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Development and evaluation of a lightweight root cause analysis method (ARCA method) - field studies at four software companies

Lehtinen, Timo; Mäntylä, Mika LU and Vanhanen, Jari (2011) In Information and Software Technology 53(10). p.1045-1061
Abstract (Swedish)
Abstract in Undetermined

Context



The key for effective problem prevention is detecting the causes of a problem that has occurred. Root cause analysis (RCA) is a structured investigation of the problem to identify which underlying causes need to be fixed. The RCA method consists of three steps: target problem detection, root cause detection, and corrective action innovation. Its results can help with process improvement.

Objective



This paper presents a lightweight RCA method, named the ARCA method, and its empirical evaluation. In the ARCA method, the target problem detection is based on a focus group meeting. This is in contrast to prior RCA methods, where the target problem... (More)
Abstract in Undetermined

Context



The key for effective problem prevention is detecting the causes of a problem that has occurred. Root cause analysis (RCA) is a structured investigation of the problem to identify which underlying causes need to be fixed. The RCA method consists of three steps: target problem detection, root cause detection, and corrective action innovation. Its results can help with process improvement.

Objective



This paper presents a lightweight RCA method, named the ARCA method, and its empirical evaluation. In the ARCA method, the target problem detection is based on a focus group meeting. This is in contrast to prior RCA methods, where the target problem detection is based on problem sampling, requiring heavy startup investments.

Method



The ARCA method was created with the framework of design science. We evaluated it through field studies at four medium-sized software companies using interviews and query forms to collect feedback from the case attendees. A total of five key representatives of the companies were interviewed, and 30 case participants answered the query forms. The output of the ARCA method was also evaluated by the case attendees, i.e., a total 757 target problem causes and 124 related corrective actions.

Results



The case attendees considered the ARCA method useful and easy to use, which indicates that it is beneficial for process improvement and problem prevention. In each case, 24–77 target problem root causes were processed and 13–40 corrective actions were developed. The effort of applying the method was 89 man-hours, on average.

Conclusion



The ARCA method required an acceptable level of effort and resulted in numerous high-quality corrective actions. In contrast to the current company practices, the method is an efficient method to detect new process improvement opportunities and develop new process improvement ideas. Additionally, it is easy to use. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Root cause analysis, Problem prevention, Software process improvement, Industrial field study, Design science research, Cause-effect diagram
in
Information and Software Technology
volume
53
issue
10
pages
1045 - 1061
publisher
Elsevier
external identifiers
  • scopus:79959956911
ISSN
0950-5849
DOI
10.1016/j.infsof.2011.05.005
language
English
LU publication?
no
id
8a33e3aa-a0b4-4a93-9aa1-84e3679b4ce1 (old id 2225587)
date added to LUP
2011-12-15 14:42:52
date last changed
2017-01-01 07:52:09
@article{8a33e3aa-a0b4-4a93-9aa1-84e3679b4ce1,
  abstract     = {<b>Abstract in Undetermined</b><br/><br>
Context<br/><br>
<br/><br>
The key for effective problem prevention is detecting the causes of a problem that has occurred. Root cause analysis (RCA) is a structured investigation of the problem to identify which underlying causes need to be fixed. The RCA method consists of three steps: target problem detection, root cause detection, and corrective action innovation. Its results can help with process improvement.<br/><br>
Objective<br/><br>
<br/><br>
This paper presents a lightweight RCA method, named the ARCA method, and its empirical evaluation. In the ARCA method, the target problem detection is based on a focus group meeting. This is in contrast to prior RCA methods, where the target problem detection is based on problem sampling, requiring heavy startup investments.<br/><br>
Method<br/><br>
<br/><br>
The ARCA method was created with the framework of design science. We evaluated it through field studies at four medium-sized software companies using interviews and query forms to collect feedback from the case attendees. A total of five key representatives of the companies were interviewed, and 30 case participants answered the query forms. The output of the ARCA method was also evaluated by the case attendees, i.e., a total 757 target problem causes and 124 related corrective actions.<br/><br>
Results<br/><br>
<br/><br>
The case attendees considered the ARCA method useful and easy to use, which indicates that it is beneficial for process improvement and problem prevention. In each case, 24–77 target problem root causes were processed and 13–40 corrective actions were developed. The effort of applying the method was 89 man-hours, on average.<br/><br>
Conclusion<br/><br>
<br/><br>
The ARCA method required an acceptable level of effort and resulted in numerous high-quality corrective actions. In contrast to the current company practices, the method is an efficient method to detect new process improvement opportunities and develop new process improvement ideas. Additionally, it is easy to use.},
  author       = {Lehtinen, Timo and Mäntylä, Mika and Vanhanen, Jari},
  issn         = {0950-5849},
  keyword      = {Root cause analysis,Problem prevention,Software process improvement,Industrial field study,Design science research,Cause-effect diagram},
  language     = {eng},
  number       = {10},
  pages        = {1045--1061},
  publisher    = {Elsevier},
  series       = {Information and Software Technology},
  title        = {Development and evaluation of a lightweight root cause analysis method (ARCA method) - field studies at four software companies},
  url          = {http://dx.doi.org/10.1016/j.infsof.2011.05.005},
  volume       = {53},
  year         = {2011},
}