Estágio realizado na Sage Portugal e orientado pelo Eng.º Jorge Santos Carneiro / Tese de mestrado. Engenharia de Serviços e Gestão. Faculdade de Engenharia. Universidade do Porto. 2009

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. 

<p>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.</p><p></p>

Using Software-as-a-Service (SaaS), software resides on servers not on user computers. Service Oriented Architecture (SOA) provides the ability to divide an application into parts known as services. This allows enhanced support for distribution, code re-use and code sharing. Combining these ideas, applications can be dynamically composed from components stored at convenient locations in a wide-area network. This benefits users since software installation and upgrades are unnecessary and is also suited to personal devices that may have limited resources (e.g. disk space) to support conventional installed software. I have designed, prototyped, and evaluated component-placement and location algorithms for a system that combines ideas from SaaS and SOA to support on-demand composition of applications that run on user devices from storage sites in the network. These algorithms support mobility and are scalable and reliable. I have implemented a Java prototype and a simulation system that I used to assess my system’s behaviour.

Using Software-as-a-Service (SaaS), software resides on servers not on user computers. Service Oriented Architecture (SOA) provides the ability to divide an application into parts known as services. This allows enhanced support for distribution, code re-use and code sharing. Combining these ideas, applications can be dynamically composed from components stored at convenient locations in a wide-area network. This benefits users since software installation and upgrades are unnecessary and is also suited to personal devices that may have limited resources (e.g. disk space) to support conventional installed software. I have designed, prototyped, and evaluated component-placement and location algorithms for a system that combines ideas from SaaS and SOA to support on-demand composition of applications that run on user devices from storage sites in the network. These algorithms support mobility and are scalable and reliable. I have implemented a Java prototype and a simulation system that I used to assess my system’s behaviour.

Our society is increasingly entangled with, and reliant on software. Previously, software has mainly been operated on-premises, i.e., installed and ran on a physical computer, manually supported, and maintained by individuals at the location where the software is running. Today, software is often delivered via the cloud using a pay-as-you-go subscription service, hosted, and continuously supported by the vendor, i.e., the organization providing the solution. A collective name for this type of solution is “Software-as-a-Service” (SaaS). SaaS is a popular delivery model amongst software start-ups, who are known to be innovative and create valuable new solutions that benefit society. Hence, it can be valuable to help SaaS start-ups understand how most effectively navigate and reach their first customers. This thesis does this by investigating what buyers find important when buying SaaS from a start-up vendor. Technology and innovation adoption has been extensively studied. Theories such as the “TOE-framework” and “Diffusion of Innovation” attempt to explain how the adoption of new solutions is determined and what factors influence it. Moreover, multiple studies have also investigated what affects the decision to buy SaaS. Finally, studies have examined what buyers find important when buying from a start-up. However, no studies have explored what buyers consider when buying SaaS from a start-up vendor. This thesis aims to fulfill the research gap presented above and to answer the following research questions:   What are the determining factors for adoption of Software-as-a-Service delivered by a start-up vendor? How do these determinants affect adoption? To answer the research questions, the study utilizes a deductive approach with elements of induction. Qualitative data is collected in 8 semi-structured interviews, all with a focus on buying organization's SaaS adoption decision. The interview structure is based on the theoretical framework which consists of four major categories that can affect adoption: “Technology”, “Organization”, and “Environment”, of the TOE-framework, and “Vendor Relationship” which is added by the authors of this thesis based on prior studies that suggested this as an important aspect in for the studied context. Within each major category, determinants of adoption, i.e., factors that influence the decision to adopt, are derived from theories specific to SaaS and start-up adoption. The findings confirm all four of the overarching categories of the theoretical framework as important in the decision to adopt SaaS from a start-up vendor. The confirmation of the vendor relationship category can be considered a key finding of the thesis since it is not present in the original TOE-framework or any of the studies on SaaS and start-up adoption. On a more granular level, the thesis highlights the observed adoption determinants under each of the categories and describes how they relate to each other and to existing theory. By answering the research questions, the thesis provides useful insights that can help SaaS start-ups better understand what factors potential buyers consider in their adoption decision. As a result, start-ups can better align their strategy with the wants and needs of buyers and increase the probability of success. Finally, the thesis contributes to theory by expanding knowledge related to the factors determining the adoption of SaaS, when it is delivered by a start-up vendor.

Tese de mestrado. Engenharia de Serviços e Gestão. Faculdade de Engenharia. Universidade do Porto. 2009

Projecto realizado na Sage Portugal - Software, S. A. e orientado pelo Eng.ª Fernanda Marmelo / Tese de mestrado. Engenharia de Serviços e Gestão. Faculdade de Engenharia. Universidade do Porto. 2009

The theme of this thesis is one of ways, which develops area of Business Intelligence in the last few years. This way are BI systems design on the principle of Cloud computing, also called BI SaaS. This is a cost available solution also suitable for small companies. This work is aimed to acquaint the reader with basic theoretical knowledge in the areas of Cloud computing, Business Intelligence and their connections. Wants to show risks of this technologies and compare between on-premise and cloud BI. In the next step want to offer a practical comparison of selected BI SaaS systems. Finally it aims to create forecast of possible future paths of development in Business Intelligence.

Enterprise systems have been used since the 1970s. They have changed over the time but their main purpose - to automate and streamline the corporate processes, is still the same. However the scope has increased and the enterprise systems became very widespread. They integrate many usefull utilities into one system and have moved from the mainframes to common desktop computers. The abreviation ERP is very well known in today's IT world. It would be really difficult to find a large or midsize company which does not use the enterprise resource planning system. Yet the situation is dramatically different at the small enterpirse market. Due to theirs complexity, ERP systems are expensive. Many small companies are unable to afford heavy investments into the software they are using. Such enterprises can use the lightweight versions of the commercial solutions or not to use ERP systems at all. There is a new business trend - the SaaS business model. It is based on providing the access to the system over the network for regular fees. These fees are smaller than the licence ones so that it is easier for small companies to get up to ERP systems that would be too expensive for them otherwise. Even big software companies (such as SAP) have been getting engaged with the adoption of the SaaS recently. The IT experts say the SaaS business model is to be very prospective. The goals of this dissertation consist of the analysis of providing the ERP system as a service and the description of technical and processionary aspects that are mandatory for succesful adoption of the SaaS business model. A proprietary solution of the ERP system will be provided as a part of this thesis. The solution would be designed and developed especially for purposes of the adoption of the SaaS model.