The area of Business Intelligence (BI) is both broad and multifaceted and is becoming an increasingly pervasive tool utilized within organizations allowing them to gain greater insight into their business operations as well as well as the way in which their customers interact with them. By enabling businesses to perform powerful, effective analytics and reporting, BI tools allow them to maximize use of their data and facilitate better planning, forecasting and the ability to have a more targeted and efficient value chain. Usage of BI tools allow organizations to not only achieve but leverage their competitive advantage. SMEs are no different in their pursuit for competitive advantage and market share but often is the case that they lack the resources in order to make the substantial investments into the software and infrastructure required to host a solution on-premise. The Software-as-a-Service (SaaS) model of allowing users to have access to powerful tools and services without having to purchase the solutions or the infrastructure needed to host it on-premise allows SMEs an ideal opportunity to perform many or all of the functionalities that on-premise BI provides. SaaS BI is a relatively new concept only a few years old, but improvements in functionality and features, reliability of service levels and lower costs are allowing it to gain traction and it is projected to increase its momentum in the next few years. The aim of this paper is to investigate the factors that lead to adoption/non-adoption, assigned importance and perceived business value of SaaS BI within SMEs. These issues will be addressed through identification of the key decision criteria that influence SMEs to adopt SaaS BI solutions over an on-premise solution and vice versa. Greater insight into the decision making process, usage and value will be investigated with the cooperation of two vendors within the BI field. A two pronged approach targeting both SaaS and on-premise BI vendors and the users is adopted in order to find out the perspective on either end and whether or not they are incongruent. Semi-structured interviews were targeted at both an on-premise vendor and a SaaS vendor and their customers. A questionnaire was deployed to clients of both these vendors. Analysis was then conducted on the findings using an integrated selection model encompassing BI and SaaS theories and concepts outlined in the paper.