What’s interesting about analytics projects, from our experience, is that they all start out so promising. Someone presents a mock dashboard of the data they can visualize once the project is complete, and immediately everyone is sold on it.
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? We became really intrigued and wanted to find out the answer, so our team got together to conduct a study by interviewing 20 senior IT executives in the Chicago area regarding their biggest challenges with analytics projects.
What we discovered was a little surprising, to say the least. It had nothing to do with the visualization, data science team, or analytics products.
The biggest issue that caused many of these analytics projects to fail?
The inability to get the right data to be analyzed.