Document Type

Closed Project

Publication Date

Spring 2018


Ramin Neshati

Course Title

Decision Making

Course Number

ETM 530


Artificial intelligence, Machine learning, Hierarchical decision model, Service industries -- Management, Technology -- Management


The field service industry is a highly competitive market place, where the establishment of a competitive advantage can lead to future product sales, maintenance contract extensions and product line expansions into new markets. On the other hand, a failure with in a service department can lead to devastating results that impact a company far beyond that of the service team alone. As companies continue to utilize operational strategies like 6-Sigma and Lean in order to reduce waste, improve efficiency and minimize defects, an opportunity has arisen from the rapid growth of technology, which could aide service teams in obtaining the objectives of higher productivity and improved efficiency.

The incorporation of Artificial Intelligence (AI) and Machine Learning (ML) software programs developed by established technology leaders could offer these companies a completive advantage in optimizing the process work flows, reducing wasted resources and improve customer relationships through improved transparency and repair accuracy.

For field service teams, the decision about what software technology would best serve the company can be a difficult question to answer. To aid the team in answering this question, a hierarchical decision model (HDM) has been constructed to help alleviate the congestion in this decision and provide a method of pairwise comparison to establish a primary alternative. In this model, six experts with a range of operational experience ranging from 5 years of field service operations, to field service managers who have a combined management and field service experience of more than 30 years. The results of this model showed an almost unanimous selection of an AI software platform developed by General Electric and its Service Max platform. The use of additional subject matter experts and the addition of alternative decision making techniques such as flow analysis might yield a different outcome and should be considered in order to ensure the best possible result are achieved.


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