Cloud-based decision support systems and availability context: the probability of successful decision outcomes

In an age of cloud computing, mobile users, and wireless networks, the availability of decision support related computing resources can no longer guarantee five-nines (99.999%) availability but the dependence on decision support systems is ever increasing. If not already, the likelihood of obtaining accurate deterministic advice from these systems will become critical information. This study proposes a probabilistic model that maps decision resource availability to correct decision outcomes. Grounded in system reliability theory, the probability functions are given and developed. The model is evaluated with a simulated decision opportunity and the outcome of the experimentation is quantified using a goodness of fit measure and ANOVA testing.