Abstract
In our increasingly interconnected world, information systems play a pivotal role in various aspects of daily life. From banking and communication to food production and logistics, these systems underpin critical services. In 2024, organisations will invest over 5 Trillion dollar to improve existing information systems and create new ones. However, not all ventures succeed; even giants like Canon have faced financial challenges due to misaligned investments. Mark van der Pas investigates decision-making in IT management. He shows that over 85% of the IT investment requests are approved by management boards. He also created machine learning models that outperform managers in predicting IT project cancellations. This means a computer can better predict a project cancellation than managers.
IT investments are regularly supported by business cases. The business cases used in IT investments are so inaccurate that they are addressed by practitioners as ‘filled with lies’. These business cases can be improved over reference class forecasting. For this to work reference classes need to be defined. Mark van der Pas successfully defined reference classes that can be used to better predict the financial effects of portfolios of IT investments. Furthermore, the dissertation delves into the behaviour of IT controllers within Information Technology Management and it presents instruments how to influence their behaviour.
IT investments are regularly supported by business cases. The business cases used in IT investments are so inaccurate that they are addressed by practitioners as ‘filled with lies’. These business cases can be improved over reference class forecasting. For this to work reference classes need to be defined. Mark van der Pas successfully defined reference classes that can be used to better predict the financial effects of portfolios of IT investments. Furthermore, the dissertation delves into the behaviour of IT controllers within Information Technology Management and it presents instruments how to influence their behaviour.
Original language | English |
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Qualification | Doctor of Philosophy |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 26 Jun 2024 |
Place of Publication | Maastricht |
Publisher | |
Print ISBNs | 9789464699852 |
DOIs | |
Publication status | Published - 2024 |
Keywords
- IT Management
- Machine Learning
- Change Management
- Business Cases