How Bias Impacted the Project Manager Decision to Not Terminate a Failing Project

How Bias Impacted the Project Manager Decision to Not Terminate a Failing Project

Kenneth David Strang, Narasimha Rao Vajjhala
Copyright: © 2022 |Pages: 17
DOI: 10.4018/IJITPM.304059
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Abstract

Almost half of projects have failed globally during the last 50 years yet most studies in the literature review were inclusive. The research design was a robust repeated measures controlled experiment where the 16 participants received all treatments, which may be contrasted to a similar 4 x 4 factorial experiment with a control group (common in psychology or healthcare) resulting in a group size of only 4. All but the individual project manager (PM) factors were controlled, while primary demographic and behavior data were collected. PM’s were tested for competence using a risk management scenario, and given two manipulated conditions (a basic and a biased treatment). Since the organizational and project level factors were controlled, some individual level factors impacted the decision. PM’s with higher competence made better decisions, with a 22% effect size, when all other factors in the model were accounted for. Competent non-certified PM’s made better decisions as compared to certified incompetent PM’s.
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Introduction

Practitioners need to determine why approximately half of all projects fail globally because the cumulative economic cost will be enormous, and more so the professional project management discipline was developed to prevent that. It is generally accepted across all disciplines and industries globally that the project failure rate of approximately 50% has not varied significantly in over 5 decades (Borbath, Blessner, & Olson, 2019; Eckerd & Snider, 2017; Strang, 2021). By analogical comparison, what would happen if half of all global heart surgery projects failed? The project manager (PM) is the leader and decision maker in their project. Consequently we can make the reasonable assumption that the PM was hired or appointed based on their individual factors including competency. Does this mean half of all PMs are not competent? We assert no, instead, there must be other causes for the high project failure rate. Unfortunately, a thorough review of the literature returned only a few empirical studies pinpointing the common project failure factors, namely PM experience and certification (Anthopoulos, Reddick, Giannakidou, & Mavridis, 2016; Laurie, Rana, & Simintiras, 2017; Strang, 2021). Nonetheless, in those studies, most project failure factor effect sizes were small, such as lower than 2%. Consequently, it is clear more research is needed to determine why up to half of all PM’s failed to meet their scope, time, quality and or budget mandates.

An alternative argument in the literature is that a competent PM is not individually responsible for project failures due to factors beyond their control, at the organization, industry, or global levels of analysis. To elaborate on that, the common organizational level project success factors encompass firm level predictors such as executive competency, tenure, size, revenue, and maturity level/standard operating procedures (Laurie et al., 2017; Pace, 2019). Not surprisingly, corruption and bureaucracy were found to be related to project problems (Carlton, 2019; Jennings, Lodge, & Ryan, 2018; Orr & Scott, 2008). The most salient claim of project success factors was that larger organizations will have more revenue, resources, and elasticity to subsume risks and therefore prevent failure, as compared to the small-to-medium-sized-enterprises. To explain this in more detail, their studies posited that older profitable companies were likely to have effective leaders, good quality documentation, mature best-practices, and big companies pay attractive salaries to retain the most talented, well-educated certified PMs. Paradoxically, none of those organizational factors have yet been proven to account for project failure, although some studies have produced significant results from population-specific small samples but as noted above the effect sizes were either missing or negligible (Anthopoulos et al., 2016; Carlton, 2019; Damoah, Akwei, Amoako, & Botchie, 2018; Jennings et al., 2018; Pace, 2019). Furthermore, many new global risks recently occurred including the COVID-19 coronavirus pandemic, economic volatility, climate change, and political instability. Thus, more research is needed to examine if the organizational and global factors impact project failure.

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