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International Conference on Internet Studies,
July 22-24, 2016, Osaka, Japan
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IMPACT OF PROJECT MANAGEMENT TOOLS ON
PROJECT ESTIMATES AND BENEFITS
Makoto Nakayama,
DePaul University, U.S.A.
mnakayama@cdm.depaul.edu
Charlie C. Chen,
Appalachian State University, U.S.A.
chench@appstate.edu
ABSTRACT
We have seen a variety of project management (PM) tools available for project
managers in recent years. Yet, projects continue to face significant challenges. The
use of PM tools is considered a means to counter these challenges. However, the
effectiveness of PM tools has not been demonstrated empirically. The results of this
study show that the use of PM tools positively impacts overall project benefits. At the
same time, only four PM tools were critical for project success. PM tool use was also
found not to improve the accuracy of initial project estimates. Instead, project risk
assessment improves the accuracy of project estimates, which in turn relates to overall
project benefits. The implications of these results are discussed.
Keywords: project estimate, project management tool, project risk assessment,
project success
1. INTRODUCTION
Despite the increasing availability and variety of project management (PM) tools in
recent years, projects continue to face challenges. According to the 2016 Pulse of the
Profession [1], 47% of projects exceed the budget, 51% do not complete on time, and
55% experience scope creep. PM tools are used to design and control project plans,
deliverables, resources, budgets, staff assignments, roles and responsibilities,
communications, and quality management [2]. They have been commonly adopted
not only to minimize project risks but also to counter unique challenges of each
project. The 2012 global survey by PricewaterhouseCoopers [3] notes 77% of
respondents use PM methodologies and software. According to [4], software tools that
comply with the Capability Maturity Model Integration (CMMI) or the Project
Management Body of Knowledge (PMBOK) can effectively manage project
management processes and achieve project success. However, the same study
cautions that a large number of PM tools are still not aligned with state-of-the-art PM
practice. Although [5] has emphasized the importance of using right tools and
methods, it is not clear how much their use can contribute to containing project risks
and helping project success. Therefore, the main research goal of this study is to
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assess empirically the extent to which PM tool use helps achieve more accurate
project estimates and better overall project outcomes.
2. THEORETICAL BACKGROUND AND HYPOTHSES
2.1 The Impact of PM Tool Use
Raz and Michael [6] find a positive relationship between project tool use and project
management performance (PMP) score. While there are a variety of PM tools, they
should be selected and applied in the right stage of a project cycle. In the initial stage,
project managers can utilize user stories [7]. As project ideas become more mature,
semi-structured qualitative interviews help project managers gain fine details of
requirements [8]. It is imperative for project managers to know what tools to use
under what project circumstances to estimate projects accurately as well as to achieve
project success. Indeed, Fortune and White [9] note the correct choice or past
experience of PM tools as one of the critical success factors (CSFs) for projects.
Zwikael, Shimizu, and Globerson [10] compare the extent of PM tool use in Israel and
Japan. Project managers in Israel use PM tools more than their Japanese counterparts.
They observe that PM tools enable project managers in Israel to focus more on
executing planning processes and to enjoy the higher intensity of organizational
support processes than their Japanese counterparts. Better planning processes are
likely to yield better project estimations. Therefore, we propose:
H1: The extent of project management tool use positively impacts the degree of
overall project benefits.
H2: The extent of project management tool use minimizes the deviation from project
estimation.
2.2 Project Risk Assessment, Project Estimation, and Project
Success
The success of a project was once viewed primarily as a matter of scheduling, but it
actually depends on many factors [11]. Among the critical success factors are project
risk addressing, assessment, and management [9]. Project risk is defined as “an
uncertain event or condition that, if it occurs, has a positive or negative impact on one
or more project objectives such as scope, schedule, cost, and quality” [12]. Thus, the
estimate of a project inherently depends on how its project managers assess the degree
of project risks. A decent estimate of a project is a prerequisite for successful
outcomes with projects such as information system development [13]. For instance,
inadequate project estimates result in the amoebic growth of project costs [14], which
in turn minimizes project benefits. Thus, we hypothesize:
H3: The degree of project risks positively impacts the deviation from project
estimation.
H4: The deviation from project estimation negatively impacts the degree of overall
project benefits.
3. METHOD AND RESULTS
A survey questionnaire was developed and distributed to 200 randomly chosen
registered Project Management Professionals (PMPs) from the list of Project
Management Institute (PMI) members in China. A final sample of 93 valid responses
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was obtained (the response rate of 46.5%) and used to test the hypotheses. The
majority of respondents were department managers (31.2%), followed by project
managers (20.4%), line managers (17.2%), general managers (10.8%), and deputy
general managers (7.5%). As for company characteristics, 38.7% of PMPs in our
response are currently working for state-owned companies, versus 61.3% of PMPs for
private companies. Respondents were also asked what types of projects they are
currently responsible for. A large proportion (60.2%) of respondents work on business
projects, whereas 21.5% work on IT projects and 18.3% on both IT and business
projects.
