| description abstract | The gross domestic product (GDP) of the Canadian construction industry in 2012 amounted to $111 billion, all having been exchanged in the form of invoices. In fact, a typical construction company processes tens of thousands of invoices for payment annually. There are two significant challenges associated with this invoice processing: (1) process costs due to remuneration of the construction owner’s highly paid personnel, and (2) the cost of delayed invoice payments, which is typically a cost absorbed by the contractor that is consequently added to the overall project cost. Ensuring on-time payment of invoices, even when funds are available, can be a challenging exercise because of variety, volume, and the unpredictable number of received invoices. These realities make overdue invoices a pressing problem to be addressed, which in the long term leads to loss in profit and damaged reputation for both contractors and owners. The research presented in this paper utilizes a cohort Markov model to evaluate invoice processing. It seeks to identify and rank bottlenecks to highlight and prioritize opportunities for process improvement, thereby leading to a null-overdue invoice-processing approach. Furthermore, given the stochastic nature of invoice processing, various probabilistic sensitivity analyses are proposed, including an empirical approach that can be used at the experimental design stage where data are either limited or unavailable. | |
