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Facilitating the Implementation and Use of Self Service Business Intelligence
University of Skövde, School of Informatics. University of Skövde, Informatics Research Environment. (Informationsystem, Information Systems (IS))
2022 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

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.

 

Place, publisher, year, edition, pages
Skövde: University of Skövde , 2022. , p. 90
Series
Dissertation Series ; 42
National Category
Information Systems
Research subject
Information Systems
Identifiers
URN: urn:nbn:se:his:diva-21049ISBN: 978-91-984919-6-8 (print)OAI: oai:DiVA.org:his-21049DiVA, id: diva2:1651459
Public defence
2022-05-05, Insikten, Kanikegränd 3A, Skövde, 13:00 (English)
Opponent
Supervisors
Note

Publications with lower relevance:

Rose, J. & Lennerholt, C. (2017). Low Cost Text Mining as a Strategy for Qualitative Researchers. Electronic Journal of Business Research Methods, 15, 2-16.

Available from: 2022-04-13 Created: 2022-04-12 Last updated: 2022-04-13Bibliographically approved
List of papers
1. Implementation challenges of Self Service Business Intelligence: A literature review
Open this publication in new window or tab >>Implementation challenges of Self Service Business Intelligence: A literature review
2018 (English)In: Proceedings of the 51st Hawaii International Conference on System Sciences, Hilton Waikoloa Village, Hawaii, USA: IEEE Computer Society, 2018, p. 5055-5063, article id 0633Conference paper, Published paper (Refereed)
Abstract [en]

In a traditional Business Intelligence (BI) system, power users serve less experienced casual users. Power users analyze and gather data requested by casual users, and produce the reports and visualizations that casual users base their decisions on. When data volumes and the usage frequency of a traditional BI system increase, power users have problems serving all the requests from casual users. The Self Service Business Intelligence (SSBI) approach can enable users to be more self-reliant and less dependent on power users. Although SSBI promises more benefits compared to a traditional BI system, many organizations fail to implement SSBI. The literature review presented in this paper discusses six SSBI challenges related to "Access and use of data" and four challenges related to "Self-reliant users". Awareness of these ten challenges can help practitioners avoid common pitfalls, when implementing SSBI, as well as guide SSBI researchers in focusing on their future research efforts.

Place, publisher, year, edition, pages
Hilton Waikoloa Village, Hawaii, USA: IEEE Computer Society, 2018
Series
Annual Hawaii International Conference on System Sciences. Proceedings, ISSN 1060-3425, E-ISSN 1530-1605 ; 51
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-14618 (URN)10.24251/HICSS.2018.631 (DOI)000625208505014 ()2-s2.0-85044602941 (Scopus ID)978-0-9981331-1-9 (ISBN)
Conference
51st Hawaii International Conference on System Sciences, Hilton Waikoloa Village, Hawaii, USA, January 3-6, 2018
Projects
CCRAAAFFFTING
Funder
Swedish Civil Contingencies Agency, 2016-3046
Note

CC BY-NC-ND 4.0

Available from: 2018-01-04 Created: 2018-01-04 Last updated: 2024-05-16Bibliographically approved
2. Data access and data quality challenges of self-service business intelligence
Open this publication in new window or tab >>Data access and data quality challenges of self-service business intelligence
2019 (English)In: Proceedings of the 27th European Conference on Information Systems (ECIS) / [ed] Paul Johannesson, Pär Ågerfalk, Remko Helms, Association for Information Systems, 2019Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Association for Information Systems, 2019
Keywords
Self-Service Business Intelligence, Challenges, Data Access, Data Quality
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-16935 (URN)2-s2.0-85087103055 (Scopus ID)978-1-7336325-0-8 (ISBN)
Conference
27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019
Note

