A telecommunications services provider wants to allocate its service engineers to various customer locations in a manner that minimizes engineers’ travel requirements while still ensuring customer satisfaction under its service level agreements (SLAs). Segmentation techniques are deployed for the various exchanges across which the company operates. Optimization techniques are put in place to develop a robust work allocation framework that meets demand-side requirements amidst supply-side constraints in a fashion that minimizes engineers’ travel requirements. The optimization model is evaluated across various scenarios that model peaks & troughs in service demand as well as engineers’ availability.
A telecommunications services provider wants to optimize the work allocation framework for its field workforce (i.e., service engineers). The company’s engineers cater to customer service requests across the various exchanges in a given region. To meet the service demand at different customer locations, the engineers need to travel to the customer sites. While the company maintains a fairly versatile workforce with a wide variety of skillsets, certain service requests mandate deployment of engineers with specific skills and experience levels.
A critical success factor for telecommunications services providers is effective & efficient deployment of its field workforce so as to ensure that customer requirements are met within the timelines specified under pre-defined service level agreements (SLAs). Moreover, since the engineers need to travel to the various customer locations, it is imperative to manage the work assignments for the workforce in a fashion that minimizes travel requirements (and hence travel times & costs) as well as harmonizes utilization of the workforce.
Geographical segmentation is carried out for the exchanges across which the telecommunications services provider operates. This enables the company to view its circle of operations as a set of work-zones for its field workforce.
Optimization techniques are deployed to minimize the engineers’ travel requirements. The model accommodates demand-side constraints, like meeting service demands at the exchanges, skillsets required, terms of service level agreements (SLAs), etc. The model also incorporates supply-side constraints, such as availability of engineers, skillsets, single-sited engineer information, etc. Linear programming, assignment problem modelling, and binary programming techniques are used to arrive at an optimal work allocation schedule for the company’s engineers that minimizes travel costs and meets customer service demands.
Since customer service demands as well as engineers’ availability are likely to vary from day-to-day, the model is evaluated across a host of scenarios that envisage peaks & troughs in demand as well as engineers’ supply.
The telecommunications services provider is able to put in place an effective & efficient work allocation framework that enables the company to optimize the deployment of its field workforce across the various customer locations in a manner that minimizes engineers’ travel costs and also meets service level agreements (SLAs) with regards to customer satisfaction. The company is also able to vary its work assignment in a dynamic fashion, in response to variations in service demand and engineers’ availability.