7504BEQR Project Planning Executing Controlling Closure Assignment Sample

Introduction Of Project Planning Executing Controlling Closure Assignment

The accuracy of the time, cost, and benefit estimates in projects depending on the industry is another common problem that plagues organisations’ projects and results in substantial losses. The causes of these project challenges have received much attention, with scholars and practitioners analysing the causes of these delays and overruns to find feasible solutions. Herein, based on these points, several theories from psychology and organisational behaviour can be highlighted as several perspectives of the causes of inefficiency in the projects. Still, one of them is worth a closer look – the planning fallacy, which defines a universal human inclination to underestimate the time, money, and possible difficulties of a given task even if one has some prior knowledge and experience with similar assignments.

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Overview of the Planning Fallacy

In general, the planning fallacy refers to the phenomenon of over-optimism when planning projects, underestimating the time, money, and effort which are needed to implement the planned activities, as evidenced in daily practical experience. This idea was originally developed in the late 1970s by framing studies as done by Kahneman and Seversky (The Decision Lab, no date). These authors noted that people and teams tend to demand less time to complete subsequent tasks and are overoptimistic in their production and performance estimates when there are distractions and challenges. The planning fallacy occurs when people believe a task will take less time or effort than it actually requires, even if they have previously made the same error. This happens because they focus on the best-case scenario and ignore previous delays or problems. Moreover, the kind of planning fallacy is ‘anchoring’, where people backtrack to the initial capacity points regardless of their infeasibility. The planning fallacy is especially valuable in project management since it creates inaccurate time and cost estimates and unfavourable project changes (Buehler et al., 1994). Since optimism bias forms a major part of the planning fallacy, project managers and teams tend to underestimate the project’s difficulty and needs, making them ignore the possibility of risks and difficulties. Project managers can avoid making planning fallacy mistakes by using past data, setting risk margins, and using forecast check-ups to make every planning and control activity more relevant.

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Literature Review: The Planning Fallacy in Project Management

The planning fallacy, a concept which has been studied extensively in the field of project management, is the phenomenon whereby people underestimate the time and costs needed to complete a particular task, regardless of experience and statistics. It further results in underpreparation for probable difficulties or time loss, a factor evidenced by various industries (Love, Ika and Sing, 2019). Hohmann (2022) also notes that the planning fallacy is a case of the inside view, that is, a project-specific approach, not the outside view that incorporates data from comparable projects to compile far more accurate estimates (Hohmann, 2022).

Flyvbjerg and his team came up with methods such as "reference class forecasting", which involves comparing an estimate of a project cost with statistics of analogous projects in a class referred to as a "reference class", with the hope of reducing optimism-inflation by establishing a statistical baseline. For example, a project manager is planning to decide the cost of the executing stage; then, in such a case, they can compare the cost of other successful projects, and relatively the cost can be decided. Other recent work also finds that other factors such as project complexity, scope, and change, as well as managerial optimism, also magnify the fallacy’s effects (Stone, 2023). Research into projects in different fields suggests that while historical data provide more accurate estimates, optimism bias always reigns because organisations have institutional/motivational pressures to over-optimise the project timelines and budgets. They incorporate quantitative value methodologies and psychological modifications as a way of providing more composite, not arbitrary, solutions (MacGillivray, 2021). Through ‘outside view’ methods of forecasting and ‘reality check’ methods where expectations can be periodically adjusted based on previous actualisations, project planners can work to control optimism bias and thereby the effect of the planning fallacy on the project (Armstrong and Green, 2018).

Furthermore, group work common in most project events results in group polarisation and peer pressure whereby no one is willing to question the high estimates made by others in the group. The group polarisation affects the decision-making to a great extent. It is due to the reason that when views of different people in a team are different, then it will be affecting the decision-making, as it will get delayed. Thus, a better strategy to reduce group polarisation is to make a balance between information exposure and trying to develop heterogeneous relationships so that better working can be fostered. To counteract these effects, structured decision-making activities, such as project review and assessment meetings, should be planned and utilised, particularly during planning sessions where critical thinking and the expression of concerns are expected.

With further analysis, it is clear that Hohmann supports the project-specific approach because, in case of attaining the goals of the project, it needs to be specific to the requirements of the project. Further, when the project management is not specific, then it will be affecting the accomplishment of the project. On the other side, the view of Flyvbjerg states that taking external data and help is assistive in ensuring that the project is accomplished well. Both the views affect the completion of the project differently, as the objective of the project is also different. In case external help is taken, then there are chances that the project will become successful, whereas when the project is not specific, then the working objectives will also not be attained well.

