Abstract: Big data usage is a hot topic in academics and practice, but the existing literature lacks research on data-driven new product development processes. This study develops a research model of the impact of big data-embedded new product development processes on innovation performance based on the theory of new product development. To test the proposed research model and implement a cross-national comparative study, this study collected data from China, the United States, and Singapore and analyzed the data using cross-group regression analysis methods. The empirical results indicate that the big data-embedded business analysis stage and the big data embedded product testing stage have a significant positive impact on innovation performance in China, the United States, and Singapore. Furthermore, the most important stage with regard to the impact on sales growth is the big data embedded product design stage in China, the big data embedded product testing stage in the United States, and the big data embedded product testing stage in Singapore. The most important stage with regard to the impact on gross margin is the big data embedded product design stage in China, the big data embedded product testing stage in the United States, and the big data embedded commercialization stage in Singapore.