Critical factors in agile software projects according
to people, process and technology perspective
Karla M. B. Silva
Simone Santos
Informatics Center
Federal University of Pernambuco
Recife, Brazil
kmbs@cin.ufpe.br
Informatics Center
Federal University of Pernambuco
Recife, Brazil
scs@cin.ufpe.br
Abstract—Agile Software Development have become very
important over the years for organizations of the modern world;
however, software development itself is a very complex process.
There are so many factors that affect project success or failure.
This paper is a systematic review on the critical success factors of
agile software development projects. We classified fourteen
critical factors into three categories based on the pillars of
Information Systems: people, process, and technology. In
addition, primary studies were selected to identify the profile of
agile development organizations, projects’ characteristics, and
implications of agile studies in these projects.
Keywords—critical factors; agile
software development; systematic review
software
development;
I. INTRODUCTION
Software development has been the focus of many
researches, managers, and engineers in the last years; however,
software development is not a simple process. Several software
projects are not delivered on time or budget. In addition, some
of them do not give real value to the client. In order to improve
the software development process, 17 specialists created The
Agile Manifesto in 2001. Some of the Manifesto principles are:
effective communication among team members and between
the team and its clients and users; variable scope, in which
changes in requirements during the project are accepted as
intrinsic to software development; rapid delivery of software to
the client; and team self-management, to provide flexibility and
efficiency in the development [01].
In addition, there are some software development methods
that are called “agile”; for instance, Scrum, Extreme
Programming (XP), Lean, Crystal, and Kanban. These are the
methods used in the companies cited in this paper. Although,
according to the Standish Group [10], software development
projects continue to fail even with the existence of
communities of methodology practice such as PMI and Agile
that promote best practices.
Our research aims to identify and provide insights into the
critical success factors that help agile software development
projects to succeed. We decided to explore and categorize the
critical factors in agile software projects according to people,
process and technology perspective. In addition, we started to
investigate the profile of organizations in agile environments,
their projects’ characteristics, and implications of CSFs studies
in software development companies. Our studies included both
in-house and outsourced software development projects.
The broad objective of this study is to answer the following
research question. What to consider when developing software
in agile environments? More specifically, this study focuses on
four specific questions:
RQ-01: What are the critical factors in agile software
development under people, process and technology
perspective?
RQ-02: What kind of organizations work with software
development in agile environments?
RQ-03: What are the implications of critical factors studies
in agile software development field for the organization’s
projects?
RQ-04: What are the main characteristics of the developed
projects, according to number of collaborators by team, project
duration, domain, and platforms used?
Answering these questions, this review will help companies
that work with agile to understand the critical factors in ASD,
and how they can improve the success rate in their projects.
The next section gives an overview of the research method
used in this study, and section 3 describes the results of this
research. After all, section 4 concludes and provides
recommendations for further research in the agile software
development field.
II. RESEARCH METHODS
This research has been carried out by following
Kitchenham [04] procedures for conducting a Systematic
Review (SR), which involves several activities. Kitchenham
summarizes the activities into three major phases: planning,
conducting, and reporting the review. The planning and
conducting stages have several minor phases. On the other
hand, reporting is a single stage phase. Table I shows the
complete review process proposed by Kitchenham. According
to Kitchenham [03], many of these stages involve interaction.
For example, some activities are initiated during the protocol
development stage, and refined when the review proper takes
place.
TABLE I.
Phases
Planning
REVIEW PROCESS
Java to get the search result on the databases. These scripts are
available online in a public repository at GitHub [08]. At the
end of stage 4, we were left with 23 papers.
Stages
Identification of the need for a
review
Development of a review
protocol
Identification of research
Selection of primary studies
Conducting
Study quality assessment
Data extraction & monitoring
Data synthesis
Reporting
N/A
A. Data Sources and Search Strategy
The search strategy included only electronic databases, and
papers that are written in English. The following electronic
databases were searched:
Fig. 1. The selection process of primary studies.
