The group's work is in discovering new and exciting ways of improving data used for organisational decision making.

Research is continuing on the DASHlog project, which is investigating how to improve organisational performance for warehousing and logistics companies by enabling them to adapt quickly to new and changing requirements.

The aim is to develop a solution that can extend existing IT systems and modify current operations so that these types of companies can operate in ‘different modes’, switching between them so that the most appropriate mode is used for different circumstances.

A classic example of a change in circumstances is shopping festivals, which may only occur once or twice a year and for the duration of one or two days. A real example is Singles' Day (or Guanggun Jie) in China on 11^th November, which has become an enormous shopping date with orders reaching more than $25 billion in 2017.

In order to cope with the massive number of orders, warehousing organisations must operate ultra-fast, and the normal everyday operations and use of the IT systems were not designed for this extreme case. So, the question is: should organisations make a sacrifice and operate sub-optimally during the shopping festival (potentially losing significant revenue) or sub-optimally for the rest of the year? The answer seems to be neither, because we have observed that it is possible to change the way the organisation operates just for this special case, and then revert back to normal afterwards.