Evaluation of Business Intelligence in telecommunications companies

Breno Brand Fernandes


TemboSocial Inc, Toronto, Canada

Priscilla Cristina Cabral Ribeiro


Fluminense Federal University – UFF, Niterói, Rio de Janeiro, Brazil

Helder Gomes Costa


Fluminense Federal University – UFF, Niterói, Rio de Janeiro, Brazil


Highlights: Most companies have issues with large volumes of data, lack of information, knowledge, and insufficient reporting. Business Intelligence (BI) allows companies to find patterns and connections between apparently independent and disconnected pieces of data. Evaluating success or effectiveness of information systems is crucial for investment in these technologies. Despite advancements made by evaluation studies, there is still a gap in regard to BI-oriented evaluation models.

Objective: Propose and apply a model for BI evaluation in telecommunication companies through IT evaluation attributes. Design/Methodology/Approach: In order to develop the research, an alignment between literature review and field research was made. Multiple case studies of qualitative approach were used as method, using semi-structured interviews as data collection techniques. These were conducted with IT managers and system users.

Results: Despite the main advantages, BI's disadvantages and aspects for obtaining success were identified in literature and are aligned with the field research. It was found that motivations and pressures for BI implementation are principally related to the alignment of the organization's strategic planning to BI's benefits.

Investigation's limitations: Not all hardware attributes can be applied to software evaluation processes, similar to how some are not appropriate to the service sector. Thus, this work's proposition focuses on software evaluation attributes.

Practical implications: From a management perspective, this article contributes with the proposition of a new set of key attributes to the evaluation of BI after its implementation in companies which are not necessarily in the telecommunications sector.

Originality/Value: Despite the adoption and growth of BI, there is a gap to be filled regarding models for the technology evaluation. This type of model is crucial for understanding why a tool with a number of advantages is still affected by implementation difficulties and use in the telecommunications sector. Therefore, this work provides a set of evaluation attributes supported by literature which can subsidize the development of new evaluative studies that are not restricted to IT.

Keywords: Evaluation; Model; Business Intelligence; Telecommunication.


Most companies have issues with large volumes of data, lack of information, knowledge, and insufficient reporting (Farrokhi, 2012; Gandomi et Haider, 2014; Alpar et al., 2015). Meanwhile, executives prefer to work with singular and integrated information instead of a larger number of reports originating from different information systems (Ferreira et Kuniyoshi, 2015). In the case of small and medium businesses, the businessperson or executive needs to know the impact adequate information management can have on the organization’s performance. (Sanchez Limón et De la Garza Cárdenas, 2018). This allows competition in better conditions through enabling cost reduction, quality improvement, shorter deadlines, product diversification, and better post-sales service (Leal Morantes et al., 2018).

In this context, Business Intelligence (BI) appears as a tool of integration, transformation, interpretation, and viewing of this data (Duan et Xu, 2012; Chen et al., 2012). BI allows companies to find patterns and connections between apparently independent and disconnected pieces of data. This allows for there to be new answers to the organization’s needs and the creation of fundamental information to decision-making (Kowalczyk et al., 2013; Chaudhuri et al., 2011).

In order to decrease investment risks in information technology (IT) that relate to lack of alignment between the technology and business strategies, it is necessary to have an effective evaluation policy or a set of guidelines that follow these investments (Lönnqvist et Pirttimäki, 2006; Ribeiro, 2010). For Delone et McLean (2003). The evaluation of success or effectiveness of information systems is fundamental to investing in these technologies.

Considering this, the main research question is: how to evaluate BI in companies of the telecommunications sector? This central question leads to the following secondary questions: what are BI’s advantages and disadvantages? What are the pressures and motivations to the implementation of BI?

Despite the advancements already made with the studies developed, there is still a gap regarding dedicated models, specifically relating to the evaluation of BI (Popovič et al., 2014; Bole et al., 2015). Taking this into consideration, this work’s general objective is to propose and apply a model for BI evaluation in telecommunication companies through IT evaluation attributes. This contribution lies in filling this gap by proposing a model to evaluate BI.


