The need for businesses to embrace predictive analytics
Have you ever wondered how Netflix seems to know exactly what to recommend in your queue? Thank ‘predictive analytics’ for those smart recommendations. And, you do not have to be a media giant like Netflix to take advantage of this technology.
When organizations want to make data-driven predictions about future events, they rely on predictive analytics. It is sometimes lauded as a crystal ball, guiding companies away from business risks, unknown future events and behaviors, and towards newer business opportunities.
Driven by the explosion of big data, predictive analytics is fast becoming an important part of many industries and functions. Using predictive analytics, enterprises can harness the power of data to provide the business with a more fact-based vision of where to aim and how to get there.
Many organizations across sectors are turning to predictive analytics to increase their bottom line and competitive advantage. Some of the most common uses include:
Healthcare: In healthcare, models connecting symptoms and treatments to outcomes are seeing wider use by providers. For example, a model can predict the likelihood that a patient presenting a certain set of symptoms is actually suffering a heart attack, helping staff determine treatment and urgency.
Customer behavior: Predictive analytics are used to determine customer responses or purchases, as well as promote cross-sell opportunities. Online retailers are using tons of data they gather on the behavior of their customers to adjust their prices respective to what will appeal to their clients the most.
Preventing cyber threats: Combining multiple analytics methods can improve pattern detection and prevent criminal behavior. Gathering information on past attacks and identifying a digital fingerprint to prevent future infiltrations is emerging as an effective way to prevent data breaches.
Improving operations: Predictive analytics is enabling companies to function more efficiently. Some businesses have benefitted from predictive models by forecasting inventory and managing resources. Airlines use predictive analytics to set ticket prices. Hotels try to predict the number of guests for any given night to maximize occupancy and increase revenue.
An incredible amount of predictive analysis can be done on whatever type of data businesses have. As enterprises traverse this path they can be assured to uncover more opportunities for analysis that will lead to the collection and integration of more and more data over time.
For enterprises embarking on this journey, one thing is for certain, they will be using their data to drive decision making, and that glimpse into the future will reap some very real rewards.