| Field service management continues to be a major challenge for many service organizations as companies are required to provide better service with less cost. This problem was not perceived as being significant in the past and there has not been very much academic research done in this area, as yet. In recent years, as competition grows in the field service area, service providers realize that the customer satisfaction and client loyalty are the fundamental factors to their continued revenue growth. Delivering the levels of support that the customers have grown accustomed to is not enough to maintain market share and win the business from competitors. More efficient and sophisticated system design and management procedures are shown to be the best way to raise the service bar and stimulate business.; In the field service application, although quantile related performance measures have been proposed as a quality measure for a long time, research taking them as a main performance measure in system design has been scant. However, this investigator worked with a leading service provider in the computer industry which has been pioneering field service concepts for decades. The management has decided to have their field service system explicitly driven by quantile based performance measures. Practically, there is a need for experimental results and systems analysis to gain insights into the potential system behaviors. It also has been an open theoretical research problem which shows a lot of challenging characteristics. In this research, we consider such a quantile based performance measure and study a series of corresponding fundamental management concerns in developing the system design such as manpower planning, service territory design, dispatching rules, etc. A field service system planning framework, different decision models, and a simulation system are developed to aid in understanding the implications of the field service design and facilitate the field service manager to evaluate different support strategies. Extensive numerical experiments are conducted and the functional relationship between the server utilization, customer arrival rate, service rate; and the percentage of customers attended to within the contracted time are illustrated by using a simulation metamodel. |
