Big Data in New Product Development

Today, technology has turned the average customer into an incessant generator of both transactional, traditional, structured data as well as more contemporary, unstructured, behavioural data. The magnitude of the data generated, the relentless rapidity at which data is constantly produced, and the diverse richness of the data are transforming NPD and decision making. This is therefore the era of "big data". Big data is characterised by its 3V characteristics (volume, velocity and variety) and can be generated through different information systems and technologies, including smartphone applications, online communities, sensor networks, internet clicks and social media platforms. By studying the literature, we have identified three phases that big data can be used to support in NPD: generation of ideas and concepts; design and engineering; and test and launch. Potential roles and tasks that can be transferred to customers are demonstrated in each of these phases.

Generation of ideas and concepts

The initial phase is centred on the recognition and creation of opportunities, novel ideas and new product concepts. Big data can be engaged in supporting this phase through the collection of huge amounts of external information to offer managers supportive product ideas. Noteworthy here is the group of inventive customers categorised as 'lead users'. The information generated can be incorporated in proposals from the firm's NPD teams. For instance, Lenovo set up a competition for its customers that involved online services, telematics as well as future PC online assistance systems. Novel ideas generation by the customers has been endorsed by an interactive multimedia tool for services, as well as assessing ideas generated by others. During the initial phase of NPD process, big data enables the integration of customers and turns them into valuable sources to support companies in ideas generation and evaluation.

Design and engineering

In the design and engineering phase, the term 'co-creator' indicates the customer's role more precisely. Six web-based approaches have been proposed by Dahan and Hauser that seek the engagement of the Internet users in an enhanced approach than the conventional market research approaches. For instance, a web-based approach can enable customers to design individual products that will meet their particular needs and wants.

With such techniques, the advantage of using big data in customer involvement (assessed against conventional market research) is that customers are not only asked about their needs, opinions and wants. They can, rather, exhibit their creativity and competence by deriving and assessing new product ideas; they can challenge, explain and enhance detailed solutions; they can identify and individualise virtual prototypes, experimenting with and embracing the novel product features. This can be achieved by conducting simulations, or by acquiring information from different sources regarding a novel product. For instance, Chow Tai Fook Company (a Chinese company engaged in diversified businesses such as jewellery, property and casinos) instituted an internet-based design and launch competition; primarily, customers assessed Chow Tai Fook's idea of 'Forevermark magic', a novel type of jewellery. Subsequently, an internet-based toolkit enhanced customers' individual 'Forevermark magic' design. Within a timeframe of a single month, thousands of customers engaged in virtual dialogue and stated their personal preferences. The sampled individuals were able to create hundreds of appealing designs, which motivated Chow Tai Fook's NPD teams in addition to aiding the assessment of customers' latent needs.

Test and launch

In the test and launch phase, big data allows companies to transfer individuals from different sources (e.g. web-based communities, websites and platforms) into the roles of end customers or buyers. Previous studies have illustrated how customers can represent important resources for a company's development of new products and services. Conventional, manufacture-centric innovation greatly limits the role of the customer. For instance, previously customers (termed 'eventual evaluators') were often used to support companies in fixing bugs. Otherwise, customers were lucky to have any role at all. In contrast, customers can be seen as co-creators or co-developers in a big data environment. For example, Xuancai Company (a Chinese leading game company), in cooperation with China Telecom (one of the largest telecommunication SOE in China), constructed a customer-friendly online platform (PLAY.CN) to enable customers to compose and download their individual internet mobile java games without any special skills (e.g., programming). Enthusiasts of mobile gaming are acquainted with the novel service, platform testing, as well as downloading their self-designed games for their smartphones. As a consequence, more than a million customers have offered their feedback regarding acceptance, usability, intention to play and willingness to pay. In this way, the customers were able to come up numerous improvement ideas for supporting a company's NPD.