 ACM Digital Library (www.acm.org)
 IEEE Xplore (www.ieee.org/ieeexplore)
 ScienceDirect (www.sciencedirect.com)
 Scopus (www.scopus.com)
The search on these databases was based on the three
keywords identified in this paper: (1) critical factors, (2) agile
software development, and (3) software development. With the
major search terms, we could identify synonyms (Table II) that
will compose the search string.
TABLE II.
Keywords
Critical factors
Agile
software
development
Software
development
KEYWORDS AND SYNONYMS
Synonyms
Critical success factors, CSF,
crucial factors, risky
Agile, ASD, lean, scrum, XP,
kanban, crystal
Software
project,
software
process development
The search string was combined by using the Boolean
“AND” operator to connect the three categories above.
("critical factors" OR "critical success factors" OR CSF
OR "crucial factors" OR risky) AND ("agile software
development" OR agile OR ASD OR lean OR scrum OR
XP OR kanban OR crystal) AND ("software development"
OR "software project" OR "software process")
This search strategy resulted in a total of 1581 results that
included 1387 unduplicated papers. Fig. 1 shows the complete
review process including the number of papers identified at
each stage. To analyze and store the data from all stages, we
used a Google Sheet that is stored at Google Drive [09]. In
addition, in stage 1, our study used Selenium scripts written in
B. Abbreviations and Acronyms
Inclusion and exclusion criteria are used to exclude studies
that are not relevant to answer the research questions [05]. In
general, we included all the studies related to agile software
development which passed the following criteria:
 The studies must be written in English;
 They must be completely and available on the
electronic databases searched in this paper;
 The studies should be about agile software development
practices, critical factors, or companies that use agile.
In addition, we excluded studies which focus or main focus
was in a specific framework, or related to very specific fields in
the software development area; for example, user interface and
architecture studies.
III. RESULTS
A. Overview of Studies
We selected 23 primary studies, and we categorized the
studies into four main groups according to their methodology:
case study, conceptual, research, and review.
Papers were classified as case study if there was an
implementation of a research method involving a detailed
examination of agile development practices, as well as its
related contextual conditions. Conceptual papers are the ones
primarily based on theoretical considerations. In addition,
research papers are the ones that use surveys as input. If the
study tends to summarize, discuss, or criticize, they were
classified as a review. However, some studies fit more than one
category, so we created a new group to contain all these mixed
studies. Fig. 2 shows that most of the primary studies are
researches.
RQ, but it was incomplete, and “3” indicates that the study
completely answered the question.
TABLE IV.
PRIMARY STUDIES BY RESEARCH QUESTIONS
RQ-01
RQ-02
RQ-03
RQ-04
Total
PS-01
3
1
2
2
8/12
PS-02
2
1
2
1
6/12
PS-03
3
1
1
1
6/12
PS-04
3
1
2
3
9/12
PS-05
1
3
1
3
8/12
Fig. 2. Primary studies by category.
PS-06
1
1
1
3
6/12
These categories helped us to understand the primary
studies, and answer the research questions. Equally important,
Table III shows that the number of studies in the agile
development field are not always increasing through the years.
PS-07
2
1
1
1
5/12
PS-08*
1
1
1
1
4/12
PS-09
2
3
1
3
9/12
PS-010
2
1
2
1
6/12
PS-011*
1
1
1
1
4/12
TABLE III.
PRIMARY STUDIES BY YEAR
Year
Number of
Paper
%
PS-012
1
2
1
1
5/12
2005
1
4,35%
PS-013
3
2
1
2
8/12
2008
2
8,70%
PS-014
2
1
1
1
5/12
2009
1
4,35%
PS-015*
1
1
1
1
4/12
2010
2
8,70%
PS-016
2
1
1
1
5/12
2012
4
17,39%
PS-017
1
2
1
2
6/12
2013
4
17,39%
PS-018
2
1
1
2
6/12
2014
6
26,09%
PS-019
3
1
1
2
7/12
2015
3
13,04%
PS-020
2
1
1
1
5/12
PS-021
2
1
3
1
7/12
PS-022
2
1
2
1
6/12
PS-023
2
2
2
2
8/12
Total
44/69
31/69
31/69
37/69
To put it differently, Fig. 3 shows the amount of primary
studies by database and year of publication.
* Indicates that the study did not answer any research
question.
