How does it compare to your list?
When you look at lists from project managers in different industries (construction, software, research, IT, manufacturing, etc.), you will find that their lists of reasons for why projects are late are almost identical, regardless of the industry.
What do the reasons on the list have in common?
In the mid-1990s, Dr. Eli Goldratt, creator of Theory of Constraints and author of "THE GOAL", asked himself this question.
His observation was that all the reasons that project managers use to explain why projects are late and over budget seem to be examples of “On projects, many things can happen that are simply out of our control.”
Or put differently, most Project Managers believe it is the Variability and Uncertainty that is the MAIN cause of delays and budget overruns.
Is this really true?
Dr. Goldratt challenged this assumption.
What if the leading cause was how we manage projects?
How could we check the hypothesis of what the MAIN cause is for project delays and cost-over-runs?
Is it the level of inherent variability and uncertainty in projects?
Or is it the way we manage projects?"
The traditional way of testing is through pilot studies. You can implement new rules for planning and executing projects like Critical Chain or Agile Kanban and see what happens.
However, this can be a risky and costly way to test the impact of changing how your organization manages projects.
In Multi-year Projects, even if the changes are relatively simple and can be done quickly, it can take a long time to see the effect of your change.
That means it can take a long time to know whether the change was helpful, not so beneficial, or even harmful.
And the more counter-intuitive the change that is being tested – and Critical Chain and Agile are both counter-intuitive - the more likely you will encounter resistance to change.
Is there a better alternative?
For many decades, industries like aerospace, mining, and manufacturing, have used simulation models to do low-cost, low-risk virtual pilots.
Simulation can be used to check if operational and financial commitments were viable if we thoroughly considered the variability, capacity constraints, and unplanned events. They could even be used to compare the operational and financial performance of different strategies and tactics for how we plan work, allocate resources, and manage execution.
But unfortunately, building simulation models or digital twins of complex systems like Project Management environments is very costly and time-consuming. It would take months, often years, and it would cost hundreds of thousands and sometimes millions of dollars to build them… So only the largest companies and organizations could afford to develop such simulation models.
A few years ago, I challenged myself and my team to see if we could develop a Project Portfolio Digital Twin (PPDT) that is almost entirely self-configurable from data that most companies already have about their projects. If this were possible, we could offer this breakthrough technology to practically any size company.