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.
Stored only when both papers are in the corpus — 21 citations exist upstream.
Imported from OpenAlex (CC0) — nothing here is generated.