The planning fallacy theory proposed by Kahneman and Tversky shows that people believe that more time, money, and effort will be needed than is practically possible in actuality. It identifies a cognitive error similar to the inside view that will largely concentrate on the details of the project while ignoring the outsider view, which is the basic statistics of similar projects (Zohrehvandi and Soltani, 2021). Although the theory provides a good angle for looking at cognitive biases in project management, its empirical basis has been criticised for inconsistency in analysing situational factors that affect projects. For example, Armstrong and Green (2018) show that the planning fallacy generalises across tasks, and while excessive knowledge about project processes reduces optimism, it does not reduce the errors of these optimistic forecasts (Armstrong and Green, 2018). Further, the cognitive biases can affect the project outcome, and it can result in failing to identify the proper risk, and as a result of this, overestimation might take place. Thus, as a result of this, the future prediction of the project may be impacted. However, providing better training to the project manager will be assisting them in identifying the better biases and trying to overcome the issues. For instance, due to bias, the project manager thought that the project would be accomplished on the scheduled time, but in actuality, there was a technical breakdown, and the project got delayed.

On the other hand, Stone focuses on the fact that when the organisational pressure and corporate culture are focused, then it creates some of the challenges in project planning. This is due to the reason that when the project planning is done under any pressure, then it will be affecting the planning. So it is mandatory for the company or the project manager that they must effectively try to work on improving the efficiency of the project.

Critics have cited yet again the planning fallacy as relying too much on cognitive factors without docketing context and organisational factors. For instance, Stone (2023) opines that corporate culture and organisational pressure ensure that managers provide stakeholders with overly optimistic project timelines, which automatically make the forecasts deliberately biased. These organisational pressures are prevalent in almost every type of industry, and they impact the work to a great extent. The assumption underlying the pressure is that when employees are pressurised, then they will be working well. But in actuality, when more pressure is created, then it creates a negative impact on the performance of employees, and ultimately, project objectives will not be attained. This brings us to the second aspect, the social and organisational dimension, which implies that correcting the planning fallacy is not only or even primarily a matter of modifying the way people think about their planning heuristics and their forecasts; it precludes revising organisational structures that do not accommodate accurate and public planning (Stone, 2023).

Moreover, some critics do not agree with the “outside view” strategy, which includes the reference class forecasting, because the ideas do not work for all industries and projects (MacGillivray, 2021). This is especially the case in industries characterised by higher-than-average innovation, where the past does not hold good pointers to cost and time. Another weakness is that Love, Ika, and Sing (2019) also discovered that reference class forecasting is most efficient when project types are clearly defined, which means it is not suitable for innovative or complicated projects. These criticisms stress the need to go beyond the simple treatment of the planning fallacy at the individual level by incorporating both cognitive and organisational solutions for developing effective, fact-based forecasting methodologies in project management (Love, Ika, and Sing, 2019).

The Mechanisms and Causes of Optimism Bias in Project Planning

Over-optimism is widely acknowledged to be a pervasive feature of project planning and estimation because it distorts the resulting estimates. As to the range of cognitive and psychological causes, overconfidence can be considered the primary reason for this bias. Self-confidence is a very closely related concept to overconfidence, here referring to a situation whereby people overestimate their calibres and judgements. Hence, the risks associated with contingencies are grossly underpredicted, and contingency budgets are overly optimistic. Optimism bias is influenced by the organisational context in the way discussed above. It is widely understood that there is tremendous pressure within many organisations to deliver optimistic forecasts to key stakeholders, including senior management and investors. This pressure can disenfranchise certain aspects of the planning and scheduling of projects since, aware or subconsciously, project managers may manipulate estimations to support the optimistic outlook. It deters free and frank discussions of potential risks or issues associated with various approaches to the project since such a culture can reinforce optimism bias. Self and other accountability also play a part in optimism bias (McKinsey & Company, 2021). This is especially the case when project managers are made to answer for their choices, and therefore, they may opt for higher short-term benefits rather than use appropriate estimative heuristics. It may lead them to deny perceived risks or ignore past data that goes against their estimates. Consequently, there is a tendency of providing over-optimistic time overtures and costs as potential means of building image, the promulgation of which may obliterate project challenges. Moreover, pessimism bias is also influenced by external factors working for and with the organisations. Clients and other business partners normally harbour some self-serving interest in wanting to see the forecast positive of a project, and this colours project teams’ operations. This external pressure forms a loop of pressure under which project managers are forced to offer unfavourable estimates due to possible negative impacts if they highlight possible challenges. Therefore, the simple need to keep good relations with stakeholders results in an optimistic bias cycle (Norrie, 2020). One practical way to reduce optimism bias is to use structured narratives of project management aimed at realistic forecasts. Such methods as reference class forecasting, in which cost estimates are based on historical information from like projects, can help avoid biases. They also suggest that promoting good relations in an organisation can prevent, or at least reduce, the psychological factors that are related to optimism bias. By doing this, organisations can enhance project success rates since the forecasting of potential challenges shall be accurate due to the many discussions that take place under the assertion that potential challenges may exist.