The methodological stages of the research were structured and organized, aiming at reaching the answer to the main research question, which in turn was reached through obtaining answers to the secondary questions. These were obtained through developing the actions indicated in Figure 1:

Figure 1. Research secondary questions and actions conducted to answer them.


In order to answer the main research question, articles found in the bibliographic review and exploratory research were used. They were organized into two groups: IT evaluation and BI evaluation. The first group was split into two perspectives: the financial one and the most complex evaluation models. In the first one, contributions to building the model were found, as it will be disclosed ahead. In the second, the contributions came from two studies from DeLone et McLean (1992; 2003)—which display a great number of citations in the leading IT journals (11.654 and 9.654 citations on Google Scholar, respectively, by August 2018). The majority of subattributes were extracted from them (23 out of the 21 cited here were mentioned by them).

In the second group, BI evaluation, another set of authors was utilized. Among the ones consulted, the main ones were selected after their publications had been read, their contribution had been analyzed, and their relevance to the research had been verified Figure 4). To organize the variables, the method proposed by Ribeiro (2010) was utilized with the goal of organizing the contributions to attributes and subattributes and the area of operation (IT or BI). The answers to the main question are indicated in Figures 9 and 10.

Regarding the field research, the semi-structured question script was utilized to answer the questions in Figure 1. Likert’s scale was used as a scale for the answers to these questions, from 1 to 5 associated to it for classification (1 = very low; 2 = low; 3 = average; 4 = high; 5 = very high). In Figure 9 the interviewees’ scores and their sum are indicated in the last column. Therefore, BI’s evaluation by the respondents is known through close-ended questions. In Figure 10 the analysis of BI by its score frequency was preferred in order to conclude whether it obtained a positive score (greater number of “4” and “5” answers), an average score (greater number of “3” answers) or if it needs to improve (greater number of “1” and “2” answers).

After the questionnaire’s data collection, the subattributes Complexity and Integration of the attribute System’s Quality had their scales inverted because differently from all the other subattributes, the greater weight given in the answer, the more negatively the answer will affect BI’s evaluation. In order to process the registered information, the following criterion was adopted for answers of interviewees from the same organization: the interviewees’ answers (scores from 1 to 5) given to a single subattribute were subtracted one from the other. Results superior to |1| were considered divergent answers.


The literature review and research results will be shown in this item.

3.1 Literature review

The literature review was conducted in order for answers to be obtained for the questions in Figure 1. The process chosen for the literature review has as basis the article by de Carvalho Pereira et al. (2017) (with a few steps being independent from the model utilized by the authors). The bases utilized for the research were articles indexed on the databases Web of Science (ISI) and Scopus, resulting in an 85-article set. The next stage consisted of manual verification of titles and summaries for the verification of adherence of the articles selected to the theme. The starting point for the literature review is a sample with 57 articles that served as basis for the model construction. The reason is that after filtering, a few articles that had been excluded during the filtering process were restored to the sample due to their adherence to the theme. From that collection, some points were raised for this review, such as the advantages shown in Figure 2.

Figure 2. Advantages of BI.


Despite the fact that the adoption of BI and its set of techniques brings several advantages as previously stated, there is risk both in adopting and in not adopting BI. In any relevant investment a few points must be observed, such as: possibility of early return and impact on competitiveness, effects of the adoption on the organization’s internal processes; opportunity cost of other investments, and the possibility that the tool will undermine another investment or render it useless (Isaca, 2014). From the texts analyzed in this research Figure 3 was constructed; it summarizes the disadvantages of BI.

Figure 3. Disadvantages of BI.


Additionally, the literature review sought to identify the characteristics that a BI evaluation model must have. Figure 4 synthetizes the search results.

Figure 4. Attributes and subattributes for BI and IT evaluation.

Figure4 Figure4

3.2 Field research

The field research aimed at evaluating BI adoption in Brazilian companies operating in the Brazilian telecommunications sector.

