed framework based on big data represents a paradigm shift. It can help firms to make new product development dramatically faster and less costly. Research limitations/implications The proposed accelerated innovation processes demand a shift in traditional organisational culture and practices. It is, though, meaningful only for products and services with short life cycles. Moreover, the framework has not yet been widely tested. Practical implications This paper points to the vital role of big data in helping firms to accelerate product innovation processes. First of all, it allows organisations to launch new products to market as quickly as possible. Second, it helps organisations to determine the weaknesses of the product earlier in the development cycle. Third, 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. Last, but not least, it identifies and then prioritises customer needs for specific markets. Originality/value The research shows that firms could harvest external knowledge and import ideas across organisational boundaries. An accelerated innovation process based on big data is characterised by a multidimensional process involving intelligence efforts, relentless data collection and flexible working relationships with team members.
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