The research model was tested using structural equation modeling with partial least
squares (PLS) because PLS enables a small sample size and latent (reflective)
constructs to be modeled as formative constructs [15]. The constructs of the variables
adapted were Project Tool Use (formative, 4 items) [2], Project Risk Assessment
(formative, 2 items) [16], Deviation from Project Estimates based on the four basic
variables of project estimations (reflective, 4 items) [16], and Overall Project Success
(reflective, 7 items) [2]. The results of path significance tests using a PLS model is
given in Figure 1.
Project Management
Tool Use
Project Risk
Assessment
Deviation from Project
Estimates
R2 = 0.055
Overall Project Success
R2 = 0.163
0.382***
N.S.
-0.234**
-0.136*
*: significant at α = 0.10, **: α = 0. 50, ***: α = 0.01
Figure 1. Results of PLS model
The summary of hypothesis tests is shown in Table 1. H1 is strongly supported, given
the beta estimate of the path from Project Management Tool Use to Overall Project
Success is -0.382 (p < 0.01). The path between Project Management Tool Use and
Deviation from Project Estimate is not significant. This does not support H2. H3 is
supported, given the beta estimate of the path between Project Risk Assessment and
Deviation from Project Estimate is -0.234 (p < 0.05). Finally, Deviation from Project
Estimate marginally impacted Overall Project Success with the beta estimate of
-0.136 at p < 0.10. Then, H4 is weakly supported.
Table 1. Summary of hypothesis testing
Hypothesis
Result
H1: project management tool use overall project benefits
supported
H2: project management tool use less estimation deviations
not supported
H3: project risk assessment less estimation deviations
supported
H4: less estimation deviations overall project benefits
supported
4. IMPLICATIONS AND CONCLUSION
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Overall results of this study draw several important lessons for both researchers and
project managers. First, PM tool use is effective to assure project success. Among the
26 PM tools entered into the model, about 85% were not significant for the model and
removed from the final hypothesis testing. The PM tool significant for the model are
those that manage (1) overall project planning, (2) resource costs, (3) risk
management plan, and (4) disciplined change control process. That is, not all PM
tools are critical for project success. Project managers should reference this result and
consider which PM tools to adopt given the relative abundance of PM tools. Second,
PM tool use does not impact the accuracy of project estimates. Rather, better project
risk assessment minimizes the deviation from project estimates. Such results should
not be taken by surprise because most PM tools are not meant to be forecasting tools
but management tools to anticipate contingencies and risks and cope with dynamically
changing projects and their operational environment. Finally, the accuracy of project
estimates does play an important role in achieving better project outcomes. The more
accurate project estimates are, the higher overall project benefits.
There are several limitations of this study. The study participants were project
managers in China. PM operational environments in other geographic areas may give
slightly different results. Also, the sample size of 93 is relatively small. However, the
study did draw project managers with diverse profiles at a high response rate. Future
studies should test the external validity of the results based on more project managers
with possibly different profile distributions in different geopolitical areas.
5. REFERENCES
[1] T. Project Management Institute, 2016 Pulse of the Profession, in, 2016.
[2] O. Zwikael, S. Globerson, From critical success factors to critical success
processes, International Journal of Production Research, 44 (2006) 3433-3449.
[3] PricewaterhouseCoopers, Insights and Trends: Current Programme and Project
Management Practices, in, 2012.
[4] A.M. Pereira, R.Q. Gonçalves, C.G. Von Wangenheim, L. Buglione, Comparison
of open source tools for project management, International Journal of Software
Engineering and Knowledge Engineering, 23 (2013) 189-209.
[5] H. Thamhain, Managing risks in complex projects, Project Management Journal,
44 (2013) 20-35.
[6] T. Raz, E. Michael, Use and benefits of tools for project risk management,
International Journal of Project Management, 19 (2001) 9-17.
[7] M. Cohn, User stories applied: For agile software development, Addison-Wesley
Professional, Boston, MA, 2004.
[8] P. Mayring, Qualitative Sozialforschung, Beltz Verlag, 2002.
[9] J. Fortune, D. White, Framing of project critical success factors by a systems
model, International Journal of Project Management, 24 (2006) 53-65.
[10] O. Zwikael, K. Shimizu, S. Globerson, Cultural differences in project
management capabilities: a field study, International Journal of Project Management,
23 (2005) 454-462.
[11] W. Belassi, O.I. Tukel, A new framework for determining critical success/failure
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factors in projects, International Journal of Project Management, 14 (1996) 141-151.
[12] T. Project Management Institute, A Guide to the Project Management Body of
Knowledge (PMBOK® Guide), Project Management Institute, Incorporated,
Newtown Square, PA, 2013.
[13] K. Burnett, Project Initiation, in: The Project Management Paradigm,
Springer-Verlag London Limited, 1998, pp. 131-172.
[14] C. Eden, F. Ackermann, T. Williams, The amoebic growth of project costs,
Project Management Journal, 36 (2005) 15-27.
[15] W.W. Chin, P.R. Newsted, Structural equation modeling analysis with small
samples using partial least squares, in: R. Hoyle (Ed.) Statistical strategies for small
sample research, Sage Publications, Thousand Oaks, CA, 1999, pp. 307-342.
[16] O. Zwikael, A. Sadeh, Planning effort as an effective risk management tool,
Journal of Operations Management, 25 (2007) 755-767.
