Högskolan i Skövde

Artificial Intelligence (AI) can take Business Intelligence (BI) to the next level by empowering users in their daily decision-making tasks. Just like Self-Service Business Intelligence (SSBI), AI integrated business analytics comes with many benefits, but also with numerous implementation challenges. In fact, typical SSBI implementation challenges like data quality, data governance, and employee training are equally relevant when integrating AI. Hence, lessons learned from development of SSBI education could increase data literacy and AI literacy. Two case studies of SSBI education in large BI consultancy firms have identified five SSBI education steps: (1) increase the interest of using data; (2) introduce data to all users; (3) clean and define data to create standard reports; (4) develop SSBI data governance and (5) become self-reliant on accessing and using data. SSBI education can create a foundation that leads to being better prepared for the implementation and use of more advanced AI analytics.

Challenges and opportunities for becoming a data-driven organization have been investigated in the literature mostly from the perspective of large organizations. In contrast to previous research, this paper targets a public school in a small municipality that sets up a pilot project for monitoring IoT sensors for indoor and outdoor climate. The public school intended to become more data-driven in its decision-making. Data was collected through interviews, documents, and ethnographic studies. The main findings are that the pilot experienced: i) technical challenges due to faulty sensors and IoT interoperability problems, ii) development challenges due to an unbalanced cross-functional network and poor requirement documentation, iii) raised awareness on indoor and outdoor climate among children and teachers, iv) mixed results of using the dashboards' visualizations, and v) lack of supporting guidelines on how to integrate the system into the organization's daily work.

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.

In traditional Business Intelligence (BI), there is a request-response scenario between technical power users serving non-technical casual users. Today, when data volumes and the frequency of use of a traditional BI system increase, power users are unable to serve all requests from casual users. Self-service Business Intelligence (SSBI) is an upcoming trend that addresses this problem since it enables all users to use BI in a self-reliant manner without support from power users.

The aim of SSBI is to simplify the usage of traditional BI by letting all users conduct their own analysis. Users are allowed to access and use data as desired for their analysis when making decisions, which speeds up the process to use BI. At the same time the pressure on the IT department is relieved, since no power user is needed to support the process. SSBI enables organisations to make time critical decisions without waiting for reports that normally take weeks or months to be delivered. This saves organisational resources since all users can work more effectively and in a self-reliant manner compared to traditional BI. 

Although SSBI offers many benefits compared to traditional BI, many organisations are still struggling and failing to implement SSBI. The process to implement and use SSBI is not an easy task. There is no clear roadmap for how to achieve the SSBI benefits. Therefore, the aim of this thesis is to facilitate the implementation and use of SSBI. Two objectives have been formulated to address this aim. First, it is important to identify what challenges organisations are facing when implementing and using SSBI. The second objective aims to identify success factors for managing the associated SSBI challenges. 

Case study research has been chosen as an appropriate research method to fulfil the research aim and objectives. The case study involves one BI consultancy firm and two of their main customers. The customers are medium-sized organisations which are considered to be the most experienced with implementing SSBI in the consultancy firm’s client base. 

With regard to research objective 1, 37 SSBI challenges have been identified and organized in in five categories of the AQUIRE framework: Access and use of data; Data Quality; User Independence; creating Reports; and Education. For research objective 2, nine success factors for SSBI implementation and use have been revealed as well as how they can be applied over time.  Initially, pilot groups and champions can increase interest in SSBI. Next, user groups and their data needs should be identified, and these user groups should get responsibility to change faulty data. Later, common data definitions and standard reports can simplify the use of data sources. Only then, top management support is needed to accomplish that business governs SSBI data content and that business employees and IT department employees work together in integrated settings. Finally, ongoing SSBI education should target non-technical and technical users differently and change its content over time.

Self-service Business Intelligence (SSBI) allows non-technical users to use Business Intelligence in a self-reliant manner without the support of technical users. Many organizations struggle to utilize the potential of SSBI and experience implementation challenges. This study aims to explore user-related SSBI challenges by conducting 30 qualitative interviews with 2 SSBI implementation projects. Analysis revealed challenges that can help practitioners to avoid unnecessary obstacles when implementing and using SSBI, and guide researchers in simplifying the implementation process.

Becoming a data-driven organization is a vision for several organizations. It has been frequently mentioned in the literature that data-driven organizations are likely to be more successful than organizations that mostly make decisions on gut feeling. However, few organizations make a successful shift to become data-driven, due to a number of different types of barriers. This article investigates, the initial journey to become a data-driven organization for 13 organizations. Data has been collected via documents and interviews, and then analyzed with respect to: i) how they scaled up the usage of analytics to become data-driven; ii) strategies developed; iii) barriers encountered; and iv) usage of an overall change process. The findings are that most organizations start their journey via a pilot project, take shortcuts when developing strategies, encounter previously reported top barriers, and do not use an overall change management process.

Self-service Business Intelligence (SSBI) is an upcoming trend allowing non-technical casual users to use Business Intelligence (BI) in a self-reliant manner without the support of technical power users. Many organizations struggle to utilize the potential of SSBI and experience data-related and user-related SSBI implementations challenges. This study aimed at exploring user-related SSBI challenges by conducting and analyzing a total of 30 qualitative interviews with 5 BI consultants and 10 customer representatives involved in 2 SSBI implementation project teams. Analysis of the interviews revealed ten challenges related to “self-reliant users”, seven challenges related to “creating SSBI reports” and five challenges related to “SSBI education”, which differ considerably from SSBI challenges commonly discussed in literature. Awareness of these 22 challenges can help practitioners to avoid unnecessary obstacles when implementing and using SSBI, and guide SSBI researchers in simplifying the implementation process of SSBI.

Self-service Business Intelligence (SSBI) is an upcoming trend that allows non-technical casual users to use BI in a self-reliant manner without the support of technical power users. Many organisations struggle to utilize the potential of SSBI and experience data-related and user-related SSBI implemen- tations challenges. This study aimed at exploring data-related SSBI challenges by conducting and analysing a total of 30 qualitative interviews with 5 BI consultants and 10 customer representatives involved in 2 SSBI implementation project teams. Analysis of the interviews revealed five challenges related to “Access and use of data” and four challenges related to “Data quality” that differ consid- erably from SSBI challenges commonly discussed in literature. Awareness of these challenges can help practitioners to avoid unnecessary obstacles when implementing and using SSBI. They can also guide SSBI researchers to simplify the implementation process of SSBI.

Municipalities manage a significant part of society's services, and hence also handle a vast amount of information. A municipality's activities include managing a significant part of society's services, and the municipality's supply and management of information are, therefore, critical for society in general, but also for achieving the municipality's own operational goals. However, investigations show weaknesses in the municipalities' work on information security, and there is a need to study and identify the current level of security. This paper presents the result from a GAP analysis mapping the Swedish municipalities current situation for systematic information security work, based on the demands made on municipalities from both research and social perspectives. The result shows that the information security level regarding systematic security work is generally low and that there is a need for adapted tools for Information Security Management Systems in order to support municipalities.