Big data really can't be put to use without proper execution. There's a lot that goes into a big data project, and if any part of the package is lacking, then the whole thing could take a hit. But IDC Retail Insights looks to help on that front, and in order to give retailers a better shot at putting full-use of big data analytics to work, introduced recently its IDC Maturity Model.
IDC's study, outlined in the report, “Business Strategy: IDC Maturity Model Benchmark – Big Data and Analytics in Retail in North America,” brought together the results of study of 701 different organizations, including 100 food retailers, 100 non-food retailers and CPG companies, and is designed to support earlier studies from IDC in the field.
The issue that IDC discovered was a general lack, by many figures in the industry, of overall competence in big data and analytics. More specifically, there were five key areas of trouble when it came to big data and analytics: Data, intent, people, process and technology. Failure to understand and apply these five critical areas resulted in less-than-maximum effectiveness of a big data project, and needed to be addressed in order to yield the most from such a project.
But the study went on from there to introduce more noteworthy conclusions. First, the study found that the use of big data was going to be increasingly necessary, and thus one of the biggest investment priorities that retail outlets could make. Moreover, there are two classes of retail business rapidly emerging: Those who are proficient in big data, and those who are not. With about 20 percent of retail businesses occupying the “BDA haves,” as the study refers to such businesses, and 20 percent of retail businesses in the “BDA have-nots” slot, that leaves 60 percent of businesses in the middle and ready to either invest and expand current capabilities or fall behind the curve.
The report also advised retailers to put more investment into big data, as the more mature a big data system is, the more likely it is to produce beneficial results. Focusing on the aforementioned five major points of big data will help produce those improved results, and focusing in a balanced fashion will help produce the most desirable for results.
Big data and M2M are working together to transform retail environments. Digital signage, kiosks and modern point-of-sale solutions are powered by M2M, and collect data for retailers to analyze and deliver value to customers.
Big data is a powerful tool, but the problem with big data is two-fold. One, there has to be the data in place for big data to work with. Like a shovel needs to dig through dirt to find ore to be ground up so gold can be extracted, so too does a big data project need plenty of raw material to work with. If the data is incomplete or otherwise flawed, it has an impact on the project in question. Two, beyond having the data—and having good data—the project also needs to have the ability to make sense of the data. The data needs to be effectively analyzed, trends and patterns found, and the resulting trends and patterns must be sufficiently actionable to be worthwhile.
Big data can mean big things for a business, but having the proper tools and models in place to get the most out of it is very important. IDC's study should provide plenty of information on how to make big data work best for users.
Edited by
Rachel Ramsey