Fig. 3. Primary studies by year of publication and database.
In a moment that we finished stage four from the selection
process, our next step was to extract the data from the selected
studies, and address the research questions. Evidences and
answers were found for the four questions discussed in the
introduction section of this paper. Table IV shows the
correspondence between primary studies and research
questions. The studies were graded according to the following
criteria: “1” indicates that the paper does not answer the
research question, “2” means that the study helps to answer the
B. What are the critical factors in agile software
development under people, process and technology
perspective?
This question has the highest score on Table IV because
most of the selected studies answered or helped us to answer
the research question 1 (RQ-01). While analyzing the primary
studies, we find out that nine papers [PS-01, PS-03, PS-05, PS07, PS-017, PS-018, PS-019, PS-021, and PS-023] use Chow
and Cao study [PS-04]. This reference is a survey study with
109 agile projects, and these studies mention Chow to provide
a list of main success and failure factors in agile software
development.
The critical success factor technique to identify and
measure an organization’s performance was developed by
Rockhart [02], and was refined and became well established
few years later [07]. According to [05], CSFs are issues that if
addressed appropriately, it can increase the chances of project
success. However, there are many interpretations for definition
of success in software development. In this study, we will
indicate that success is associated with time, scope, cost, and
quality variables [PS-01, PS-03, PS-04, PS-013, PS-022, PS023]. The failures and success factors from [PS-04] listed in
[PS-07 and PS-023] contain a total of 55 items grouped into 4
and 5 categories. Different from [PS-04], we decided to
regroup these factors into three main categories: people,
process, and technology. From the people perspective, we will
consider team members of the development team, customers,
end users, or any other human resources. By the same token,
process is related to the operation of ASD, and technology is
related to all technical and tech procedures.
Table V shows the most common critical success factors
found in [PS-01, PS-03, PS-04, PS-07, PS-010, PS-013, PS016, PS-018, PS-019, PS-020, PS-021, PS-022, and PS-023] in
agile environments. It is important to realize that the primary
studies not cited above did not have an explicit list of success
or failures factors.
TABLE V.
CRITICAL FACTORS BY PEOPLE, PROCESS, AND TECHNOLOGY
PERSPECTIVE
People
Competence
and expertise
Executive
support
Team and user
motivation
Team size
User
participation
Process
Agile practices
Delivery
most
important features
first
Right amount of
documentation
Strong
communication
Technology
Appropriate technical
training
As show above, some factors are cited more frequently in
studies; for example, team and user motivation. Chow and Cao
[PS-04] found that “team members with great motivation
positively influenced the perceived success of the agile
software development projects”. Although, [PS-013] disagrees
with some of the Table V factors. The author explains that the
methodology of asking a few people for their opinion without a
mediated focus group methodology has its limitations. The
study defends that team size, technical competency, and
communication are not significantly related with success.
C. What kind of organizations work with software
development in agile environments?
Only 6 studies provide contents to answer the question 2
(RQ-02) because it is a very specific question. In our research,
we have a broad range of companies. This range includes startups [PS-017], small and large outsourced software
development companies, and companies that their business are
not software development [PS-05]. Two papers [PS-08, PS011] are not specific about success and failures factors in agile,
so their cases will not be counted in this question. In addition,
[PS-017] includes some educational and governmental
organizations.
Primary study [PS-017] conducted a survey with 200
companies to identify the agile practices in these companies. In
this survey, the author identified that most of the companies are
medium size (less than 100 employees). Fig. 5 shows [PS-017]
research results.
Integration testing
Simple design
Tool supports
Well defined coding
standards
Based on our analyses, we identified 14 factors as the most
frequently cited across 13 studies. To put it differently, Fig. 4
shows the number of occurrences of each factor from Table V.
Fig. 5. Survey results from [PS-17]
Similarly, [PS-05] presents 3 cases, and the company of
case 1 has over 500 IT employees. As can be seen in Table VI,
the second case from [PS-05] presents a well-established
company with more than 10 years delivering e-commerce and
infrastructure services. Table VI shows the summary of the
cases from the [PS-05] study.
TABLE VI.
