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In my experience, four causes for project failure are:
100%Q. In your specific project experiences what percentage of each of the four (4) attributes above would you assign, such that the total per project always adds up to 100% of its "Common Causes?"Stay Healthy!Cheers,Bill
I think understanding and learning from project failures is an important topic for all engineers and fundamental for professional growth. However, I don't think this is topic that can put in a simple box.
By way of grounding, I see project failure as not being able to deliver on or meet promises. These could be cost, schedule, or functionality or some combination. I'm using functionality here as a catch all for solving the right problem and providing a solution that meets the requisite level of serviceability, reliability, longevity and public acceptance.
From my own experience and as a student of this topic I can muster up a list of frequently occurring themes of causality leading to project failure. But, I also see a dependency between these themes and their relative importance on project characteristics and setting. For me, these factors include project type and scope, technical complexity and novelty, commercial setting, non-technical issues, and actors (catch all for owner, stakeholders including general public, designers, contractors, etc.). Therefore my earlier comment about being careful to over simplify.
The professional, academic and grey literature is replete with information on project failures and causality. I think this is where engineering professionals need to go to learn. Sadly, from my own experience, there's a reluctance to learn and or the desire to get something done takes precedent over the fundamentals of seeking out experience and learning from others.
I also think the connection can be made between themes of causality behind project failures and cognitive biases and heuristics. Examples of cognitive biases and heuristics that I think are common in the engineering world include over confidence, confirmation and anchoring. The Dunning–Kruger effect is also important in explaining behaviors and outcomes. I think awareness of the role cognitive biases and heuristics play in determining outcomes is equally important as learning from experience.