Biases in Project Management
Contents |
Abstract
The human mind is an effective and powerful tool. However, it is not without faults and has some limitations e.g., biases. In this article cognitive biases are examined, with most emphasis on optimism bias since it is a very important factor in project management. Cognitive Bias also includes other topics such as Gender Bias, Stereotyping and Information Bias. The notion of biases has evolved through time and the understanding of them has been steadily increasing. These biases are very important in a team setting and therefore fall under the realm of project management. It can be found in project management literature when team building is discussed e.g. in Guide to the Project Body of Knowledge where Interpersonal and Team Skills or Expert Skills are mentioned. [1] Project managers have a tendency to overestimate benefits and underestimate cost i.e., be too optimistic. This is known as “Optimism Bias” and is widely accepted as a key reason for overruns in projects. [2]
Being aware of these biases is crucial for all project managers in order to be able to offset them. By acknowledging biases and applying appropriate measures, it is possible to counter the effects.
In this article these biases related to Project Management are examined in more detail. How these biases can be seen in project management and measures to counter them are presented as well as how they can be applied and when. Finally, some limitations are considered and topics for further reading recommended.
The Big Idea
What is bias?
The definition of bias in the Oxford dictionary is split in four meanings, two of whom are relevant in project management and will be addressed in this article:
- “a strong feeling in favour of or against one group of people, or one side in an argument, often not based on fair judgement.” [3]
- “the fact that the results of research or an experiment are not accurate because a particular factor has not been considered when collecting the information.” [3]
The first definition is tied to people and communications between either team members or stakeholders. The latter can be more related to uncertainty and risk management.
Cognitive bias [4]
Optimism Bias
Application
Limitations
Annotated bibliography
The following resources are the key resources used for this article, and can provide basis for further and deeper studies on the topic.
1. Leleur, S., Salling, K.B., Pilkauskiene, I. and Nicolaisen, M.S. (2015). Combining Reference Class Forecasting with Overconfidence Theory for Better Risk Assessment of Transport Infrastructure. The European Journal of Transport and Infrastructure Research (EJTIR), 15(3), 362-375. This article highlights the importance of risk assessment in infrastructure projects since large number of projects have has cost overruns. It explains the concept of Optimism Bias and provides measures to combat it. The article recommends using Reference Class Forecasting, overconfidence theory and to interpret expert judgements about benefit and cost estimation, and provides instructions on these methods.
References
- ↑ Project Management Institute, Inc.(PMI). (2017). Guide to the Project Management Body of Knowledge (PMBOK® Guide) (6th Edition). Retrieved on February 9th 2021 from https://app.knovel.com/hotlink/toc/id:kpGPMBKP02/guide-project-management/guide-project-management.
- ↑ Leleur, S., Salling, K.B., Pilkauskiene, I. and Nicolaisen, M.S. (2015). Combining Reference Class Forecasting with Overconfidence Theory for Better Risk Assessment of Transport Infrastructure. The European Journal of Transport and Infrastructure Research (EJTIR), 15(3), 362-375. Retrieved on Feburary 10th 2021 from https://www.researchgate.net/publication/275213953_Combining_Reference_Class_Forecasting_with_Overconfidence_Theory_for_Better_Risk_Assessment_of_Transport_Infrastructure_Investments .
- ↑ 3.0 3.1 Oxford University Press. (2021). bias noun. Retrieved from https://www.oxfordlearnersdictionaries.com/definition/english/bias_1?q=bias on February 9th 2021.
- ↑ Tversky, A. and Kahneman, D. (1974) Judgement under Uncertainty: Heuristics and Biases. Science, New Series, 185(4157), 1124-1131. Retrieved on February 10th from http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=4F92E2FFA38970D381524DF81AF1D10F?doi=10.1.1.207.2148&rep=rep1&type=pdf
- ↑ Make, P. and Preston, J. (1998). Twenty-one sources of error and bias in transport project appraisal. Transport Policy, 5(1), 1-7. Retrieved on February 10th from https://www.sciencedirect.com/science/article/pii/S0967070X98000043
