Title: A probabilistic model for predicting service level adherence of application support projects

Authors: Srijith Sreenivasan; Manimaran Sundaram

Addresses: Anna University of Technology, Sardar Patel Road, Guindy, Chennai 600-025, Tamil Nadu, India ' PSNA College of Engineering and Technology, Kothandaraman Nagar, Dindigul 624-622, Tamil Nadu, India

Abstract: Application support projects are those which maintain the operations of software in production environment. Service level adherence is a key outcome metric which monitors the contractual compliance of these projects with customers. This paper discusses an approach to develop a prediction model using process factors impacting service level adherence. These factors are derived from the processes and sub-processes having a logical relationship with the outcome. A total of 23 factors were considered initially for modelling, of which six were found to be statistically significant. The model, developed using regression and Monte Carlo simulation, is validated in an actual industrial project to ensure its accuracy. The model can be used in application support projects to arrive at timely decisions for suitable mid-course corrections to control service level adherence.

Keywords: application support; software maintenance; service level adherence; SLA; prediction model; regression analysis; Monte Carlo simulation; model validation.

DOI: 10.1504/IJPQM.2018.095648

International Journal of Productivity and Quality Management, 2018 Vol.25 No.3, pp.305 - 330

Received: 20 Feb 2017
Accepted: 09 Oct 2017

Published online: 16 Oct 2018 *

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