SUMMARY OF THE CASES FROM [PS-05]
Company 1
Financial
corporation
Number of
employers
over 500 IT
employees
Company 2
Software company
120 developers
Company 3
Internet content and
access provision
200 developers
Domain
Fig. 4. Factors from Table V by total citation count.
In contrast, study [PS-09] argues that “we have to be aware
of large companies with well-defined structures and
processes”. The author explains that the transition process to
agile might not be easy. The article suggests to try to use agile
practices in small projects in these bureaucratic companies.
Must be remembered that all of these companies use agile
methodologies and frameworks; for example, Crystal, XP,
Scrum, and Kanban. Most of these companies’ sprints are
around four weeks where each interaction is a complete
development life cycle. For agile practitioners, the most
important points are a collaborative environment and
organizational culture adaptive to changes. According to them,
the agile approach requires self-organizing teams that have the
power to coordinate their work without direct supervision. Fig.
6 shows the summary of the companies’ profile.
Fig. 6. Number of primary study by companies’ size.
D. What are the implications of critical factors studies in
Agile Software Development field for the organization’s
projects?
Study [PS-04] argues that failures and success factors “can
contribute to the understanding of how to avoid certain serious
pitfalls that are critical to the success of a project”. In Table V,
we classified 14 factors into people, process, and technology
categories. According to [PS-023], these factors can help
managers to prioritize tasks better and improve resource
allocation.
In the final analysis, the general implications of these
factors are related to project success or failure. Although, it can
be more slowly or not directly associated; for example, internal
conflicts and duplicated work. A team with internal
communication issues will have problems to share information
among team members, so each member will need to find their
our solution. As a result, collaborators will spend a lot of time
and money with this approach.
E. What are the main characteristics of the developed
projects, according to number of collaborators by team,
project duration, domain, and platforms used??
Primary study [PS-09] discusses the myth that “agility
helps in any case”. The author explains the variety of
applications, domains, and risks are different to each project;
however, for [PS-09], the main reasons to use agile practices
are to achieve shorter development cycles, be able to cope with
changing requirements in a cost-effective manner, and have a
close cooperation with the customer.
The first minor question was about the number of
collaborators by team. According to [PS-013], “the number of
members in a team greatly influences the degree of
communication that can be had between team members. For
instance, in a team that has a large number of members, it is
quite likely that frequent, informal, and rapid interactions will
become difficult. The pace of informal communications can be
made faster in small teams”. Our research contains small and
large teams. In addition, these teams could be located in
different countries, and working on the same projects [PS-06
and PS-023]. Primary studies [PS-04, PS-013, and PS-017]
focus on the small teams, but they do have bigger teams where
the number of team members are equal or greater than 20. Only
studies [PS-05 and PS-016] contain just small teams. Fig. 7
shows the number of primary for each size of companies.
Communication is present in our fourteen factors list.
Based on our research, we defend that companies need to
understand that communication is very critical for any project.
In [PS-01], the author says that internal project communication
between projects’ members can decrease the amount of team
conflict and keeps the team stable. It is important to point out
that instability can result in a project being delayed and
exceeding budget. Software development activities require
collaboration between team members, and these interactions
can improve the knowledge management in the project.
Fig. 7. Number of primary study by companies’ size.
Similarly, study [PS-03] argues that people is a very
important key in the software development process.
Competence, expertise, and user participation are CSFs listed
in the people category. In [PS-01], the author explains the
relation between these two factors and inconsistent
requirements. According to them, these factors are relevant to
develop a software product that meets the client’s expectations.
In addition, it will decrease process performance.
Similarly, for project duration, we have short and long
projects. In [PS-016], we found really small projects; for
example, 2 or 3 months duration. [PS-05] contains projects
which duration was about 2 years. In contrast, [PS-08], which
does not comment about agile projects, contains projects that
took more than four years to be completed; however, all of
them encourage user participation in the development process
to obtain rapid feedback.
