The paradox of project planning – four strategies for planning successful projects

Revision as of 13:16, 9 May 2023

References

BigThings: ^[1] Modular: ^[2] Curb: ^[3] PMBOK: ^[4] Fuzzy: ^[5]

Abstract

The paradox of project planning refers to the inherent tension between the desire to thoroughly plan a project and the limitations of our ability to predict the future. In his book How Big Things Get Done, Bent Flyvbjerg presents strategies to that can mitigate what he calls “The Iron Law of Megaprojects: over budget, over time, under benefits, over and over again”. According to Flyvbjergs research on more than 16.000 projects in 136 countries, only 8.5 percent delivers on budget and in time, while a mere 0.5 percent deliver on cost, time and benefits.

Think slow, act fast

Projects, by their very nature, have a finite timeline during which they must be completed. Research suggests that projects that extend beyond their projected timeline are more likely to fail [REF Flyvbjerg database]. As time passes, external factors introduce additional risks to the project's success. Recent events such as the COVID-19 pandemic, global supply chain disruptions caused by the grounding of a single container ship in the Suez Canal, and the war in Ukraine, which has caused inflation in the global market, illustrate how external factors can derail even the most carefully planned projects. Therefore, there is a significant incentive to expedite project completion to reduce risk. However, attempting to execute projects within a compressed timeframe is certain recipe for disaster.

The right way to deal with this paradox, is to start thinking about projects in two phases: first, planning; and then delivery. Planning the project include sufficiently researching, analyzing and testing, until there is a reliable road map of the way forward. Delivery is the executing the plan, bringing the project to life. The most important distinction is that planning is almost always much cheaper than delivering a project. Planning happens using computers, paper, physical models and prototypes which is cheap, but it builds the foundation for executing the project, which is expensive.

Therefore, the first heuristic for project managers is to think more slowly during the planning phase, making sure to make the right decisions, before moving into the delivery phase.

How project manager can think more slowly: 1) Embrace the Fuzzy Front End [LINK]. The Fuzzy Front End is often tied to product innovation. It is, however, also a strong method for aligning stakeholders, defining requirements and a way to plan a project before it is ready for delivery. 2)

Plan iteration into your project

Only a select few can excel at performing a task perfectly the very first time. Most people need time to practice and learn, and the same is true for projects. Therefore, it is wise to include mechanisms for learning in project planning to ensure that knowledge can be acquired and utilized. Professor Bent Flyvbjerg, known for his extensive work and research on large projects, has identified two crucial factors for planning successful projects: replicable modularity in project design and speed iteration. The following is a guide for project managers on how to implement iteration in projects.

One approach to iteration is the concept of the minimum viable product (MVP), which involves creating a basic version of a product or service that can be tested and refined through feedback from early users. This allows for quick validation of ideas and early identification of potential issues, which can save time and resources in the long run.

On the other end of the spectrum, the maximum virtual product (MxVP) is an approach that utilizes virtual simulations and modeling to test and refine a product or process before physical implementation. This can be particularly useful in complex projects, as it allows for experimentation and iteration in a controlled environment, reducing the risk of costly mistakes during implementation.

Both MVP and MxVP approaches involve rapid iteration and testing, which can help teams identify and address issues early on in the project lifecycle. By implementing these approaches, project managers can create an environment that encourages learning and adaptation, ultimately leading to more successful project outcomes.

Build with Lego

Building upon the second factor identified by Flyvbjerg; modularity in project design. Replicability in projects allows people to learn, and thereby become better at doing what they do. It is therefore important to consider and what type of modularity can be applied in a project. Modularity can be seen in two ways: 1) as stages that a project or product goes through, throughout its lifecycle. These include:

Product modularity refers to the ability to break a product down into smaller, independent components that can be combined in different ways to create different versions of the product. For example, a computer manufacturer may use a modular design for their laptops, allowing customers to choose different configurations of components such as the processor, memory, and storage.

