Category: Project risk management
Project risk management is a key part of managing projects and programmes. It’s been good, but it needs to improve for tomorrow’s challenges.
Risk management is limited to identifying potential problems, describing and sizing them, and then trying to control them. It’s relatively easy to teach, widely applied, and has helped millions of people reduce the project risks at work.
When I think back to the projects we handled 20-30 years ago, I wouldn’t say there is less risk. What’s happened is that we’ve been able to handle much more complex and unstable projects. It’s worked well for new technologies, and agile delivery methods have helped further.
But where now? We have disruptive new technologies like artificial intelligence, the internet of things and quantum computing. And we are seeking to bring data together in innovative new ways to help companies serve their customers. How can project management techniques rise to that challenge?
First, by looking at its weaknesses:
(1) If the risk can’t be described as a potential problem, it’s excluded. That means the “unknowns” are left unmanaged until very late, when they start to emerge. (For more, see stories and posts here on Unknown Unknowns.
(2) The potential problems (risks) are assumed to be independent of each other, like when dice are rolled. But these dice are controlled people who are watching to see how the other dice roll.
(3) Sizing of risk impact is usually done on an “ordinal” scale (such as 1=very low, 2=low, 3=medium, 4=high, 5=very high). But the scale is exponential, and very high could be a 1000 times larger than very low. The calculations of total risk are statistical nonsense.
(4) The way we control risks often introduce new risks, and can impact on other risks.
(5) The risk register becomes a narrative for discussion with people, with each risk following its own journey. The descriptions of the risks evolve as they become clearer. And if they are not avoided and occur as problems, it’s often not was predicted. So we didn’t predict this problem, we predicted something else and are now pretending its the same.
The articles and stories here start to work on illustrating these failings, and how people work around them.