Big Data in New Product Development

The benefits of using big data to support customer involvement in NPD are identified as follows: first of all, risk and market uncertainties can be reduced by using big data analytics. Market feedback in a variety formats and from different sources can be acquired in the early development stages. Secondly, by harvesting big customer data allows previously unrecognised customer needs or combinations of needs to be identified. Market share will go to "first mover" firms that can respond to customers quickly and meet their needs. Thirdly, big data can be used to generate great ideas from a variety sources. Lead customers (or innovative users) often act as co-creators and support NPD managers in developing 'winning products' to the market. Fourthly, big data enables a company to contact potential customers in different ways. Fifthly, it also lends itself to customer loyalty and retention; for example, through online participation in NPD, customers gain a better understanding of a new product but also become attached to the product to which they have made a contribution. It is a compelling experience which creates commitment and trust. Customer involvement in NPD not only improves a company's product performance, but also serves as a means of building and enhancing relationships with both potential and existing customers. Finally, big data can provide NPD teams with a broader basis for their decisions. By applying big data analytics, it is possible to increase the number of test options and to institute parallel testing of product alternatives among a variety of customers; moreover, this can be done repeatedly throughout the different stages of NPD.

Implications for research and practice

This study contributes to the big data literature with the development of a customer involvement approach for NPD by unlocking the power of big data. The approach can be applied through all the phases of NPD. In terms of theoretical contributions, this paper extends the traditional NPD boundaries and provides evidence of the vital role of the customer-centred NPD approach in a data-rich environment. Firms are leveraging big data to embed customer sentiment in product development. This enables firms to move away from product-focused innovation and to turn their attention to innovation around the customer experience. The proposed paradigm-shifting customer involvement approach enables firms to find ways to innovate - unlocking the power of big data to improve customer understanding and make NPD faster and less costly. However, the implementation of the customer involvement approach may put considerable strain on an organisation. Nonetheless, we posit that any stress presented by the introduction of the approach will be more than compensated for by the time and cost reductions achieved in the modification of the NPD process.

This study also contributes to practice. The approach is recommended to NPD managers, as it will allow them to arrange their resources to in order to develop new features and new products in a fast and effective manner. From the examples in the case study, NPD managers can maximise positive outcomes from the approach of customer involvement. In the case of STE, implementing the customer-centred approach allowed it to decrease costs, to increase the speed of NPD and to gain a better understanding of customers' needs (and interaction with customers), and a change in leadership and team organisation. Compared with traditional NPD approach, STE was able to launch a range of new products in <5 months, at a total cost of $2 million. The company estimate that competitors using traditional design approaches have to invest around $20 million over 12 months to complete a similar set of NPD. Nonetheless, the challenges STE faced in implementing the customer involvement approach were identified such as IT infrastructure, managing relationships with intermediates, and the culture shift from product focus to customer focus.

However, managers must also be aware of several vital issues. First of all, the exploitation of customer information may cause intellectual property problems. Secondly, a company's existing NPD programme could be disrupted by the implementation of the new approach. Thirdly, the greater degree of customer interaction is almost certain to mean that competitors will get access to information that would for preference remain secret. Finally, certain knowledge and expertise is needed to meet company's objectives through establishing compelling customer involvement. Therefore, in order to balance potential costs and expected benefits, it is necessary for managers to identify their truly needs from big data and plan the customer involvement approach carefully for specific purpose.

Limitations and future research

It is worth to mention that the main focus of this study is to investigate the approaches for utilising big data in new product development. Because the real company situation is more than complicated, for different companies, they have different objectives, R&D focus, big data technology, available data and so on. More importantly, the feedback from the industrialists indicate that most of the companies already have their own big data analytics and technologies. Therefore, instead of conducting specific big data analyses, this research explores the approaches that could support organisations tap into new ideas captured from big data to facilitate their customer involvement in NPD. In this way, future empirical studies can be conducted at the organisational level to identify the implications of the approach. In particular, relevant business models, strategies, as well as data analytics need to be developed to support the approach. Although the findings of this research focus on a high-tech industry, we believe it can be generalised to any industry that applies big data and employs R&D in its product development and enables their businesses to be connected to the Internet. Additionally, in this research we pay attention to the approach needed to achieve customer involvement via unlocking the power of big data and we found that the approach can also be generalised and applied to other properties of the service or product (e.g. software companies, hospitals or real-estate companies). So far, the development of a high-level approach for such a complicated phenomenon as customer involvement in a big data environment may highlight some obvious connections while failing to capture others. The approach applied is mainly focused on utilising big data to improve customer involvement in NPD, where different big data analytics were applied to support each of the stages. Therefore, the approach may not work where there is no data or data analytics to support it. For effective and efficient customer involvement, certain big data skills and knowledge are necessary. However, not every company may have these specific skills and knowledge and it may prove hard to get the information from the right customers.

As illustrated in this paper, big data plays an important role in enabling companies to come up with genuinely innovative new products. On the contrary, customers facing leading edge problems may spark a company's innovation or NPD process. With this study we intended to provide helpful insights into how big data can be used to enhance customer involvement in developing new products. We are hopeful, though, that this broad approach will offer a means to help integrate the wealth of research on big data and NPD in order to advance both research and practice.