How to enable multiple skill learning in a SLA constrained service system?

Abstract

In a knowledge based service system like IT services, the requirements of skills to service customer requests keep changing with time. The service workers are expected to learn the required skills very quickly and become productive. Due to high attrition rate and demand, service workers are given basic class room training and then rest of the training is carried out on-job. When a service worker learns multiple skills simultaneously, learning slows down due to factors like forgetting and interference. At the same time, the organization needs to meet service level agreements (SLA). We have developed a model for on-job training which extends the business process for IT service delivery. The key idea is to model learning, forgetting and interference in service time estimation to get realistic service times. Accurate estimation of service time taken by a service worker to resolve the service tickets helps in resource allocation and planning decisions for achieving the desired objectives of upskilling and SLA success. The simulation of execution of the augmented business process provides insights into what kind of planning and dispatch policies should be practiced for achieving the desired goals of multi-skill learning and SLA success.