The EPSRC-ESRC funded Network in Consumer Goods, Big Data and Re-Distributed Manufacturing (RECODE) has been created to develop an active and engaged community to identify, test and evaluate a multi-disciplinary vision and research agenda associated with the application of big data in the transition towards a re-distributed manufacturing model for consumer goods.

Key Facts

    RECODE Network members have developed novel methods and held innovative events that engaged communities of academics, international experts, user groups, government and industrial organisations to define and scope the shared multi-national vision and research agenda:

    • Feasibility Studies: We have funded five short-term feasibility studies to test and evaluate specific research challenges. These studies were selected from applications submitted by members of the wider network
    • Student Projects: 20 student projects are completed in collaboration with a number of our industrial partners. MSc degrees were awarded based on these projects
    • Future Vision of Manufacturing: The network has made use of an innovative online tools and live events to identify challenges and opportunities for the future of manufacturing
    • Steering Group: We have relied on an active steering group of industrial professionals from across the core themes of the network to guide the research direction and network events.

Impact of our research

  • Mapped the possible consumer interventions across the lifecycle of products, focusing primarily on consumer products. This mapping exercise helped to identify the challenges and opportunities for user engaged design and manufacture, and investigated their application to bridge the gap between users and manufacturers.

  • Delved into fast moving consumer goods (FMCG) by exploring crowdsourcing techniques such as the Open Food gaming portal, to enable consumer interactions at large scale with brands

  • Shoe Lab Story
  • Why the research was commissioned

    This was commissioned to develop an active and engaged community through which to identify, test and evaluate a multi-disciplinary vision and research agenda associated with the application of big data in the transition towards a re-distributed manufacturing model for consumer goods.

    Why Cranfield?

    This research was commissioned by the Engineering Physical Sciences Research Council (EPSRC) and the Economic Social Research Council (ESRC). The RECODE Network core academic partners are: University of Cambridge, University of Manchester, Brunel University and Teesside University. The consortia was led by Cranfield University.

    Key Learnings:

    • The re-distribution of manufacturing for the consumer goods sector is in its infancy in a UK setting. However, there is significant evidence of big data being used to close the gap between the manufacturer and end-user.
    • Is still unclear if the re-distribution of manufacturing is driven by technology push or strategy pull. 
    • RdM needs to take into account not just the re-distribution of location of manufacturing, but also the re-distribution of the value chain, including the raw material, the distributors, and the end user.
    • Our initial assumption was that the transformation to RdM was enabled by technology through bringing the end user closer to the manufacturer and through localisation. However, we learned that other dimensions such as legal, economic and environmental aspects need to be taken into account. 
    • Re-distributed models of production and consumption need to align with a business model. However, maturity on this type of thinking differs between organisations.
    • Technology is currently reaching a tipping point, specially in being use to capture big data to better understand users. However, this data is being use for merely marketing and commercial purposes. Through the research conducted, it was found that there is greater potential to use big data to improve product and service design as well as manufacturing processes. 
    • The RECODE Network took an experimental approach through simulations, design and case study analysis looking at the potential re-distribution of the consumer goods sector. Through this experimental approach, we identified the factors that influence industry towards RdM. Some of these factors are: Competitive advantage, business case, and business model options, mapping the right actors and having the vision to make it happen, making data accessible, and investing on skill for 21st century manufacture and industry connectivity, amongst others. 
    • Up to now there wasn’t an exemplar of all of the elements of RdM. With the Shoe Lab our intention was to give a narrative of how RdM would look like. This narrative happened through explaining a new business model for the consumer goods sector. Having this as an exemplar helps us to map out the ecosystem of actors that would influence and make this happen.  
    • SMEs are disruptors to enable RdM. However, they can threat established firms. For example, the shoe lab  was conceptualised without involving a shoe manufacturer.
    • SMEs are not capitalising on their own data and constantly have issues to access data. 
    • Re-Distributed Manufacturing has the potential to not only change the economics and organisation of manufacturing with regard to location and scale but could radically transform the interrelationships between industry, technology and society as a whole!