Decision Support System For Cost-Benefit Analysis In Service Provision

Cost-benefit analysis is an approach to relate effort and cost of an activity to the resulting benefit. In this paper a novel decision support system for cost-benefit analysis in the context of service provision is proposed. Four decision support scenarios are investigated: (i) analyzing the impact of the services on cost and benefit, (ii) sensitivity analysis for the system variables, (iii) goal-seek analysis, and (iv) analyzing the impact of the services on operational resources. The key engine of the analysis approach is a Bayesian Belief Network (BBN). The BBN incorporates the key incoming, control and outgoing service parameters as well as their probabilistic relationships. In the sense of a hierarchical system, the variation of some of the parameters is guided by the results of optimizing operational resources being some of the BBN parameters. We've evaluated the framework in a case study with the City of Calgary's Waste and Recycling Services. The results showed that using such a DSS facilitates the decision making process and improves the overall cost-benefit ratio.