A Bayesian Network for IT Governance Performance Prediction
2008 (English)In: Proceedings of the 10th International Con-ference on Electronic Commerce, 2008Conference paper (Refereed)
The goal of IT governance is not only to achieve internal efficiency in an IT organization, but also to sup-port IT‟s role as a business enabler. The latter is an ability of an organization here denoted as IT gover-nance performance. IT management cannot control the IT governance performance directly. Instead, their realm of control includes several IT governance maturity indicators such as the existence of different IT activities, documents, metrics and roles. Current IT governance frameworks are suitable for describing IT governance, IT-systems, and business processes, but lack the ability to predict how changes to the IT gover-nance maturity indicators affect the IT governance performance. This paper presents a Bayesian network for IT governance performance prediction. Bayesian networks are widely used for goal modeling and prediction in other research fields. Data from 35 case studies conducted in a variety of organizations has been used to determine the behavior of the network. An assumption on linearity is introduced in order to compensate for the limited amount of data, and the network learns using the proposed Linear Conditional Probability Matrix Generator. The resulting Bayesian network for IT governance performance prediction can be used to support IT governance decision-making.
Place, publisher, year, edition, pages
IT Governance, Bayesian networks
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-9124DOI: 10.1145/1409540.1409542ScopusID: 2-s2.0-65449158454OAI: oai:DiVA.org:kth-9124DiVA: diva2:24302
QC 201009092008-09-222008-09-222010-09-09Bibliographically approved