Tapping the potential of predictive analytics
- By Thom Rubel
- May 23, 2014
With every business decision comes the need to plan, implement and evaluate so that its overall value can be calculated. But what if government agencies could shorten that process by using existing data to predict people's needs and better understand behaviors?
Using data to make predictive decisions is not a new trend by any means, but it is something that governments can use to be more efficient. McKinsey and Co. considers the Internet of Things to be one of the most important disruptive technologies that will transform our lives. The Internet of Everything (as Cisco labeled it) will involve billions of devices connected via the Internet -- sensing, generating data, responding and providing opportunities that are ripe for innovations that will transform individual lives and business operations.
When applying predictive analytics in government, there are plenty of scenarios in which data should be made more useful to support more effective decision-making. By using current and historical data, we can predict trends that can improve program performance and operational efficiency. 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.). Predictive decision-making ensures that the right combinations of information come together based on business rules that optimize desired outcomes -- think smooth traffic flows.
Real-time situational awareness is a powerful new tool that can create high-performance programs operating on a solid foundation of continuous effective decision-making. However, there are obstacles to overcome. When dealing with data to gain insights, the obvious challenge is how to make sense of the massive data flow. And once that is decided, we must ensure that the technology is highly scalable.
Eventually, traditional government business processes will be replaced -- or deeply aided -- by a system of Internet-of-Things devices. Those devices will have society's regulations and values deeply embedded so that they participate in a "societal mediation process" as conflicts arise. Devices will be able to analyze data to observe behavior and adapt their actions accordingly to influence our compliance with the rules and/or regulations embedded in them. It's not too difficult to envision a world in which cars won't let users speed or will stop working if a driver lacks a valid license and insurance. Those rules could be based on any widely accepted policy that society defines.
By using current and historical data, we can predict trends that can improve program performance and operational efficiency.
Likewise, government agencies run multiple programs designed to make individuals economically successful, such as job placement services, training, family services, transportation, etc. Are government agencies getting the benefit of intuitive success scenarios to make those programs operate to their full potential based on what they can learn from existing and expanding data sources?
Increasingly, that network will include a wide range of elements, such as biometric and health-monitoring devices, sensors on mobile devices and buildings, food products, cars, utilities, animals, the houses we live in -- it really will be the Internet of Everything. In the next decade, digitally enabled things will generate more Internet traffic than people do, and the growth will only continue from there. Data will not just be something we look to for information; it will be a part of our everyday lives and the basis for making critical decisions -- many of which we will never even know were made.
Agencies need to be laying the foundation now to ensure that they capture and maximize the value that the Internet of Things will bring.
Thom Rubel is the public sector business line leader at Pegasystems.