Reducing user input requests to improve IT support ticket resolution process

M. Gupta, A. Asadullah, S. Padmanabhuni, A. Serebrenik

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
197 Downloads (Pure)

Abstract

Management and maintenance of IT infrastructure resources such as hardware, software and network is an integral part of software development and maintenance projects. Service management ensures that the tickets submitted by users, i.e. software developers, are serviced within the agreed resolution times. Failure to meet those times induces penalty on the service provider. To prevent a spurious penalty on the service provider, non-working hours such as waiting for user inputs are not included in the measured resolution time, that is, a service level clock pauses its timing. Nevertheless, the user interactions slow down the resolution process, that is, add to user experienced resolution time and degrade user experience. Therefore, this work is motivated by the need to analyze and reduce user input requests in tickets’ life cycle.

To address this problem, we analyze user input requests and investigate their impact on user experienced resolution time. We distinguish between input requests of two types: real, seeking information from the user to process the ticket and tactical, when no information is asked but the user input request is raised merely to pause the service level clock. Next, we propose a system that preempts a user at the time of ticket submission to provide additional information that the analyst, a person responsible for servicing the ticket, is likely to ask, thus reducing real user input requests. Further, we propose a detection system to identify tactical user input requests.

To evaluate the approach, we conducted a case study in a large global IT company. We observed that around 57% of the tickets have user input requests in the life cycle, causing user experienced resolution time to be almost twice as long as the measured service resolution time. The proposed preemptive system preempts the information needs with an average accuracy of 94–99% across five cross validations while traditional approaches such as logistic regression and naive Bayes have accuracy in the range of 50–60%. The detection system identifies around 15% of the total user input requests as tactical. Therefore, the proposed solution can efficiently bring down the number of user input requests and, hence, improve the user-experienced resolution time.
Original languageEnglish
Pages (from-to)1664-1703
JournalEmpirical Software Engineering
Volume23
Issue number3
Early online date6 Nov 2017
DOIs
Publication statusPublished - 2018

Fingerprint

Life cycle
Clocks
Computer software maintenance
Computer networks
Computer hardware
Logistics
Software engineering
Industry

Keywords

  • software process
  • machine learning
  • process mining
  • service level agreement
  • ticket resolution time

Cite this

Gupta, M. ; Asadullah, A. ; Padmanabhuni, S. ; Serebrenik, A. / Reducing user input requests to improve IT support ticket resolution process. In: Empirical Software Engineering. 2018 ; Vol. 23, No. 3. pp. 1664-1703.
@article{3ee1f9ff4abc41bb872f47118abf404c,
title = "Reducing user input requests to improve IT support ticket resolution process",
abstract = "Management and maintenance of IT infrastructure resources such as hardware, software and network is an integral part of software development and maintenance projects. Service management ensures that the tickets submitted by users, i.e. software developers, are serviced within the agreed resolution times. Failure to meet those times induces penalty on the service provider. To prevent a spurious penalty on the service provider, non-working hours such as waiting for user inputs are not included in the measured resolution time, that is, a service level clock pauses its timing. Nevertheless, the user interactions slow down the resolution process, that is, add to user experienced resolution time and degrade user experience. Therefore, this work is motivated by the need to analyze and reduce user input requests in tickets’ life cycle.To address this problem, we analyze user input requests and investigate their impact on user experienced resolution time. We distinguish between input requests of two types: real, seeking information from the user to process the ticket and tactical, when no information is asked but the user input request is raised merely to pause the service level clock. Next, we propose a system that preempts a user at the time of ticket submission to provide additional information that the analyst, a person responsible for servicing the ticket, is likely to ask, thus reducing real user input requests. Further, we propose a detection system to identify tactical user input requests.To evaluate the approach, we conducted a case study in a large global IT company. We observed that around 57{\%} of the tickets have user input requests in the life cycle, causing user experienced resolution time to be almost twice as long as the measured service resolution time. The proposed preemptive system preempts the information needs with an average accuracy of 94–99{\%} across five cross validations while traditional approaches such as logistic regression and naive Bayes have accuracy in the range of 50–60{\%}. The detection system identifies around 15{\%} of the total user input requests as tactical. Therefore, the proposed solution can efficiently bring down the number of user input requests and, hence, improve the user-experienced resolution time.",
keywords = "software process, machine learning, process mining, service level agreement, ticket resolution time",
author = "M. Gupta and A. Asadullah and S. Padmanabhuni and A. Serebrenik",
year = "2018",
doi = "10.1007/s10664-017-9532-2",
language = "English",
volume = "23",
pages = "1664--1703",
journal = "Empirical Software Engineering",
issn = "1382-3256",
publisher = "Springer",
number = "3",

}

Reducing user input requests to improve IT support ticket resolution process. / Gupta, M.; Asadullah, A.; Padmanabhuni, S.; Serebrenik, A.