Our primary studies do not comment a lot about the domain
or platforms used. In [PS-05], we found more details about the
projects; for example, it says that the project 1 was a redevelopment of an existing system for the financial market,
project 2 was a new e-commerce service, and project 3 was the
maintenance of a recommendation system for products from
several virtual stores. By the same token, [PS-016] comments
about three cases. The first one is a finance critical software for
public use. The second case contains two kinds of projects: a
video codec product for mobile applications, and customer
tailoring for the video codec product. The last case was a
mobile version of the internet security system, and a
monitoring system for the internet security system.
Because we have a broad range of projects in terms of
number of team members, project duration, domain, and
complexity, we could not create a single profile of these
projects. Our studies included both in-house and outsourced
software development projects. In addition, the companies use
several agile methodologies and frameworks; for instance,
Crystal, XP, Scrum, and Kanban.
CONCLUSION
This systematic review identified 1387 unduplicated papers
from the search on four electronic databases. We selected 23 to
conduct this research, but only 20 contribute to answer our
research questions. This study has been carried out in three
main steps as follows: an extensive literature review to identify
CSFs and factors related to agile software development,
analysis of identified CSFs and the agile environment,
development of a CSFs list based on people, process, and
technology and explanation about organization's profile,
projects’ characteristics and implications of CSFs.
The list of critical success factors contains the most
commons factors found in our primary studies. For people
perspective, they are: competence and expertise, executive
support, team and user motivation, team size, and user
participation. Similarly, we have 4 factors for process list: agile
practices, delivery most important features first, and right
amount of documentation. The technology category is
composed by: appropriate technical training, integration
testing, simple design, tools supports, and well-defined coding
standards. General implications of these factors are related to
project success or failure.
Our primary studies had a mix of companies and projects.
Most of them were small companies with less than 10
employees, but they do have large cases. Our studies included
both in-house and outsourced software development projects.
As a result, we had companies from different markets.
Although, according to the articles, the most important
characteristics are collaborative environment and adaptive
culture. We could not provide more evidences for the RQ-02
RQ-04 because the number of case studies was too small.
This review has identified several attractive research
challenges that need to be addressed in future researches. A
clear finding of the review is that we need to increase the
number of case studies in agile software development. In
particular, to understand how companies of the modern world
are using agile methodologies.
Talk about future work in others databases
APPENDIX A. PRIMARY STUDIES INCLUDED IN THIS REVIEW
[PS-01] Ahimbisibwe, A., Cavana, R., & Daellenbach, U. (2015). A
contingency fit model of critical success factors for software
development projects. Journal Of Ent Info Management, 28(1), 7-33.
doi:10.1108/jeim-08-2013-0060
[PS-02] Bano, M., & Zowghi, D. (2015). A systematic review on the
relationship between user involvement and system success. Information
And
Software
Technology,
58,
148-169.
doi:10.1016/j.infsof.2014.06.011
[PS-03] Bermejo, P., Zambalde, A., Tonelli, A., Souza, S., Zuppo, L., &
Rosa, P. (2014). Agile Principles and Achievement of Success in
Software Development: A Quantitative Study in Brazilian
Organizations.
Procedia
Technology,
16,
718-727.
doi:10.1016/j.protcy.2014.10.021
[PS-04] Chow, T., & Cao, D. (2008). A survey study of critical success
factors in agile software projects.Journal Of Systems And Software,
81(6), 961-971. doi:10.1016/j.jss.2007.08.020
[PS-05] de O. Melo, C., S. Cruzes, D., Kon, F., & Conradi, R. (2013).
Interpretative case studies on agile team productivity and management.
Information
And
Software
Technology,
55(2),
412-427.
doi:10.1016/j.infsof.2012.09.004
[PS-06] Drury-Grogan, M. (2014). Performance on agile teams: Relating
iteration objectives and critical decisions to project management success
factors. Information And Software Technology, 56(5), 506-515.
doi:10.1016/j.infsof.2013.11.003
[PS-07] França, A., da Silva, F., & de Sousa Mariz, L. (2010). An
empirical study on the relationship between the use of agile practices
and the success of Scrum projects. Proceedings Of The 2010 ACMIEEE International Symposium On Empirical Software Engineering And
Measurement - ESEM '10. doi:10.1145/1852786.1852835
[PS-08] Ghobadi, S., & D’Ambra, J. (2012). Coopetitive relationships in
cross-functional software development teams: How to model and
measure?. Journal Of Systems And Software, 85(5), 1096-1104.
doi:10.1016/j.jss.2011.12.027
[PS-09] Hochmüller, E., & Mittermeir, R. (2008). Agile process myths.