Research paper

Available from: 2019-06-03 Created: 2019-06-03 Last updated: 2022-04-13Bibliographically approved
3. A Blueprint for Training Future Users of Self-Service Business Intelligence
Open this publication in new window or tab >>A Blueprint for Training Future Users of Self-Service Business Intelligence
2019 (English)In: Business Intelligence Journal, ISSN 1547-2825, Vol. 24, no 1, p. 30-38Article in journal (Refereed) Published
Place, publisher, year, edition, pages
The Data Warehousing Institute (TDWI), 2019
Keywords
self-service business intelligence
National Category
Computer and Information Sciences
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-17278 (URN)
Available from: 2019-06-24 Created: 2019-06-24 Last updated: 2022-04-13Bibliographically approved
4. User Related Challenges of Self-Service Business Intelligence
Open this publication in new window or tab >>User Related Challenges of Self-Service Business Intelligence
2020 (English)In: Proceedings of the 53rd Hawaii International Conference on System Sciences, Hawaii International Conference on System Sciences , 2020, p. 188-197Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Hawaii International Conference on System Sciences, 2020
Series
Proceedings of the Annual Hawaii International Conference on System Sciences (HICSS), ISSN 1530-1605, E-ISSN 2572-6862
Keywords
Business Intelligence, Self Service Business Intelligence, Challenges, Users
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-18162 (URN)10.24251/HICSS.2020.024 (DOI)2-s2.0-85108157729 (Scopus ID)978-0-9981331-3-3 (ISBN)
Conference
The 53rd Hawaii International Conference on System Sciences. HICSS 2020. Maui, United States, January 7-10, 2020
Note

CC BY-NC-ND 4.0

Available from: 2020-01-24 Created: 2020-01-24 Last updated: 2022-04-13Bibliographically approved
5. 13 Organizations' Attempts to Become Data-Driven
Open this publication in new window or tab >>13 Organizations' Attempts to Become Data-Driven
2020 (English)In: International Journal of Business Intelligence Research, ISSN 1947-3591, E-ISSN 1947-3605, Vol. 11, no 1, p. 1-21Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
IGI Global, 2020
National Category
Other Computer and Information Science
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-18032 (URN)10.4018/IJBIR.2020010101 (DOI)2-s2.0-85077520007 (Scopus ID)
Funder
Knowledge Foundation
Note

CC BY 4.0

Available from: 2019-12-25 Created: 2019-12-25 Last updated: 2023-09-25Bibliographically approved
6. User-Related Challenges of Self-Service Business Intelligence
Open this publication in new window or tab >>User-Related Challenges of Self-Service Business Intelligence
2021 (English)In: Information systems management, ISSN 1058-0530, E-ISSN 1934-8703, Vol. 38, no 4, p. 309-323Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Taylor & Francis, 2021
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-19056 (URN)10.1080/10580530.2020.1814458 (DOI)000568943800001 ()2-s2.0-85090986820 (Scopus ID)
Note

CC BY-NC-ND 4.0

Available from: 2020-09-14 Created: 2020-09-14 Last updated: 2022-04-13Bibliographically approved
7. Success factors for managing the SSBI challenges of the AQUIRE framework
Open this publication in new window or tab >>Success factors for managing the SSBI challenges of the AQUIRE framework
2023 (English)In: Journal of Decision Systems, ISSN 1246-0125, E-ISSN 2116-7052, Vol. 32, no 2, p. 491-512Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2023
Keywords
Self service business intelligence, success factors, challenges, SSBI, education
National Category
Information Systems
Research subject
Information Systems
Identifiers
urn:nbn:se:his:diva-21038 (URN)10.1080/12460125.2022.2057006 (DOI)000780314700001 ()2-s2.0-85127119742 (Scopus ID)
Funder
Swedish Civil Contingencies Agency, 2016-3046
Note

CC BY-NC-ND 4.0

Published online: 23 Mar 2022

CONTACT Christian Lennerholt christian.lennerholt@his.se School of Informatics, University of Skövde, Skövde, Sweden

This research was supported by Grant [2016-3046] of the Swedish Civil Contingencies Agency

Available from: 2022-04-06 Created: 2022-04-06 Last updated: 2023-08-15Bibliographically approved

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