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IT Governance Decision Support using the IT Organization Modeling and Assessment Tool
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0002-3293-1681
KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.ORCID iD: 0000-0003-3922-9606
2008 (English)In: 2008 Portland International Center for Management of Engineering and Technology, Technology Management for a Sustainable Economy, PICMET '08, New York: IEEE , 2008, 802-810 p.Conference paper, Published paper (Refereed)
Abstract [en]

It is important to ensure that the IT governance is not only designed to achieve internal efficiency in the IT organization, such as deploying good IT processes and making sure that the means and goals are docu-mented. The final goal of good IT governance is rather to provide the business with the support needed in order to conduct business in a good manner. This paper describes the IT Organization Modeling and As-sessment Tool (ITOMAT) and how it can be used for IT governance decision making. ITOMAT consists of an enterprise architecture metamodel that describes IT organizations. ITOMAT further contains a Bayesian network for making predictions on how changes to IT organization models will affect the IT governance performance as perceived by business stakeholders. In order to make such predictions accurately, the network learns from data on previous experience. Thorough case studies at 20 different companies have been conducted in order to calibrate the network. Finally, the paper describes a case study where ITOMAT was used to analyze the future impact of two IT organization change scenarios in a medium sized engineer-ing company.

 

Place, publisher, year, edition, pages
New York: IEEE , 2008. 802-810 p.
Keyword [en]
IT governance, IT organization, Enterprise Architecture, modeling, metamodel
National Category
Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-9126DOI: 10.1109/PICMET.2008.4599688ISI: 000261710000087Scopus ID: 2-s2.0-52449117428ISBN: 978-1-890843-17-5 (print)OAI: oai:DiVA.org:kth-9126DiVA: diva2:24303
Conference
Portland International Conference on Management Engineering and Technology Univ Pretoria, Cape Town, SOUTH AFRICA, JUL 27-31, 2008
Note

QC 20100909

Available from: 2008-09-22 Created: 2008-09-22 Last updated: 2014-01-22Bibliographically approved
In thesis
1. Predicting IT Governance Performance: A Method for Model-Based Decision Making
Open this publication in new window or tab >>Predicting IT Governance Performance: A Method for Model-Based Decision Making
2008 (English)Doctoral thesis, comprehensive summary (Other scientific)
Abstract [en]

Contemporary enterprises are largely dependent on Information Technology (IT), which makes decision making on IT matters important. There are numerous issues that confuse IT decision making, including contradictive business needs, financial constraints, lack of communication between business and IT stakeholders and difficulty in understanding the often heterogeneous and integrated IT systems. The discipline of IT governance aims at providing the decision making structures, processes, and relational mechanisms, needed in order for IT to support and perpetuate the business. The adjacent discipline of enterprise architecture provides a broad range of frameworks and tools for model-based management of IT. Enterprise architecture is a commonly and successfully used approach, but the frameworks need to be adapted with respect to the concerns at stake in order to become truly useful.

The IT organization includes all people involved in decision making regarding IT. The quality of the IT organization differs between enterprises and depends on aspects such as: are rights and responsibilities assigned to the appropriate people, are formalized processes implemented, and does proper documentation exist? This internal IT organization efficiency is labeled IT governance maturity. One might argue that internal efficiency metrics of the IT organization are of moderate interest only. What really matters is the external effectiveness of services that the IT organization delivers to the business. This latter effectiveness is labeled IT governance performance. Even though it is reasonable to believe that enterprises with good IT governance maturity also achieve high IT governance performance, the validity of this assumption has never been tested. IT management’s ability to make well-informed decisions regarding internal IT organization matters would increase if it were possible to predict IT governance performance.

The contribution of this thesis is a method for model-based IT governance decision making. The method includes a metamodel, i.e. a modeling language, and a framework for the assessment of IT governance maturity and performance. The method also allows prediction of IT governance performance. 

This thesis is a composite thesis consisting of four papers and an introduction. Paper A presents an overview of the method for model-based IT governance decision making. Paper B presents the mathematical foundation of the prediction apparatus, i.e. a Bayesian network that is based on statistical data. Paper C presents how the method can be used in practice to support IT governance decision making. Finally, Paper D analyzes the correlation of IT governance maturity and performance. The analysis is based on statistical data from case studies in 35 organizations.

Place, publisher, year, edition, pages
Stockholm: KTH, 2008. ix, 28 p.
Series
Trita-EE, ISSN 1653-5146 ; 2008:42
Keyword
IT governance, IT governance maturity, IT governance performance, Enter-prise Architecture, Bayesian networks.
National Category
Computer and Information Science
Identifiers
urn:nbn:se:kth:diva-9129 (URN)
Public defence
2008-10-17, E1, KTH, Lindstedtsvägen 3, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
QC 20100909Available from: 2008-10-03 Created: 2008-09-22 Last updated: 2010-09-09Bibliographically approved

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Johnson, PontusEkstedt, Mathias

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