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The problem statement has since evolved to “there is too much data from all over the place that I don’t know where to start” or that “the data is being updated too frequently that we scamper to react.
Unfortunately, throughout all these years when BI technology developed at such a fast rate, with hundreds of BI applications out there now claiming to be the best in the field, the problem that BI was trying to solve 20 years ago is still there how can the business make better business decisions with the data assets the company?
One key component that was arguably left behind in the journey is the human capability to optimally consume, analyze, and present the information made available to them. A state of the art, multi-million dollar tool cannot replace good human decision making and good business practices. In fact, I have seen in some cases that the same dataset can be used to justify two totally different outcomes. There are even websites that make fun of false correlations people can make with data.
Companies need to invest more in their people – specifically the data analysts and data scientists in their company. I hear a lot of businesses claiming to be data driven but, at the end of the day, they are really “human decision” driven and data only
exists to support analysis done by people. Without a good set of resources that actually knows what the data means or how to put it to good use, the data is just an asset on a shelf. And at its worst, the data could be a dangerous weapon that can sway and support potentially damaging decisions.
I believe that every worker now, whether you are in operations or in the C-suite, is a data consumer and everyone must treat data as a true asset. We should all protect it, govern it, and capitalize on it.
For every BI project, have a corresponding change management program in place to manage the more critical people aspect of the project. The program should train the users on not just how to use the system but also ensure they understand the data behind each visualization, how they can be appropriately combined and used to create metrics and how to verify their work.
The success of business intelligence projects should really be measured not on how much was spent on a system or whether the reports/dashboards went to production, but whether it delivered the expected benefits and that metric is not something that can just be attributed to IT. And that’s because at the end of the day, it is only through a true, honest partnership between IT and business that BI projects can truly succeed.
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