Understanding why projects fail
AA: We often hear statistics being thrown around about projects failing in organizations. We could delve deeper and discuss what they mean by “failure,” but if we just take that as a given, do you think this is a reality in many organizations, and if so, what’s the reason for this?
CS: I do hear this statistic a lot. It is usually stated that 80 or 90 percent of data science projects fail, and I believe it is a pretty good representation of reality.
I think it comes down to many different factors. Again, it depends on how we define failure.
I don’t like the word “failure” because, usually, you learn from your mistakes, so it is not a complete failure.
When you fail, you should learn from what you did wrong and implement changes to be successful the next time around. If you do it that way, then it is not really a failure – it is a learning journey and a benefit for you and the company.
Usually...