You can't responsibly commit to a recovery plan before understanding the problem.

Imagine taking over a product development project that's already behind schedule.

As the Project Manager, what's your first move?
 
Will you immediately push the team to accelerate delivery or promise stakeholders that everything will be back on track in two weeks?

Personally, I'd start by understanding the situation first.

I'd review the delivery plan and available project documentation, speak with key stakeholders to understand the business needs, and work closely with the development team to understand what's been delivered, what's outstanding, why we're behind, what blockers or dependencies remain, and the possible risks.

I'd also check whether the scope and priorities still reflect the business objectives and customer feedback.

From there, I'd work with the team to assess the remaining work, apply MoSCoW, assess capacity, and make trade-offs before agreeing on a realistic recovery plan and communicating what we can deliver.

You can't responsibly commit to a recovery plan before understanding the problem.

And this brings me to something I've been thinking about lately.

Where is AI in all this?

AI can help organize information, analyze risks, and explore options.

But it can't take responsibility for understanding the project, building trust with stakeholders, understanding team dynamics, making decisions, or exercising judgment when new information changes the plan.

What happens when a senior stakeholder asks an unexpected question in a meeting?
Or a developer raises a concern that changes the delivery approach?
Or new information challenges the plan you presented yesterday?

Still learning, as we all are, but I believe good project management requires more than knowing which tools to use.
It requires understanding the work, working with people, and taking ownership of decisions.

#ProjectManagement #ProductManagement #ProjectGovernance