The cost of procurement: a neural network approach

Existing research that has attempted to determine differences between the costs of following different procurement routes has consistently aimed to determine a single blanket figure, such as “design and build is 15% cheaper than traditional”. No attempt has been made to provide a difference which is project specific (Duff et al., 1998). Furthermore, no previous research has determined the total cost to the client using any objective method. The lack of data defining client costs and the absence of suitable modelling techniques have prevented such an objective evaluation being made (Masterman, 1994). These factors prompted research into the cost of procurement at UMIST. This research has required the collection of a substantial database of the total cost, to a client, of past projects, and the subsequent creation of a neural network model of these costs. Results of the first phase of development of this model are presented, including regression analysis, preliminary neural network models and sensitivity analysis. An assessment of how these results will inform future development of the model is also made.