Business intelligence has fundamentally changed how companiesconduct their business. In literature, the focus has been on volume-operationcompanies that provide services to millions of customers. In contrast, complexsystemscompanies have fewer customers and pursue customer needs byproviding more customized products and services. This paper presents the resultsof a case study conducted at a complex-systems company, with the overall aim toidentify how complex-systems companies may take advantage of businessintelligence. A framework was used to measure business intelligence maturity ofthe company. In addition, we also explain the current maturity level of the casecompany,based on critical factors for success adopted from the literature. Indoing so, we also contribute on important details regarding factors that must beconsidered by organizations, in order to leverage their analytical capability.Finally, we also propose topics that need to be further investigated, in order toincrease current knowledge regarding BI usage and maturity in complex-systemscompanies.
Self-service business intelligence (SSBI) enables all users, including those with limited technical skills, to perform business intelligence (BI) tasks without the support of BI experts. SSBI reduces pressure on BI experts, gives more freedom to self-reliant users and speeds up decision-making. Recent research has illustrated how organisations experience numerous challenges when trying to obtain SSBI benefits. The AQUIRE framework organises 37 identified SSBI challenges in five categories: Access and use of data, Data Quality, User Independence, creating Reports and Education. SSBI literature does poorly address how these challenges can be tackled. This research study aimed to identify strategies on how to manage those 37 SSBI challenges. The performed case study includes 24 semi-structured interviews with respondents from two organisations which have been heavily involved in SSBI implementation. The results reveal how nine identified SSBI success factors are related to the 37 AQUIRE challenges and how they can be addressed over time.
BI solutions are constantly being developed to support decision-making at various organisational levels. These solutions facilitate the compilation, aggregation and summarisation of large volumes of data. Consequently, the business value created by these systems is increasing as they sustain more and more advanced analytics, ranging from descriptive analytics, to predictive analytics, to prescriptive analytics. However, most organisations work primarily with internal data. Despite many references in the literature to the value hidden in external data, details on how such data can be used are scarce. In this paper, we present the results of an extensive action case study at a public waste management company. The results illustrate how external data from several external data sources, integrated into an up-and-running BI solution, are used jointly to allow for descriptive and predictive analytics, as well as prescriptive analytics. In addition, details of these analytical values are given and related to organisational benefits.