Crime fighters have long used brains and brawn, but now a new kind of technology known as “predictive policing” promises to make them more efficient. Colleen McCue, pictured on July 10, who is a behavioral scientist at GeoEye, a firm that works on predictive analytics, said studying criminal behavior was not that different from examining other types of behavior like shopping.
A growing number of law enforcement agencies, in the US and elsewhere, have been adopting software tools with predictive analytics, based on algorithms that aim to predict crimes before they happen. The concept sounds like something out of science fiction and the thriller “Minority Report” based on a Philip K. Dick story. Without some of the sci-fi gimmickry, police departments from Santa Cruz, California, to Memphis, Tennessee, and law enforcement agencies from Poland to Britain have adopted these new techniques. The premise is simple: criminals follow patterns, and with software — the same kind that retailers like Wal-Mart and Amazon use to determine consumer purchasing trends — police can determine where the next crime will occur and sometimes prevent it. Colleen McCue, a behavioral scientist at GeoEye, a firm that works with US Homeland Security and local law enforcement on predictive analytics, said studying criminal behavior was not that different from examining other types of behavior like shopping. “People are creatures of habit,” she said.
Analytics increasingly provide competitive differentiation for insurers and are at the heart of the industry’s transformation to a more customer-centric business model, according to “Data and Analytics in Insurance: The Dawn of a New Era,” from Strategy Meets Action.
“Analytics hold great promise for the insurance industry, including the application of traditional business intelligence approaches, as well as advanced techniques such as predictive models and Big Data,” said Mark Breading, SMA Partner. “The keys to success for insurers are improving data quality and data management, and creating a corporate culture based on management by analytics.”
“In-store analytics now rivals online analytics in its depth, reliability, and usefulness,” wrote CEO Alexei Agratchev in VentureBeat. Stores can see where shoppers go, where they linger, detect whether they are shopping alone or with friends or children, and match shopping to weather. By equipping staff with RFID chips, they can see if sales people are interacting with customers.
Tim Callan, chief marketing officer at RetailNext, said web sites have been using analytics since the mid-1990s. “But people who run brick and mortar stores have not had the technology to optimize their stores. They have relied on crude tools such as walking around the store to see what they think is working well, but they have not been able to optimize the way e-tailers could.”
The IDC’s latest big data report contains several new observations on the big data market, which the research firm says grew by almost 15 percent in 2011.
But as more machines take over the analytics and visualization, will the need for data scientists be minimized before it even really gets going as a career path?
Herscher ( CEO of FirstRain) thinks not. Noting the changes in BI that shook an industry over a decade ago, she recognizes the ongoing need for a human touch to analytics and doesn’t expect things to change this time around. Echoing much of the advice we’ve heard from proponents of big data like IBM, Herscher thinks that we in fact need more data science, and more students in the areas of math and science. The automation of data analysis and visualization has “made it easier to access and manage data,” Herscher says, “but it also developed a class of companies that build software and apps to manage this data.”
The Information Security Forum (ISF) has released a report that recommends proactive, preventative big data analytics for businesses that want to increase business agility, improve information security and reduce cyber risks.
The report claims that the importance of big data analytics has never been greater however few organisations recognise the benefits for information security.
Recent surveys show IT and business unit managers are more worried than eager about big data analytics– but those surveys are probably misleading, according to at least one expert.
A seminal study on big data by McKinsey and Co., for example, found that analysis of big data sets could enhance the productivity and competitiveness of many companies, save more than $300 billion in healthcare alone by increasing the industry’s efficiency, and help retailers increase profit margins by as much as 60%.
Another study, “The Future of Big Data” by the Pew Internet and American Life Project, reiterated the findings. It quoted Microsoft chief strategy officer Craig Mundie and Wal-Mart CIO Rollin Ford predicting that a “data-centered economy” in big data analysis will help both government and corporate organizations avoid big mistakes and waste by pointing out persistent errors in practice or belief.