Impacts of the Planning Fallacy on Project Outcomes

The planning fallacy always has the greatest effects on the projects’ outcomes, including such nugatory features as unrealistic timelines, costs, and project scopes. This cognitive bias leads to projects and their particular tasks being underestimated by the project managers and the complete teams and likewise leads to huge variations between initial time and resource estimates. As such, the projects get into serious issues with regard to their objectives and fail to deliver their promise to the stakeholders as well as diluting the true spirit and essence of the project. Without doubt, the planning fallacy is the most expressed in the prolongation of project time estimates. Since it deals with the estimation of the duration of tasks, when project managers get it wrong, they set unattainable time frames (Sahlins, 2020). This results in a snowball effect, for as the teams advance in the project period, they stumble on new challenges, thus requiring extensions that are most times unpalatable to the stakeholders. For instance, the Sydney Opera House project, which was supposed to take 6 years, was completed 15 years later. The evaluative in the initial optimistic timeline depressed the real processes in the design and construction processes, which were marked by serious delays and criticisms. Where cost is concerned, one effect of the planning fallacy is excessive spending, which leads to over-budget projects. This is often mirrored by the fact that when initial cost estimates are derived based on unrealistic time horizons, more money is spent than is initially planned. This is most visible when teams are under pressure to deliver their work on time and new rates culminate into new charges for labour and materials, not forgetting the control of quality (Tversky and Kahneman, 2020). The optimism bias is also well illustrated in a chapter that discusses the Denver International Airport project, which cost more than triple what was expected, from an estimate of $1.7 billion to nearly $5 billion. Design error and there were a lot of technical problems encountered in the project, which is how optimism distorts the financial attitude and leads to financial doom. About the planning fallacy, there are other ramifications such as scope creep – the increase in the project’s scope. Often when the project manager commits fewer resources and time to a project, s/he may be forced to accept more features or changes from stakeholders to meet their expectations, and this complicates the project (van der Meer, 2019). This is common in scenarios where, during the construction of a massive project such as the California High-Speed Rail, the plans that are developed become larger due to public and political demands. Throughout the project, an increasing number of enhancements were incorporated; hence, its overall time and cost increased sharply, resulting in a public outcry and doubt over the viability of the project. In practical examples, authorities state and describe the negative influence of optimism bias on practical projects. In the case of the construction of the London Heathrow Airport Terminal 5, the estimates showed that this construction was to cost about £2.5 billion and would be completed this year, 2008. Yet, underestimating both the issue’s complexity and time consumption led to £4.3 billion and several delays. A closer look at the MIT and Oracle projects revealed that stakeholders’ overconfidence in their projections resulted in these problems, with the planning fallacy being to blame (van Oort and Vromans, 2021).

Strategies to Mitigate the Planning Fallacy in Project Management

• Introduction to Counteractive Measures Against the Planning Fallacy: Counteractive measures in project management can only be developed and implemented as an integral approach, with special consideration for accurate predictions and sound facts. Fallacy: Counteractive measures against the Planning Fallacy in project management can be developed and implemented only as an integral approach with special consideration for accurate prediction and sound facts.
• Scenario Planning as a Strategic Tool: Strategic management tools like scenario planning involve the creation of a range of potential future environments by considering various assumptions and risks. This soft systems method enables project managers to compare identified risks to the project in terms of timelines and budget, placing them in a better position to handle potential risks (Yamini and Marathe, 2018).
• Utilising Historical Data for Accurate Estimations: Using historical data, particularly real past performance, allows organisations to improve estimates rather than relying on optimistic forecasts based on approximations. For example, many construction projects implement “reference class forecasting”, where estimates are based on past projects of similar classification, reducing bias (Ika, Love and Pinto, 2020).
• Incorporating Contingency Buffers in Project Schedules: Adding contingency buffers in project schedules is a key method for addressing risks related to optimism bias. By incorporating extra time and resources into baseline figures, project managers can effectively hedge against unforeseen obstacles. This practice is especially useful in projects with inherent risks (Zohrehvandi and Soltani, 2021).
• Industry Examples of Counteractive Strategies: Aerospace Industry Companies like Boeing widely use analytics and estimations to develop effective scenario planning High-tech industry firms, such as Microsoft, use feedback from previous projects to refine future estimates, ensuring greater accuracy (Zohrehvandi and Soltani, 2021).