3.2.1 Sample

Semi-structured interviews in companies that operate in the telecommunications sector in Brazil were conducted for data collection and analysis. The data was collected through a research tool consisting of an open-ended and close-ended questions script. Likert’s scale was used as a scale for the answers to these questions; it is symmetric and balanced, allowing one to measure the degree of agreement with the questions asked to the respondent through five “stance areas” (Likert, 1932). The scale ranges from 1 to 5; 1 = very low; 2 = low; 3 = average; 4 = high; 5 = very high. The unities of analysis were three companies whose characteristics are summarized in Figure 5.

Figure 5. Characteristics of the companies investigated.


Caption: NA = not answered

In each researched organization two employees were chosen, aiming at contemplating both perspectives visualized by BI: technique, composed of the set of IT tools that constitute it, represented by the IT manager, the provider; and management, which considers all the benefits BI brings the organization, represented by the organization’s manager, who is the user of the information extracted from the system (Pirttimäki et al., 2006). The interviewee’s characteristics are summarized in Figure 6.

Figure 6. Interviewees’ profiles.


3.2.2 Data analysis—open-ended questions

At the first stage of field research, the interviewees were asked three open-ended questions: (a) In your perception, what were the advantages of adopting BI?; (b) In your perception, what were the disadvantages of adopting BI?; (c) In your perception, what were the main pressures and motivations for implementing BI in your company? Figure 7 shows a compilation of the answers given by the interviewees, comparing the advantages (Figure 2) and disadvantages reported in literature (Figure 3), considering questions a and b.

Figure 7. Advantages and disadvantages perceived by the companies reported in literature.


Obs. Advantages and disadvantages indicated in Figures 2 and 3

The analysis of Figure 7 shows:

The last aspect raised as a disadvantage in Figure 3 (difficulty by some BI system users in dealing with large amounts of information, and archiving these reports due to physical limitations) was perceived as motivation by companies to adopt BI. As a solution, company B designed a procedure oriented at reporting according to the business’s demands. One of the problems indicated in literature is the physical limitation on report archiving (Schulz et al., 2015). On this front, Alpar et al. (2015) suggest reutilizing and sharing reports among the organization’s areas, a practice adopted by the three companies studied here.

Figure 8 shows the compilation of answers to question (c): “In your perception, what were the main pressures and motivations for implementing BI in your company?” and the comparison to the results found in the literature review. Due to company A’s size, the pressure to stay afloat did not influence its decision to implement BI.

Figure 8. Motivations to implement BI.


3.2.3 Results analysis—close-ended questions

Here the answers obtained via a close-ended questionnaire are analyzed through the contrast between the answers of the IT manager and the system user’s. It should be noted that letter “M” was used to indicate the manager’s answers whereas “U” indicates the user’s.

In Figure 9 one can notice that the IT managers and users’ answers (score/evaluation) showed little divergence, even though there is different scoring in most attributes. This is due to the plurality of the user profiles, since this groups of users contains economists, advertisers, technical support agents, and IT managers. Previous experiences can lead to different scoring, given that most divergences happened due to lack of technical knowledge by the users. This affected other questions, such as easy learning, intended use, and voluntary use.

Figure 9. Field-collected data: Scoring by the interviewees evaluating BI.


Caption: M = IT manager; U = User

According to Moore et Benbasat (1991), the attribute “voluntary use” is connected to the quality perceived by the user. Thus, since the user considered it difficult to generate reports, as stated in the open-ended questions, they distanced themselves from the system, therefore affecting its voluntary use.

The subattribute “complexity” had the lowest total score at 16 points. This attribute is generally linked to ease of use. Access level initially seems to be a specific characteristic of company B, where it scored low, and is an important attribute for BI success, according to Işik et al. (2013). With extended use of BI—from, the strategic sphere to operations—the amount of reporting experienced noticeable growth. Alpar et al. (2015) suggest report reutilization and sharing among areas of the organization as a solution to this problem. All the companies from the study cases archive and reutilize or share their reports among the organization’s areas as literature suggests. The subattribute “better results” had the highest total score at 29 points. It was followed by up-to-dateness and accuracy, at 28 each. It can be said that, as a general rule, the benefits of BI extracted from the field research are aligned with the literature.

