Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approach
Abstract The ability to leverage data science can generate valuable insights and actions in organisations by enhancing data‐driven decision‐making to find optimal solutions based on complex business parameters and data. However, only a small percentage of the organisations can successfully obtain a...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Hindawi-IET
2021-12-01
|
| Series: | IET Software |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/sfw2.12033 |
| _version_ | 1797429309728620544 |
|---|---|
| author | Mert O. Gökalp Kerem Kayabay Ebru Gökalp Altan Koçyiğit P. Erhan Eren |
| author_facet | Mert O. Gökalp Kerem Kayabay Ebru Gökalp Altan Koçyiğit P. Erhan Eren |
| author_sort | Mert O. Gökalp |
| collection | DOAJ |
| description | Abstract The ability to leverage data science can generate valuable insights and actions in organisations by enhancing data‐driven decision‐making to find optimal solutions based on complex business parameters and data. However, only a small percentage of the organisations can successfully obtain a business value from their investments due to a lack of organisational management, alignment, and culture. Becoming a data‐driven organisation requires an organisational change that should be managed and fostered from a holistic multidisciplinary perspective. Accordingly, this study seeks to address these problems by developing the Data Drivenness Process Capability Determination Model (DDPCDM) based on the ISO/IEC 330xx family of standards. The proposed model enables organisations to determine their current management capabilities, derivation of a gap analysis, and the creation of a comprehensive roadmap for improvement in a structured and standardised way. DDPCDM comprises two main dimensions: process and capability. The process dimension consists of five organisational management processes: change management, skill and talent management, strategic alignment, organisational learning, and sponsorship and portfolio management. The capability dimension embraces six levels, from incomplete to innovating. The applicability and usability of DDPCDM are also evaluated by conducting a multiple‐case study in two organisations. The results reveal that the proposed model is able to evaluate the strengths and weaknesses of an organisation in adopting, managing, and fostering the transition to a data‐driven organisation and providing a roadmap for continuously improving the data‐drivenness of organisations. |
| first_indexed | 2024-03-09T09:11:18Z |
| format | Article |
| id | doaj.art-c8865220ef5546d685c66c3f5860e914 |
| institution | Directory Open Access Journal |
| issn | 1751-8806 1751-8814 |
| language | English |
| last_indexed | 2024-03-09T09:11:18Z |
| publishDate | 2021-12-01 |
| publisher | Hindawi-IET |
| record_format | Article |
| series | IET Software |
| spelling | doaj.art-c8865220ef5546d685c66c3f5860e9142023-12-02T08:45:47ZengHindawi-IETIET Software1751-88061751-88142021-12-0115637639010.1049/sfw2.12033Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approachMert O. Gökalp0Kerem Kayabay1Ebru Gökalp2Altan Koçyiğit3P. Erhan Eren4Informatics Institute Middle East Technical University Ankara TurkeyInformatics Institute Middle East Technical University Ankara TurkeyInformatics Institute Middle East Technical University Ankara TurkeyInformatics Institute Middle East Technical University Ankara TurkeyInformatics Institute Middle East Technical University Ankara TurkeyAbstract The ability to leverage data science can generate valuable insights and actions in organisations by enhancing data‐driven decision‐making to find optimal solutions based on complex business parameters and data. However, only a small percentage of the organisations can successfully obtain a business value from their investments due to a lack of organisational management, alignment, and culture. Becoming a data‐driven organisation requires an organisational change that should be managed and fostered from a holistic multidisciplinary perspective. Accordingly, this study seeks to address these problems by developing the Data Drivenness Process Capability Determination Model (DDPCDM) based on the ISO/IEC 330xx family of standards. The proposed model enables organisations to determine their current management capabilities, derivation of a gap analysis, and the creation of a comprehensive roadmap for improvement in a structured and standardised way. DDPCDM comprises two main dimensions: process and capability. The process dimension consists of five organisational management processes: change management, skill and talent management, strategic alignment, organisational learning, and sponsorship and portfolio management. The capability dimension embraces six levels, from incomplete to innovating. The applicability and usability of DDPCDM are also evaluated by conducting a multiple‐case study in two organisations. The results reveal that the proposed model is able to evaluate the strengths and weaknesses of an organisation in adopting, managing, and fostering the transition to a data‐driven organisation and providing a roadmap for continuously improving the data‐drivenness of organisations.https://doi.org/10.1049/sfw2.12033investmentdecision makingmanagement of changeorganisational aspectsinnovation management |
| spellingShingle | Mert O. Gökalp Kerem Kayabay Ebru Gökalp Altan Koçyiğit P. Erhan Eren Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approach IET Software investment decision making management of change organisational aspects innovation management |
| title | Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approach |
| title_full | Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approach |
| title_fullStr | Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approach |
| title_full_unstemmed | Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approach |
| title_short | Assessment of process capabilities in transition to a data‐driven organisation: A multidisciplinary approach |
| title_sort | assessment of process capabilities in transition to a data driven organisation a multidisciplinary approach |
| topic | investment decision making management of change organisational aspects innovation management |
| url | https://doi.org/10.1049/sfw2.12033 |
| work_keys_str_mv | AT mertogokalp assessmentofprocesscapabilitiesintransitiontoadatadrivenorganisationamultidisciplinaryapproach AT keremkayabay assessmentofprocesscapabilitiesintransitiontoadatadrivenorganisationamultidisciplinaryapproach AT ebrugokalp assessmentofprocesscapabilitiesintransitiontoadatadrivenorganisationamultidisciplinaryapproach AT altankocyigit assessmentofprocesscapabilitiesintransitiontoadatadrivenorganisationamultidisciplinaryapproach AT perhaneren assessmentofprocesscapabilitiesintransitiontoadatadrivenorganisationamultidisciplinaryapproach |