• Structured Methodologies to Improve Forecast Accuracy: These organisations demonstrate that with structured methodologies at their disposal, they can actively counter optimism bias, thereby achieving improved forecast accuracy and project performance (Williams, 2019).

Conclusion

Altogether, the planning fallacy presents considerable difficulties to project management by promoting unrealistic time expectations, budget expenditures, and project extents. Organisations should therefore prepare for risk by using optimism bias mitigation plans that best meet the cognitive and psychological aspects of their personnel, such as the development of contingency plans based on scenarios that reflect a realistic estimation of occurrence and the regular analysis of historical data. Companies in sectors such as aerospace and technology are good examples of major industries where the structured method improves forecasting banners and, in general, project performance. Thus, applying these approaches makes it easy for project managers to manage uncertainties while making realistic project plans that fit organisational and stakeholder demands.

References

• Armstrong, J.S. and Green, K.C. (2018); Forecasting methods and principles: Evidence-based checklists; Journal of Global Scholars of Marketing Science, 28(2), pp. 103–159.
• Buehler, R., Griffin, D. and Ross, M. (1994) 'Exploring the “planning fallacy”: The article titled 'Why people underestimate their task completion times' was published in the Journal of Personality and Social Psychology, volume 67, issue 3, on pages 366–381.
• Flyvbjerg, B. (2006) 'From Nobel Prize to project management: Getting the decisions right', Project Management Journal, 37(3), pp. 29–42.
• Hohmann, J. (2022), "Managing project time and cost: The impact of cognitive biases on planning," International Journal of Project Management, 40(1), pp. 12–25.
• Ika, L.A., Love, P.E.D. and Pinto, J.K. (2020); 'Moving Beyond the Planning Fallacy: The Emergence of a New Principle of Project Behaviour'; IEEE Transactions on Engineering Management, 69(6), pp. 3310–3325.
• Kleim, T. and E. A. T. (2020) 'The role of optimism bias in project estimation', Project Management Journal, 51(4), pp. 356-368.
• Love, P.E.D., Ika, L.A. and Sing, M.C.P. (2019); Does the Planning Fallacy Prevail in Social Infrastructure Projects? Empirical Evidence and Competing Explanations, IEEE Transactions on Engineering Management, 69(6), pp. 2588–2602.
• Lovallo, D. and Kahneman, D. (2003) 'Delusions of success: How optimism undermines executives' decisions', Harvard Business Review, 81(7), pp. 56–63.
• McKinsey & Company (2021) 'Overcoming the planning fallacy: Strategies for better project management', McKinsey Quarterly, 3(1), pp. 30-37.
• MacGillivray, S. (2021); Risk Management: Optimism Bias in Construction
• Norrie, J. (2020) 'Cognitive biases in project management: A review and implications', International Journal of Project Management, 38(8), pp. 633-645.
• Projects, Valency Inc., 23 September. https://valencyinc.com/other/protecting-against-optimism-bias-in-construction-projects/.
• Planning fallacy - The Decision Lab (no date). https://thedecisionlab.com/biases/planning-fallacy.
• Stone, C. (2023); Challenges and opportunities of completing successful projects using Earned Value Management,; Open Journal of Business and Management, 11(02), pp. 464–493
• Sahlins, M. (2020) 'The effect of optimism bias on project performance', International Journal of Project Management, 38(6), pp. 366-372.
• Tversky, A. and Kahneman, D. (2020) 'Judgement under uncertainty: Heuristics and biases', Science, 185(4157), pp. 1124-1131.
• van der Meer, H. (2019) 'Optimism bias and project management: A psychological perspective', Journal of Project Management, 34(2), pp. 124-138.
• van Oort, F. and Vromans, M. (2021) 'The effects of the planning fallacy on project management: An analysis of case studies', Project Management Journal, 52(2), pp. 203-215.
• Vassallo, M. and S. R. (2023) 'Biases in project estimation: Evidence from the construction industry', Construction Management and Economics, 41(4), pp. 295-310.
• Williams, T. (2019) 'The role of project management in preventing optimism bias', International Journal of Project Management, 37(1), pp. 45-57.
• Yamini, S. and Marathe, R.R. (2018); 'Mathematical model to mitigate planning fallacy and to determine realistic delivery time'; IIMB Management Review, 30(3), pp. 242–257. https://doi.org/10.1016/j.iimb.2018.05.003.
• Zohrehvandi, S. and Soltani, R. (2021); Project scheduling and buffer management: A comprehensive review and future directions; Journal of Project Management, 7(2), pp. 121–132. https://doi.org/10.5267/j.jpm.2021.9.00 2.