In: Empirical Software Engineering, Vol. 23, No. 3, 2018, p. 1664-1703.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Reducing user input requests to improve IT support ticket resolution process

AU - Gupta, M.

AU - Asadullah, A.

AU - Padmanabhuni, S.

AU - Serebrenik, A.

PY - 2018

Y1 - 2018

N2 - Management and maintenance of IT infrastructure resources such as hardware, software and network is an integral part of software development and maintenance projects. Service management ensures that the tickets submitted by users, i.e. software developers, are serviced within the agreed resolution times. Failure to meet those times induces penalty on the service provider. To prevent a spurious penalty on the service provider, non-working hours such as waiting for user inputs are not included in the measured resolution time, that is, a service level clock pauses its timing. Nevertheless, the user interactions slow down the resolution process, that is, add to user experienced resolution time and degrade user experience. Therefore, this work is motivated by the need to analyze and reduce user input requests in tickets’ life cycle.To address this problem, we analyze user input requests and investigate their impact on user experienced resolution time. We distinguish between input requests of two types: real, seeking information from the user to process the ticket and tactical, when no information is asked but the user input request is raised merely to pause the service level clock. Next, we propose a system that preempts a user at the time of ticket submission to provide additional information that the analyst, a person responsible for servicing the ticket, is likely to ask, thus reducing real user input requests. Further, we propose a detection system to identify tactical user input requests.To evaluate the approach, we conducted a case study in a large global IT company. We observed that around 57% of the tickets have user input requests in the life cycle, causing user experienced resolution time to be almost twice as long as the measured service resolution time. The proposed preemptive system preempts the information needs with an average accuracy of 94–99% across five cross validations while traditional approaches such as logistic regression and naive Bayes have accuracy in the range of 50–60%. The detection system identifies around 15% of the total user input requests as tactical. Therefore, the proposed solution can efficiently bring down the number of user input requests and, hence, improve the user-experienced resolution time.

AB - Management and maintenance of IT infrastructure resources such as hardware, software and network is an integral part of software development and maintenance projects. Service management ensures that the tickets submitted by users, i.e. software developers, are serviced within the agreed resolution times. Failure to meet those times induces penalty on the service provider. To prevent a spurious penalty on the service provider, non-working hours such as waiting for user inputs are not included in the measured resolution time, that is, a service level clock pauses its timing. Nevertheless, the user interactions slow down the resolution process, that is, add to user experienced resolution time and degrade user experience. Therefore, this work is motivated by the need to analyze and reduce user input requests in tickets’ life cycle.To address this problem, we analyze user input requests and investigate their impact on user experienced resolution time. We distinguish between input requests of two types: real, seeking information from the user to process the ticket and tactical, when no information is asked but the user input request is raised merely to pause the service level clock. Next, we propose a system that preempts a user at the time of ticket submission to provide additional information that the analyst, a person responsible for servicing the ticket, is likely to ask, thus reducing real user input requests. Further, we propose a detection system to identify tactical user input requests.To evaluate the approach, we conducted a case study in a large global IT company. We observed that around 57% of the tickets have user input requests in the life cycle, causing user experienced resolution time to be almost twice as long as the measured service resolution time. The proposed preemptive system preempts the information needs with an average accuracy of 94–99% across five cross validations while traditional approaches such as logistic regression and naive Bayes have accuracy in the range of 50–60%. The detection system identifies around 15% of the total user input requests as tactical. Therefore, the proposed solution can efficiently bring down the number of user input requests and, hence, improve the user-experienced resolution time.

KW - software process

KW - machine learning

KW - process mining

KW - service level agreement

KW - ticket resolution time

U2 - 10.1007/s10664-017-9532-2

DO - 10.1007/s10664-017-9532-2

M3 - Article

VL - 23

SP - 1664

EP - 1703

JO - Empirical Software Engineering

JF - Empirical Software Engineering

SN - 1382-3256

IS - 3

ER -