"Today our trust in machines has moved beyond doing something, to deciding what to do, and when to do it. We are starting to be surrounded by autonomous agents." - Rachel Botsman, 'Who can you trust? How technology brought us together and why it might drive us apart', 2017.

Every day we share our personal data through the use of digital technology, producing roughly 2.5 quintillion bytes a day. The world is becoming more connected with the ever-increase of electronic devices connected to the Internet. According to the OCED, the value for big data is $17 billion and is expected to grow at a rate of 40%. Despite the potential of using big data for the delivery of improved value propositions, enhanced efficiency of manufacturing processes and discovering latent customer needs; big data is failing to provide precious, unquantifiable insights from actual people that could help to make the right business decisions and drive meanginful innovations.

The Data-Driven Innovation hub sits within the established Cranfield Centre for Competitive Creative Design (C4D); a rapidly expanding, pan-University facility that works in collaboration with a national and international network consisting of academics, industrial and governmental professionals. At the hub, we try to better understand the nature of people's aspirations, to develop an emotional language that can be embedded into product and service development and delivery. The hub has a high level of expertise in implementing qualitative approaches within collaborative research on quantitative data and data analytics, to unlock the hidden insights that could transform businesses. We seek the most creative individuals, from diverse backgrounds such as mathematics, data analytics and human-centred research from across our MSc programmes, the PhD community and directly from industry, to explore their capabilities to uncover the real power of data.

The Data-Driven Innovation community of practice is led by Professor Leon Williams and aims to be a pioneer in conducting transformational research and deliver educational programmes that could help organisations to make better decisions through the application of data-driven models that can drive meaningful innovations. 

We support other communities of practice within C4D - Circular Economy, Materials Innovation and Breakthrough Innovation - by providing resources that could identify commercial opportunities and value creation activities through different streams of data, identifying user patterns, user behaviour and user preference to design interventions and find solutions that could address intellectual property and data security issues.

Outputs

  • Jones PM, Lonne Q, Talaia P, Leighton GJT, Botte GG, Mutnuri S & Williams L (2018) A straightforward route to sensor selection for IoT systems, Research-Technology Management, 61 (5) 41-50.
  • Ramos A, Talaia P & Queirós de Melo F (2016) Pseudo-dynamic analysis of a cemented hip arthroplasty using a force method based on the Newmark algorithm, Computer Methods in Biomechanics and Biomedical Engineering, 19 (1) 49-59.
  • Barros L, Talaia P, Drummond M & Natal-Jorge R (2014) Facial pressure zones of an oronasal interface for noninvasive ventilation: A computer model analysis, Jornal Brasileiro de Pneumologia, 40 (6) 652-657.