This Guest paper was first published on the PlanningPlanet blog on January 12, 2018 and is copyright to Dr. Dan Patterson, PMP, 2018
Published here
April 2018.

 
Introduction | What Exactly is Artificial Intelligence?
The Problem with Project Planning Today | AI Categories | Current Approaches to ANI
Neural Networks | Which AI Approach is Best for Helping with Project Planning?
Should We Embrace or Avoid AI in Planning?

The Problem with Project Planning Today

One of the hardest challenges in project management is accurately forecasting future outcomes (project completion date, total cost, etc.,) of very complicated and highly uncertain endeavors (projects) — we call this "planning".

As an industry, we have developed some pretty well tried and trusted techniques such as Critical Path Method (CPM) to try and help model project outcomes. But these models are only as good as the inputs we feed into them. Any worthy planning tool today uses CPM as its underlying forecasting engine but as the planner we are still left with the onerous task of knowing which activities to include in our plan. But worse yet, we must decide the activity durations, their cost and even sequence?

However, CPM does little more than convert durations and sequences of durations into a series of dates. It doesn't help one bit with:

  • What scope should I focus on when building my plan?
  • What activities should we include?
  • What should our durations be?
  • What is the true sequence and logic between our activities?

If CPM were the be-all and end-all solution, then we wouldn't continue to experience project cost and schedule overruns. The problem isn't CPM though. The problem is our inability to accurately model what we think will happen during project execution because of
The huge number of variables (tasks and sequence) and
The huge number of uncertainties associated with those variables (duration or scope uncertainty).

True, schedule risk analysis tools help tell us how bad our forecast may be, but they do nothing in terms of telling us what the inputs to our schedule should have been in the first place!

This is why I believe AI can massively help project planning. If AI can help the planner by making suggestions that are sound, then the immense challenge described above starts to become surmountable. Added to that, if our planning tool can also start to make better suggestions by observational or associative learning, then we are headed down a seriously valuable and exciting path.

What Exactly is Artificial Intelligence?  What Exactly is Artificial Intelligence?

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