Predictive analytics is the practice of analyzing past and present data to predict a future outcome. Today, every industry from insurance and finance to healthcare and child services uses neural networking, machine learning, and artificial intelligence to build predictive models to solve complex problems and support better and faster business decisions.
While the benefits of predictive analytics are open to all companies, implementing this technology requires a complete cultural and ideological shift. Predictive analytics is not just capital investment in tools and processes; it requires workforce training from the ground up.
Before deciding if implementing a predictive analytics solution is right for your business, it is crucial to understand the technologies, its use cases, and how predictive analytics firms use Big Data to forecast the future.
Predictive analytics is so pervasive because it offers many benefits. With it, organizations can:
Identify trends and patterns
Make strategic decisions
Predictive analytics has almost infinite applications. When a potential homebuyer applies for a loan, for instance, the mortgage company needs to know if the buyer will make payments on time. Predictive analytics can help calculate the odds to reduce risk and adjust premiums accordingly. When it comes to shopping, retailers want to know what their customers will buy next and what will drive sales. With predictive analytics, producers can forecast everything from upcoming sales to potential product shortages, thereby reducing strain on the supply chain.
According to a study by market research firm Aberdeen, companies that used predictive analytics to better address their customers’ wants and needs increased revenue by 21% year over year. But predictive analytics does not just help businesses make money. Predictive analytics companies also help flag potentially dangerous scenarios in healthcare, weather, social services, and more.
The prevalence of predictive analytics has surged across all industries. It can be used to catch fraudulent activity, help companies get a leg up on the competition, and even save lives. Here are a few ways that predictive analytics is being used to transform industries:
Florida’s Hillsborough County used predictive analytics services to improve child welfare. By analyzing state historical data about neglect and abuse, a data software company developed predictive models to flag high-risk cases. Child welfare officials then reviewed these cases and acted upon those predicted to result in serious injuries or death. As a result, Hillsborough County has seen a significant decline in abuse-related deaths.
The University of Chicago Medical Center (UCMC) used predictive analytics to reduce operating room delays, saving the hospital an estimated $600,000 per year. By combining real-time data with complex algorithms, UCMC was also able to improve workflows, streamline room handoffs, and reduce patient complications.
With predictive analytics, insurers can use historical data to accurately reflect a customer’s risk level by identifying elements that traditional methods may have missed. This approach builds trust and can help boost customer loyalty, leading to higher retention rates over time. For insurers, machine learning engines can also improve loss ratios, raise profitability, better predict risk, and therefore adjust pricing premiums accordingly.
Using a predictive algorithm derived from electronic health records, health system Kaiser Permanente flagged high-risk cases and discovered that the top one percent of flagged patients were more likely to commit suicide. With this finding, Kaiser showed how predictive analytics could save lives by identifying urgent cases and spurring preventative actions.
Thanks to predictive analytics, weather forecasting has improved immensely over the last few decades. Satellites orbiting the Earth feed data back down, enabling meteorologists to predict hurricane tracks three days out and issue blizzard warnings several days in advance. As a result, people in affected areas get alerts about severe weather much sooner than in the past, and have more time to evacuate or seek shelter.
Predictive analytics companies use a variety of technologies and techniques to make predictions that aid all sorts of industries. And the practice is only growing. According to Transparency Market Research, the global predictive analytics market will be worth $6.5 billion by the end of 2019, up from $2 billion in 2012. Another study by the Markets and Markets Research Group predicts the market will reach $12.4 billion by 2022.
The segments most likely to partner with predictive analytics firms are finance and risk, sales and marketing, customer and channel, and operations and workforce. And as predictive analytics consultants and companies find more uses for big data, the practice will expand further.
Interested in predictive analytics but not sure how to get started? Our predictive analytics consultants are experts in data mining, statistical analysis, machine learning, advanced analytics, and predictive modeling among other techniques and tools.
We have helped clients of all sizes implement effective strategies by discovering patterns in data that help forecast the future and align the business with these predictions.
Not confident in your digital maturity? The Trianz team will be there every step of the way to reduce your skills gaps and help you make better business decisions, deliver superior customer experiences, streamline operations, reduce risks, and gain insights into market trends.
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