How retail is learning about BI from the NSA

Nestor E. Arellano

11 years ago

By now, almost everyone knows of the until now very top secret program Prism which helps United States intelligence agencies gather and mine enormous amounts of data from Internet service providers and phone carriers to help the government in its anti-terrorism operations.

Not many however, know that since 2011 the U.S. National Security Agency has made available to the public a major component Prism called Accumulo. The Hadoop-based code enables software developers create tools that enable businesses to sift through big data with similar capabilities as the NSA, according to a recent article from Forbes.com.

While the intelligence agency creates patterns and look for irregularities to spot potential terrorist or criminal activities, the retail sector uses software to go about it the other way around. For instance, retailers want to find large numbers of people that fit a certain groups so that they can develop products they could sell to these individuals.

For many businesses the use predictive analytics to boost the bottom line is no longer a question of should we, but rather of where and how, according to Forbes’ Greg Pedro.

Where – Predictive analytics can be used in areas such as targeted email offers, to setting dynamic real-time pricing to finding out which products to develop or buy.

By using predictive analysis to understand customer demand patterns, manufacturers can boost their gross margin by three to five per cent, according to a 2011 Gartner report.

However, e-commerce represents only 10 per cent of the use of predictive analytics. Many organizations are using predictive analytics to replace traditional gut feel methods in sorting out things such as product assortment decisions. One of the advantages of using predictive analytics tools is that they eliminate human biases in the decision making process.

How – Once they have figured out a where, organizations need to decide how they can deploy predictive analytics. From a cost perspective big data and predictive analytics save retailers time and money by cutting their investments in IT personnel.

Most retailers also chose to buy rather than build their own predictive analytics tools. In buying predictive analytics software, businesses have two basic options: purchasing software from a predictive analytics software provider; or buying the technology itself.

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