How Big Things Get Done – The Surprising Factors Behind Every Successful Project

In the first chapter we see, based on extensive study of 16,000 projects, the iron law of project management - Over budget, over time, under benefits, over and over again: 47.90% on budget (or better), 8.50% on budget and on time (or better), 0.50% on budget and on time and on benefits (or better). Several case studies are given to show that think fast, act slow will not result in success. Why start projects so prematurely? 

Rush to commit

A reason is the rush to commit. Purposes and goals are not carefully considered. Alternatives are not explored. Difficulties and risks are not investigated. Solutions are not found. Instead, shallow analysis is followed by quick lock-in to a decision (commitment fallacy). Another reason is unchecked, optimism leading to unrealistic forecasts (planning fallacy, Hofstadter’s law, poorly defined goals, better options ignored, problems not spotted and dealt with, and no contingencies to counteract the inevitable surprises. Or strategic misrepresentation. A budget that was made because it could be accepted politically. If people knew the real cost from the start, nothing would ever be approved and use the start digging in hole strategy and make progress so no one would stop it (e.g. the Sydney Opera House). And when the project is in progress they keep going because they already spent so much (sunk cost fallacy or Concorde fallacy).

Think fast, act slow is the answer to the previous part but it is not enough. Why are you doing the project, what is the goal to achieve? Or with other words: think from right to left.

The plan

If we know the goal, how are we going to achieve it. What’s the plan? A good plan is one that meticulously applies experimentation or experience. A great plan is one that rigorously applies both (e.g. the Guggenheim Bilbao). Pixar movie usually goes through the cycle from script to audience feedback eight times. This is an extremely detailed and rigorously tested proof of concept and the next, ninth step is the real development. This is an iterative process that corrects the illusion of explanatory depth. Whatever can be done in planning should be, and planning should be slow and rigorously iterative, based on experience. Compare Eric Ries’ MVP.

Every Olympic Games (since 1960) has gone over budget. The average overrun is 157%. New or unique is treated as a selling point, not something to avoid. This is a big mistake. It’s a main reason that projects underperform. Planners should prefer highly experienced technology (frozen experience). Olympics are forever planned and delivered by beginners (Eternal beginners’ syndrome). Besides the frozen experience to get projects right, the lived experience (unfrozen) of people is as important too. In both planning and delivery, there is no better asset for a big project than an experienced leader with an experienced team using more than only explicit knowledge (e.g. the Empire State Building project).

Underestimation

Once we frame the problem as one of time and money overruns, it may never occur to us to consider that the real source of the problem is not the overruns at all; it is underestimation. To create a successful project estimate, you must get the anchor right. To produce a reliable forecast, you need the outside view. Don’t assume your project is unique. You have to look at a project as part of a class of projects, as one of those. This is what the author called reference-class forecasting (RCF). Reference-class forecasting is better on biases. It’s better on unknown unknowns. If you face a fat-tail distribution, the tail outcomes – the black swans – cover about 20% of the distribution you must do risk mitigation or black swan management.

You can put reference-class forecasting and risk management into your toolbox, along with experience, Pixar planning, and thinking from right to left as essential tools for thinking slow in planning before acting fast in delivery.

Some say, planning ruins your projects. Just get going! Trust your ingenuity! It’s a wonderful sentiment backed by superb stories like electric lady (recording studio Jimi Hendrix), and Sydney Opera House. But if you look at the data, we only remember the success stories, we forget the ones, and those are the majority, that failed.

Delivery team

To take the final, critical step, you need a capable, determined delivery team – a single, determined organism – to act fast and deliver on time. A team that is proud to work for the project, where psychological safety is the norm. Where from the suits to the hard hats, the spirit is the same. Where onsite management and workers worked together. E.g. the Hoover Dam or the Heathrow Terminal 5 (T5).

There are five project types that are not fat-tailed. That means they may come in somewhat late or over budget but it’s very unlikely that they will go disastrously wrong (black swan outcomes, 400 percent or worse over budget). These fortunate ones are solar power, wind power, fossil thermal power, electricity transmission, and roads. Most extreme fat-tailed project types are nuclear storage, Olympics, nuclear power, IT, hydroelectric dam, and airport.

In the final chapter the author discusses why these project types are exceptional? What makes them a safer bet than all the rest and why are wind and solar power the most reliable projects of all to be delivered successfully? 

Modularity

Modularity delivers faster, cheaper, and better, making it valuable for all project types and sizes. The core of modularity is repetition. Put down one Lego block. Snap on another. And another. Repeat, repeat, repeat. Click, click, click. Repetition enables experimentation. If something works, you keep it in the plan. If it doesn’t, you fail fast and adjust the plan. Repetition also generates experience, making your performance better (positive learning curve). When you can build modules and deliver them to the site, the building isn’t constructed; it’s assembled, like Lego. Modularity radically reduces risk. Modular projects are in much less danger of turning into fat-tailed disasters (e.g. the small modular reactors (SMRs) for nuclear plants).

Conclusion

This book offers a crucial guide for enhancing the success of mega projects, drawing on extensive research by Bent Flyvbjerg, a leading expert on mega projects from the University of Oxford. It addresses the high failure rates of projects worldwide, advocating for significant changes in project management approaches. Highlighting the importance of reference-class forecasting (coined by Bent Flyvbjerg), risk management, and a modular approach, the book integrates innovative strategies like Pixar planning and thinking from right to left. Through a clear, logical presentation and the use of many real-life case studies, it makes complex theories accessible and applicable. Despite its minimal use of graphs and tables, the book effectively communicates key concepts, such as fat-tail distribution in project overruns. It is an essential tool for anyone involved in mega project management. I can highly recommend this book.