Centre for Business Analytics in Practice research

The Centre for Business Analytics in Practice focuses on developing and disseminating theoretically driven, empirically rigorous research in the area of data-driven decision-making, particularly in its application outside academia.  

Areas of research

We are engaged in the following areas of research:

  • Efficiency and productivity
  • Sustainability and net-zero analytics
  • Operations and supply chain analytics
  • Health analytics
  • Artificial intelligence
  • Big data

Projects 

  • A workflow project with Royal Mail” - Funded by Knowledge Transfer Partnership (KTP). (Professor James Aitken)
  • An inventory modelling activity for Tilda Limited” - Funded by Knowledge Transfer Partnership (KTP). (Professor James Aitken)
  • Analysis of efficiencies and productivity evolution in manufacturing industries with CO2 emissions” funded by the Royal Academy of Engineering. (Professor Ali Emrouznejad)
  • Economic Impact of the University of Essex on the Local, Regional and National Economy (Research Lead, University of Essex, 2015)” - Estimating the overall impact on the University of Essex’s operations on the local, regional and national economies. (Dr Abhijit Sengupta)
  • ESRC Business and Local Government Data Research Centre (2014-2019)”-  One of the named researchers in the £5 million ESRC funded big data research centre. (Dr Abhijit Sengupta)
  • "Exploring power dynamics in digital platforms". Funded by British Academy/Leverhulme Small Research Grants (Dr Mahdi  Tavalaei)
  • Measuring efficiency of small-scale sugarcane growers in Africa” - Funded by British Council and several others. (Professor Ali Emrouznejad)
  • Supply chain improvement projects for a company that remanufacturers 1920s Bentley cars” - Funded by Knowledge Transfer Partnership (KTP). (Professor James Aitken)
  • Transportation optimization with Surrey County Council” - Funded by Knowledge Transfer Partnership (KTP). (Professor James Aitken)
  • Use of Insurance to Manage Reliability in the Distributed Electricity Sector (2019-2020)” - Modelling energy transition from centralized grid structures towards decentralized insurance based schemes using complex systems and simulation based approaches. (Dr Abhijit Sengupta)
  • Use of Machine Learning to optimise milk yields and animal feed in the supply chain through to the cheese manufacturing processes” - Funded by Knowledge Transfer Partnership (KTP). (Professor Ali Emrouznejad).