Abstract
Business intelligence (BI) solutions have been adopted within organizations as amean to achieve a more grounded decision making process that results in better organizational outcomes. Nowadays, about 70% to 80% of business intelligence implementation projects fail due to both technological and managerial issues. Multi-methodology proposed by Mingers (2006) was followed to develop the research in four phases: appreciation, where documental search wasconducted through a literature review; analysis, where hypothetical structures related with the key success factors were proposed; assessment, where key success factors were assessed along with experts; and action, where research results discussion was shown. As a result, 13 factors that affect the business intelligence solution’s success were identified. Those factors contributeto improve planning and implementation of business intelligence projects, accomplishing in a greater extent the purposes of these projects.
Highlights
For companies and institutions to survive in the economy and in the business world, decisions must be accurate and made on time (Karim 2011; Olszak 2016)
This key success factor is one of the most used in Business intelligence (BI) research, since it is focused on architecture, software and tools development and tangible elements whose impact is reflected in practice by its operative characteristics (Loshin 2013)
From the topics analysis of conducted interviews, results show that twelve pieces of literature identified factors that are consistent with experts’ perceptions about BI solutions success, adding the Professional Networks factor according its importance to the experts
Summary
For companies and institutions to survive in the economy and in the business world, decisions must be accurate and made on time (Karim 2011; Olszak 2016). From a specific perspective there are problems related to the project leaders, sponsorship, solution requirements, designs, training, tools, tracing, posted objectives, estimated time to execution, data, data sources, problems with the technology handling, user needs, and investments, among others (Ahmed 2014; Castelán et al 2010; EMC Consulting 2010; Gurjar and Rathore 2013; Herrera 2011; SAP 2013) Those failures produce problems within organizations such as wasted of resources, time, and costs of opportunity of invested capital, as well as an inability to achieve expected benefits (Ortiz 2014). All of these take contributions from several authors, validate those contributions at an organizational level and generate factors or specific characteristics that allow organizations to get greater effectivity rates in the adoption and implementation of these type of projects
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