Tooling as a Service

Agent Based Scenario Development for IT Services Delivery

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Abstract

Information Technology [IT] is increasingly being integrated into the modern society. Novel IT solutions are Cloud based. Cloud solutions from Microsoft Azure and Amazon AWS are examples of services which offer the benefits of cloud computing. For IT providers, leveraging novel IT artefacts may require the development of a new service model. IT services enable new service delivery models and have the ability to disrupt whole industries. Spotify, Airbnb, and Uber are examples of successful businesses using IT driven service models. The academic community researches aspects of IT governance, frameworks, architecture, and business model innovation, management and organisational theories in order to develop a more successful IT service delivery model. The heterogeneous body of these academic theories addresses different parts of the service model development. However, current IT service delivery models lack sufficient support for contextualisation. In a case study at Dutch IT services provider KPN, Agent Based modelling is used to develop future scenario’s for the IT services organisation. With a strong focus on the organisation and the agents in the organisation, the Agent Based modelling approach OperA is applied. By Using semi-structured interviews to collect data throughout the services delivery chain, a future scenario with the IT broker as a new role was developed. Consequently, roles facilitating legacy platforms are expected to discontinue. From the future scenario, a roll-out plan using three phases is developed using the social structure of the organisation model. The environments of the OperA model enable the research to focus on the social structure of IT services delivery and the analysis of interactions between roles. The OperA model is a sufficient model for strategic decision making in IT services delivery. Further work could generate tools to fully automated the validation of the OperA model and connect it to real life phenomena with real time adaption to changes.