Over the last two decades, the U.S. has been plagued with high rates of prescription drug overdose. About 142 American citizens die every day from drug overdoses, many of which are caused by prescription medications obtained legally. Additionally, the number of opioids prescribed as of 2015 is three times as high as the number of prescriptions given out in 1999. Due to these staggering statistics, doctors and data scientists are working towards using predictive analytics to reduce the number of prescription drug overdoses.
In 2018, the national per capita healthcare expenditure in the U.S. is projected to be about $11,193. This number has been steadily growing over the years. What’s most alarming about this figure is that it’s double what other ‘rich’ countries are spending per person. Surprisingly, this high expenditure does not come with better health outcomes and hospital revenues have plateaued.
With supply chains becoming larger and more complex, it is becoming more difficult to improve service through a reduced order-cycle time while enhancing inventory availability and reducing operating costs at the same time. Big data is revolutionizing the optimization of supply chain and inventory management by improving visibility. It is telling a compelling story that is making leaders listen. Companies that have adopted predictive analysis see up to a 50% reduction in non-performing inventory and a 25% reduction in inventory holding costs, thus freeing up working capital.
Have you ever gotten caught up on Facebook clicking one after another on the videos and articles it throws up on your page? Or possibly on Amazon where you end up buying something you didn’t even know you needed 10 minutes ago? Many online sites are using predictive analysis to target and retain customers by creating personalized content for them.
Despite the introduction of more secure chip technology, credit card fraud is still one of the biggest concerns of banks and credit card companies. After all, fraudsters continually change their tactics to get around any security measures that are put in place. A recent Nilson report projects that global total loss due to credit card scams and fraud will be a whopping $32.96 billion by 2021. Many financial companies are now looking at predictive analysis to see if they can depress these numbers.
James and his friends at college love traveling. They travel at least once a year, and they love fast cars. Predictive analysis can tell us they would be interested in car insurance of about $700 a year and that they respond better to instant messaging. If you have never heard of James before, this process can seem like magic. However, predictive analysis is what is helping to make this magic happen and is providing a competitive edge to insurance companies. It is fast-tracking processes right through the value chain of marketing, underwriting, pricing, claims and everything else in between.
Big data, bioinformatics, predictive analytics or genomic medicine are all buzzwords that get tossed around often. It is true that more data is generated every day than we can possibly assimilate, but predictive analysis is what helps us to use this data appropriately. It, in fact, is no stranger to health care and has been used in many breakthroughs through the years, one among them being the Human Genome Project. This example changed sequencing from a manual to an automated process and saved time, money and increased accuracy – and that’s predictive analytics benefits in a nutshell.
Traditionally, the apparel retail industry has consisted of customers going into stores, trying on clothing, and then deciding whether or not to buy. However, now that people frequently buy apparel online, businesses are leveraging the power of predictive analytics (PA) to improve their customer conversion rates and reduce returns. Machine learning, predictive modeling and data analysis are the backbone of PA technology, which uses historical shopping data to help businesses make well-informed decisions.
When you think about the travel and hospitality industry, what often comes to mind are personalized experiences and breathtaking locations. It takes a lot of planning and research to make these experiences happen. Wouldn’t it be easier to have intelligently interpreted data help? Because the hotel and hospitality industry interacts with millions of customers each day and keeps track of these transactions, this data is readily available. Using this information to meet guest expectations makes the difference between a returning customer and a lost opportunity. Read More
The big American dream: Owning your home, financial success and wealth building – all in that order. For many Americans, their biggest investment will be the home they buy. This means that a successful investment in real estate for a home, rental property or land can be a future pot of gold. With Big Data and Predictive Analysis, the risk that was part of real estate investment has been greatly reduced. Real estate agents and brokers can derive the greatest value from these calculations since they offer a competitive edge to their clients, helping them to make a more informed decision. Read More