Process modularity refers to the ability to break down the process of creating a product or delivering a service into smaller, independent components. This can allow for greater flexibility and customization in the production or delivery process. For example, a restaurant may use a modular approach to their menu, allowing customers to choose different components such as the main dish, side dishes, and drinks.

Organizational modularity refers to the ability to break down an organization into smaller, independent components that can be combined in different ways to achieve different goals. This can allow for greater flexibility and adaptability in the face of changing circumstances, as well as easier management of different parts of the organization. For example, a large corporation may have different divisions or subsidiaries that operate independently but can be combined in different ways to achieve different strategic goals.

In summary, modularity can be a powerful tool for improving the flexibility, adaptability, and learnability of projects. By breaking down complexity into smaller, more manageable components, and by designing products, processes, and organizations in a modular way, it becomes easier to test, learn from, and improve upon what we do.

Curb your optimism!

When it comes to large-scale projects, one of the biggest challenges is completing the project within the allocated budget and timeframe. Often, these projects exceed both the budget and timeline, which can be attributed to poor planning. While problems during development can cause a project to go over budget, it is often the case that the allocated budget was too optimistic to begin with [REF FLYVBJERG DATABASE]. This can be attributed to two phenomena: optimism bias and strategic misrepresentation.

Optimism bias refers to the tendency for people to be overly optimistic when making predictions about the future. Daniel Kahneman's work has shown that people are often systemically overconfident and optimistic when it comes to planning. This is because people tend to base their estimates past experiences or similar situations that turned out well, thereby skewing the picture favorably.

On the other hand, strategic misrepresentation occurs when people have incentives to lie. For example, a contractor may present an overly optimistic budget to win a contract, or politicians may put pressure on contractors to deliver all the benefits without allocating the necessary budget.

To address these issues, Flyvbjerg has developed reference class forecasting. This method involves identifying a "reference class" of similar projects or situations based on objective criteria such as size, complexity, scope, and context. Data on past projects or situations within the reference class is then gathered and used to make a forecast.

Using a reference class forces the forecaster to consider all relevant information and avoid biases that can arise from focusing only on the positive aspects of a particular project or situation. Additionally, reference forecasting can help avoid the tendency to be overly optimistic by providing a more realistic view of what can be expected based on historical data.

To use reference class forecasting, three steps are required. Firstly, identify a relevant reference class of past, similar projects. The class must be broad enough to be statistically meaningful but narrow enough to be truly comparable with the specific project. Secondly, establish a probability distribution for the selected reference class using credible, empirical data. Finally, compare the specific project with the reference class distribution to establish the most likely outcome for the specific project.

Overall, reference class forecasting can be a useful tool for anyone making predictions about the future, especially in areas such as construction, infrastructure, and other large-scale projects where accurate forecasts are crucial for success.

References

1. ↑ Flyvbjerg, B., & Gardner, D. (2023). How big things get done: The surprising factors behind every successful project, from home renovations to space exploration. Macmillan.
2. ↑ Flyvbjerg, Bent, 2021, "Make Megaprojects More Modular," Harvard Business Review, November-December issue, pp. 58-63.2
3. ↑ Flyvbjerg, Bent. (2008). Curbing Optimism Bias and Strategic Misrepresentation in Planning: Reference Class Forecasting in Practice. European Planning Studies. 16. 3-21. 10.1080/09654310701747936
4. ↑ Project Management Institute, Inc. (PMI). (2021). A Guide to the Project Management Body of Knowledge (PMBOK ® Guide) – 7th Edition and The Standard for Project Management - 3. Project Management Principles. Project Management Institute, Inc. (PMI).
5. ↑ Addressing the Problem of Fuzzy Front End | PMO Advisory. (n.d.). Retrieved May 9, 2023, from https://www.pmoadvisory.com/blog/addressing-the-problem-of-fuzzy-front-end/.