- Gerry Frizelle — Cambridge University
- Janet Efstathiou — Oxford University
Manufacturing processes and supply chains show all the characteristics of complex systems. The focus of this research area is on those aspects of complexity that can be measured. Theory suggests that an appropriate metric is the average rate at which the supply chain or manufacturing process generates information i.e. the entropy of the process. This is called its Operational complexity. Theory also predicts that operational complexity shows itself through the formation of queues – these can be of either products or information. The important point is that the system’s performance is capable of being directly measured by observing the dynamic behaviour of these queues and their causes.
However complexity is neither good not bad. For example mass customisation involves deliberately expanding the complexity of the product range to offer customers greater variety. The key is to be able to do this without raising prices. Therefore one can differentiate between ‘good’ complexity – complexity the market will pay for and ‘bad’ complexity that merely involves additional cost. This is the balance a successful mass customisation strategy achieves. One important dimension is the ability to schedule effectively. Here too the notion of information generation is central. The schedule embodies a quantity of information – the more complex the plant or supply chain the more information contained. A system that follows the schedule generates no further information. Therefore observing how much additional information the system generates is a measure of its performance against the schedule.
Observations made within factories and, more recently, on supply chain have confirmed the validity of the approach and the utility of the measures.