Enhancing the customer service experience in call centers using preemptive solutions and queuing theory

Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.

Bibliographic Details
Main Authors: Chu, Qiao, M. Eng. Massachusetts Institute of Technology, Palvia, Nisha
Other Authors: James B. Rice, Jr.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2017
Subjects:
Online Access:http://hdl.handle.net/1721.1/112874
_version_ 1811084113307762688
author Chu, Qiao, M. Eng. Massachusetts Institute of Technology
Palvia, Nisha
author2 James B. Rice, Jr.
author_facet James B. Rice, Jr.
Chu, Qiao, M. Eng. Massachusetts Institute of Technology
Palvia, Nisha
author_sort Chu, Qiao, M. Eng. Massachusetts Institute of Technology
collection MIT
description Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.
first_indexed 2024-09-23T12:45:02Z
format Thesis
id mit-1721.1/112874
institution Massachusetts Institute of Technology
language eng
last_indexed 2024-09-23T12:45:02Z
publishDate 2017
publisher Massachusetts Institute of Technology
record_format dspace
spelling mit-1721.1/1128742019-04-12T21:51:33Z Enhancing the customer service experience in call centers using preemptive solutions and queuing theory Chu, Qiao, M. Eng. Massachusetts Institute of Technology Palvia, Nisha James B. Rice, Jr. Massachusetts Institute of Technology. Supply Chain Management Program. Massachusetts Institute of Technology. Supply Chain Management Program. Supply Chain Management Program. Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (page 79). The security alarms services market in the United States delivers hardware equipment and services to homeowners and businesses to help monitor and enhance personal property protection. Customer satisfaction via wait time reduction, first call resolution, and cost minimization are key drivers of success to players in this market. Most companies invest heavily in customer service systems including call centers. Our client, AlarmCo, a top provider of property protection, manages an inbound call center that supports a range of questions from customers who call within thirty days from the alarm installation date. Often, security companies fail to utilize strategic solutions when managing inbound customer call traffic and default to reactive measures which unnecessarily increase customer wait times. The key question the team aims to address in this thesis is: "How can we improve the customer service experience for customers of a major security service provider in the United States?" For this thesis, MIT partnered with OnProcess Technology, a managed services provider specializing in complex, global service supply chain operations, to develop a robust framework to preemptively reduce the number of inbound customer calls, and thereby improve customer service. Using ABC segmentation, the team categorized customers by reason code and demographics. To simulate the client's call center queue, the team calculated the key inputs for the queuing model including average wait time, interarrival rates and number of servers. The team then chose and developed the M/M/n stochastic queuing model for the simulation. The M/M/n queue reflects a simple system with parallel servers, arrivals with a Poisson distribution and service times that are exponentially distributed. Next, the customer segmentation was used to develop targeted preemptive solutions. Taking into account feasibility ratings, the team assigned success rates to each solution and adjusted the inbound call data accordingly. By analyzing the outputs of the simulation before and after adjusting the dataset, the team quantified the impact of preemptive solutions on the call center queue. Ultimately, narrowing to twelve strategic preemptive solutions led to the enhancement of the as-is queuing model by reducing average wait time by up to 35%. by Qiao Chu and Nisha Palvia. M. Eng. in Supply Chain Management 2017-12-20T18:15:39Z 2017-12-20T18:15:39Z 2017 2017 Thesis http://hdl.handle.net/1721.1/112874 1014340358 eng MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582 79 pages application/pdf Massachusetts Institute of Technology
spellingShingle Supply Chain Management Program.
Chu, Qiao, M. Eng. Massachusetts Institute of Technology
Palvia, Nisha
Enhancing the customer service experience in call centers using preemptive solutions and queuing theory
title Enhancing the customer service experience in call centers using preemptive solutions and queuing theory
title_full Enhancing the customer service experience in call centers using preemptive solutions and queuing theory
title_fullStr Enhancing the customer service experience in call centers using preemptive solutions and queuing theory
title_full_unstemmed Enhancing the customer service experience in call centers using preemptive solutions and queuing theory
title_short Enhancing the customer service experience in call centers using preemptive solutions and queuing theory
title_sort enhancing the customer service experience in call centers using preemptive solutions and queuing theory
topic Supply Chain Management Program.
url http://hdl.handle.net/1721.1/112874
work_keys_str_mv AT chuqiaomengmassachusettsinstituteoftechnology enhancingthecustomerserviceexperienceincallcentersusingpreemptivesolutionsandqueuingtheory
AT palvianisha enhancingthecustomerserviceexperienceincallcentersusingpreemptivesolutionsandqueuingtheory