Predictive data analytics is just like it sounds – advanced analytics techniques that are capable of making predictions about future unknown events. Mainly, these analytics techniques rely on statistical algorithms and machine learning to provide the best assessment of what is most likely to happen in the future. In a little more depth, there’s a wide range of technologies that make predictive analytics possible. Aside from what was already mentioned, big data, data mining, and other aspects of artificial intelligence play a part.
A diverse array of industries is awakening to or is already leveraging the power of predictive data analytics. To name a few, banking and finance, utilities like oil, gas, and electric, retail, government, manufacturing, and the list goes on. The list of possible uses for advanced predictive analytics continues to grow day by day. A few trending applications include:
Fraud Detection – Improved pattern detection and the addition of behavioral analytics (amongst other methods) can help spot abnormalities and prevent fraudulent behavior faster and more effectively.
More Effective Marketing – Advanced predictive analytics can help businesses attract, retain, and grow their most profitable customers and determine which marketing campaigns, channels, touches, behaviors, and demographics are contributing to a specific business outcome.
Improved Operations – Efficiency gains across industries can be realized through better forecasting of the factors impacting their business, from general inventory and resource figures to more particular instances like a hotel being able to maximize occupancy through prediction of the number of guests for a given night.
Reduced Risk – Risk management, from cybersecurity to brand and reputation, and even the weather and terrorism, is being transformed by predictive analytics and is allowing companies to better plan for and mitigate these risks.
Better Healthcare – One area that has really put big data predictive analytics to use is healthcare. The challenges will not be easy, but the benefits will be far greater – from more tailored, more effective care to reduced insurance fraud and better prevention of suicide or reducing appointment no-shows.
The refinement of real-time predictive analytics really takes these process improvements to the next level, like hospitals piloting the real-time identification of infection warning signs in hospital patients. Another great example where every second counts, is credit card fraud. Here, the ability to identify fraudulent activity instantaneously during an attempted transaction is crucial. “Real-time” can also extend to predictions that need to be made in minutes or even hours or days. Customer service response can be shaped in real-time to meet the circumstances of a given call, or predictive maintenance can prevent the failure of a piece of equipment.
So, no matter what industry you hail from, there’s a path forward that harnesses the power of predictive data analytics. Imagine the value you have to gain, whether incremental or an obvious step change, through the implementation of a solid predictive analytics program.
Syntelli has been working hard to help companies realize these benefits and is excited for the future of these techniques.
