Working Up

by Dwayne Phillips

Special projects fail because they aren’t that special. We pretend or wish them to be so we can forego proven techniques and hard-learned lessons.

We know why fill-in-the-blank projects fail. Let’s fill in the blank:

• Artificial Intelligence
• Machine Learning
• big data
• data lake
• non-profit
• whatever

Of course these projects are different from the normal project. Every project is different. And given that, what is a “normal” project? I guess we could average this and that and find a norm and standard deviation and such.

These special projects fail because they aren’t that special. They are more like the normal project than they are different from it. There are known ways to project success and there are known ways to project failure.

Telling myself that, “This is a special project, not like others so I don’t have to stick with the known fundamentals and avoid the known failure modes” is wishful thinking. Sometimes wishes come true. More often, however, they don’t.

This isn’t that special. Sorry.