Oct 14, 2022 5:54 PM
Replying to Kiron Bondale
...
Given the number of variables involved including:
- Regulatory requirements
- Internal standards & policies
- The innate complexity of the project scope itself
- The make up of the team
- The level of organizational PM maturity & support
- The appetite or bias of stakeholders towards one approach or another
any time of decision-support tool would just provide guidance rather than something one could adopt with full confidence.
Even the DA toolkit relies heavily on the concept of GCI and lifecycle choices are covered under that - if we don't find the choice we've made is suitable, run an experiment with a different one and decide what to do.
I would say that this is part of the judgment which a PM develops over time with regards to a specific category or segment of projects.
Would there eventually be an AI which could pick the right approach based on access to quality data of thousands (if not millions) of completed projects? Possibly, but I'm betting on "garbage in, garbage out" making that exercise extremely complex!
Kiron