Proceedings Of The 2008 International Workshop On Scrutinizing Agile
Practices Or Shoot-Out At The Agile Corral - APOS '08.
doi:10.1145/1370143.1370145
[PS-10] Jorgensen, M. (2014). Failure factors of small software projects at
a global outsourcing marketplace.Journal Of Systems And Software, 92,
157-169. doi:10.1016/j.jss.2014.01.034
[PS-11] Lehtinen, T., Mäntylä, M., Vanhanen, J., Itkonen, J., & Lassenius,
C. (2014). Perceived causes of software project failures – An analysis of
their relationships. Information And Software Technology, 56(6), 623643. doi:10.1016/j.infsof.2014.01.015
[PS-12] Madsen, K. (2005). Agility vs. stability at a successful start-up.
Companion To The 20Th Annual ACM SIGPLAN Conference On
Object-Oriented Programming, Systems, Languages, And Applications OOPSLA '05. doi:10.1145/1094855.1094966
[PS-13] Misra, S., Kumar, V., & Kumar, U. (2009). Identifying some
important success factors in adopting agile software development
practices. Journal Of Systems And Software, 82(11), 1869-1890.
doi:10.1016/j.jss.2009.05.052
[PS-14] Moe, N., Dingsøyr, T., & Dybå, T. (2010). A teamwork model for
understanding an agile team: A case study of a Scrum project.
Information
And
Software
Technology,
52(5),
480-491.
doi:10.1016/j.infsof.2009.11.004
[PS-15] Petersen, K., Khurum, M., & Angelis, L. (2014). Reasons for
bottlenecks in very large-scale system of systems development.
Information And Software Technology, 56(10), 1403-1420.
doi:10.1016/j.infsof.2014.05.004
[PS-16] Pikkarainen, M., Salo, O., Kuusela, R., & Abrahamsson, P. (2011).
Strengths and barriers behind the successful agile deployment—insights
from the three software intensive companies in Finland.Empirical
Software Engineering, 17(6), 675-702. doi:10.1007/s10664-011-9185-5
[PS-17] Rodríguez, P., Markkula, J., Oivo, M., & Turula, K. (2012).
Survey on agile and lean usage in finnish software industry. Proceedings
Of The ACM-IEEE International Symposium On Empirical Software
Engineering
And
Measurement
ESEM
'12.
doi:10.1145/2372251.2372275
[PS-18] Senapathi, M., & Srinivasan, A. (2012). Understanding postadoptive agile usage: An exploratory cross-case analysis. Journal Of
Systems And Software, 85(6), 1255-1268. doi:10.1016/j.jss.2012.02.025
[PS-19] Senapathi, M., & Srinivasan, A. (2013). Sustained agile usage.
Proceedings Of The 17Th International Conference On Evaluation And
Assessment
In
Software
Engineering
EASE
'13.
doi:10.1145/2460999.2461016
[PS-20] Shahane, D., Jamsandekar, P., & Shahane, D. (2014). Factors
influencing the agile methods in practice - Literature survey &
review. 2014 International Conference On Computing For Sustainable
Global Development (Indiacom). doi:10.1109/indiacom.2014.6828020
[PS-21] Sheffield, J., & Lemétayer, J. (2013). Factors associated with the
software development agility of successful projects. International
Journal
Of
Project
Management,
31(3),
459-472.
doi:10.1016/j.ijproman.2012.09.011
[PS-22] Shrivastava, S., & Rathod, U. (2015). Categorization of risk factors
for distributed agile projects.Information And Software Technology, 58,
373-387. doi:10.1016/j.infsof.2014.07.007
[PS-23] Stankovic, D., Nikolic, V., Djordjevic, M., & Cao, D. (2013). A
survey study of critical success factors in agile software projects in
former Yugoslavia IT companies. Journal Of Systems And
Software,86(6), 1663-1678. doi:10.1016/j.jss.2013.02.027
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