While Figure 9 shows data collected in the field from a horizontal perspective, once the data is transformed into frequency perspective, as seen in Figure 10, vertically, it is credible that 80% of answers had positive scoring, 4 and 5. 50% of answers were concentrated at high score (4) and 30% at very high (5). The analysis of BI through the presented scale leads one to assume BI was evaluated as above average in the three companies studied, in spite of the identified disadvantages.

Figure 10. Data from the study cases from a frequency perspective.



It was verified that the advantages and benefits of BI reported in literature as key to its evaluation were confirmed by the case study participants. BI is acknowledged as a strategic tool that centralizes information in real time (updated information) from various perspectives, ensuring a better understanding of the organization, which results in faster decisions of higher quality. This information is normally presented through reports with dashboards and indicators that facilitate its interpretation.

With regard to disadvantages, the concept of BI 2.0, a trend according to scientific literature, was scarcely identified in practice. Only one of the organizations showed, in some aspect, the existence of interaction between company, providers, and clients in a single BI system. Even when it was identified, interviewees diverged about its functionality. The other disadvantage found was the difficulty in selecting which report to use in the decision-making, given the large amount of information available through BI. As a solution to this problem, one of the organizations developed a procedure oriented at generating and selecting reports. The complexity of using BI, highlighted in this research, caused other aspects, such as ease use and voluntary use, to be negatively affected, resulting in another negative perspective of BI. This setting requires greater attention to the training of users and managers in order to diminish this negative view so it does not affect the use experience.

With data decentralization inside organizations, reporting with information in real time rise as the main motivation to implement BI. Integrating data in a system is crucial because it not only adds quality to decision-making, but also reduces costs and time otherwise directed at manually generating reports that integrate different data. The large volume of data, lack of information on time and insufficient reporting are elements that act as forces pushing toward the adoption of BI. Another force is the organization’s strategic alignment with investing in technology for the organization’s evolution and survival.

A number of requirements were identified as decisive for the success of BI, such as: previous experience with the analytic decision process; the identification of whether there is alignment between the benefits BI can offer the organization and its strategic planning; support from the board of directors; and a leader figure in the organization that establishes communication between BI’s technical part and the organization’s other departments.

According to the case studies, even without financial metrics, that is, without conducting a financial study about BI’s ROI, its viability through intangible concepts suffices for the decision to implement it. The increase in the organization’s value due to BI is sufficient for its implementation. Therefore, it is critical that one assesses whether the benefits of BI align with the organization’s strategic planning. The implementation in each of the three companies investigated was successful, despite its having been carried out from a project of little structure. This data suggests that its implementation does not necessarily demand a complex project, which can be justified by the low level of complexity in implementing this type of system, that injects greater work in the stage at which data from various sources is unified.

For future studies, it is suggested that a structured survey be conducted with IT experts, preferably managers, who were involved in the process of implementing BI in technology companies.

The research aims at evaluating IT inasmuch as investment in this area in private and public companies can be overrated or underrated, if the product to which the institution’s or society’s resources are allocated is not evaluated.

Considering the literature review, other researchers can have a foundation on which to develop their studies. The set of attributes identified in the research of the leading authors on technology and information systems evaluation models allows readers to understand and reproduce this proposition; alternatively, they can develop another one based on the information available here. Furthermore, the model presented here can contribute to the creation of other evaluation models not exclusively aimed at IT.


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Received: Nov 15 2018

Approved: Jan 07 2019

DOI: 10.20985/1980-5160.2019.v14n1.1480

How to cite: Fernandes, B. B.; Ribeiro, P. C. C.; Costa, H. G. (2019), “Evaluation of Business Intelligence in telecommunications companies”, Sistemas & Gestão, Vol. 14, N. 1, pp. 64-76, available from: http://www.revistasg.uff.br/index.php/sg/article/view/1480 (access day abbreviated month).