What’s interesting about analytics projects, from my experience, is that they all start out so promising. Someone presents a mock dashboard of what data they can visualize once the project is complete, and immediately everyone is sold on it.
The dashboard looks something like this:
Look how beautiful that is. I mean, who doesn’t want to use data to make better decisions, gain operational efficiencies, and get an edge on the competition?
The reality, however, is starkly different. A majority of enterprise analytics projects fail. Not just fail, but fail before they even start.
Why does this happen? I became really intrigued and wanted to find out the answer, so I got our team together to conduct a study by interviewing 20 senior IT executives in the Chicago area regarding their biggest challenges with analytics projects.