The potential of analytics
What if you lived in a world where there are no traffic jams, where heart attacks can be predicted months in advance, and where machines squeak their status before they break down? While this seems futuristic, this smart era could dawn on us sooner than we think if some of the pilot projects in predictive analytics succeed. Consider these projects in the US. Town planners in Los Angeles have built an Automated Traffic Surveillance & Control System. The system synchronizes 4,500 traffic signals across the region, and magnetic sensors in the road at every intersection send real-time updates about traffic flow. The system analyzes the data and automatically uses this analysis to predict where traffic is likely to snarl. With the new system, the average time to drive five miles in the city has been reduced from 20 minutes to 17.2 minutes.
Meanwhile, the National Institutes of Health is working with partners to develop an analytics system that can help doctors to detect heart problems years earlier. With enough lead-time, patients can make the required lifestyle changes and take the required medications to save their lives.
Then there’s GE Aviation, which is experimenting with predictive analytics to anticipate when a CNC machine— used to make airplane engine parts—is about to break down so that its staff can carry out preventive maintenance and avoid delaying the delivery of a finished engine.
Using analytics, healthcare organizations are even personalizing treatments for cancer patients based on their DNA.
Closer home, IT services firm Mindtree is using HR analytics to predict employee turnover for the next 90 days.
Over the next few years expect analytics to be far more pervasive and intelligent than it is now. IBM predicts that within the next five years our digital lives will be protected by ‘digital guardians’ who will constantly watch over our digital lives using cloud-based analytics to spot deviations and chances of fraud.
Gartner recently forecast that ‘your smartphone will be smarter than you by 2017.’ The research firm says that smartphones will soon be able to predict a consumer’s next move, his next purchase, or interpret actions based on what it knows. For instance, if there is heavy traffic, Gartner says that your smartphone will anticipate that you are likely to be late and accordingly wake you up early for making it in time for a meeting. This decision will be made using contextual information gathered from the calendar of the user, weatherrelated information and the user’s location.
This future is much closer than we think, and the use of analytics is limited only by our imagination.