Predictive analytics is, without a doubt, one of the most promising technologies to emerge in recent years. By leveraging these solutions, organizations in a wide range of fields can make better informed, more strategic decisions in just about every area of business.
This applies not only to the private sector, but the public as well. As FCW contributor Thom Rubel recently reported, predictive analytics is poised to deliver major improvements to government agencies. However, for this to occur, a concerted effort to embrace the technology is essential.
Rubel noted that there are a number of areas where governmental use of available data combined with predictive analytics could yield powerful results.
"For example, programs that are collectively designed to ensure the smooth flow of people and commerce are typically informed by multiple data sources generated by people or things (sensors, data networks, etc.)," Rubel wrote. "Predictive decision-making ensures that the right combinations of information come together based on business rules that optimize desired outcomes – think smooth traffic flows."
By embracing predictive analytics technology, the government could see its operational efficiency rise significantly.
However, as Rubel pointed out, there are serious challenges which must be overcome first. Put simply, the government needs to make progress in terms of making sense of its massive volume of available data and also ensure that the technologies used for predictive analytics can scale up and down as needed.
Part of the reason this is such a challenge is that, as a general rule, the government struggles to attract and retain the level of IT talent necessary to develop and implement such advanced technological solutions. Numerous reports have noted that up-and-coming IT experts typically veer toward the private sector because the incentives to join the government are just not competitive. Government agencies do not afford these personnel the level of freedom they require to innovate new solutions, including advanced analytics efforts. This makes it difficult for the government to take advantage of this and other technological progress.
Yet despite this and other obstacles, Rubel believes that the government will eventually utilize predictive analytics to a wide degree. Specifically, he forecast the Internet of Things will integrate with predictive analytics and government programs to deliver more sophisticated, effective governance. As the use of analytics for critical decision making grows, it becomes more important for organizations to rely on proven and robust algorithms to deliver results that can be trusted.
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