Edward Peters, CEO of software vendor OpenConnect Systems Inc., draws a distinction between business analytics and business intelligence (BI). Analytics, in his view, is data aggregation and number crunching; BI is taking that data one step further – providing a framework in which to ask questions and implement answers to help organizations become more efficient or grow revenue.
But Peters takes his explanation of BI in another, more generic direction as well, comparing it to a concept every student in America (hopefully) understands before graduating from high school. BI, Peters said in a recent interview, is akin to the scientific method.
If your memory of science lessons is a little rusty, take a look at several stories we published this month and return to science (and BI) basics.
The scientific method begins with a question. For example: How has the mobile BI market changed between June and December 2010? That's what analyst Howard Dresner was looking to discover in his second mobile BI survey. Some of the results surprised even Dresner.
Scientists then construct a hypothesis and test it through experimentation. At Southeast Texas Medical Associates LLP, medical professionals wondered if hospital readmissions exceeded what was necessary. To investigate, SETMA used BI software to compare patients who were readmitted against those who weren't. Within six months, it reduced unnecessary readmissions by 22%.
Finally, after data is collected and analyzed, scientists draw conclusions and communicate them to the larger scientific community. Here's a relevant example for the BI community: advice on implementing an advanced data analysis process from users and consultants who have already performed the experiment of how to do so successfully.
Businesses that have yet to take the plunge may be able to incorporate that information when crafting their own sets of questions and forming their own hypotheses. And so the cycle begins again.
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