The state of North Carolina has 2 million medicaid patients and pays out $12 billion in Medicaid each year. Due to these high numbers, in 2010 governor Beverly Purdue announced a program to analyze medicaid claims. To do this, IBM was asked to step in to aid with healthcare analytics tools.
Since using the IBM Healthcare analytics there has been a 90% reduction in medicaid fraud. This software allows healthcare providers to see the patterns in medicaid claims and identify faulty claims against true claims. The great part about the use of Big Data analytics is that the IBM software can take the data collected from medicaid claims and put it into a visual format that is easy to understand. This allows for doctors and nurses to identify the fraudulent claims rather that rely on data scientists.
The use of big data analytics in the healthcare system not only aids in picking out the patterns that discover fraud, but it is also showing the population that there are people watching them and that they will be caught.
Thanks to Big Data analytics the state of North Carolina has decreased the rate of medicaid fraud and continues to search for those who dare to commit it.
If someone handed you a shovel and asked you to dig a hole, who would get credit for the hole? Did the shovel create the hole? No, you did, the shovel was a tool that allowed you to dig the hole more efficiently.
Many people believe that big data is the key to making money, and it is….just not necessarily in the way you may think. Instead of starting up your own Big Data company to make the big bucks, try using Big data instead. Companies who use Big Data to make more informed decisions are the ones who succeed, companies who produce Big Data software are the ones who get passed up by the newest model.
Don’t be a tool, be the person who uses the tool.
Back to the shovel analogy, your job is to dig a hole and though the shovel seems like your best friend in that moment, what if someone handed you an excavator? Now you can dig holes three times the size, all while sitting down! Even though the shovel seemed better than digging with your hands, the excavator now does the work for you. Businesses are the brains and Big Data is the tool, as long as the brains know what they are doing, the tool aids them wonderfully.
This is where the trouble comes in, even if you have a fancy complex program that does all the work, it still isn’t saving the business money if they don’t know how to run it. Many Big Data applications have made their money by providing a product that then requires a hired team of experts to manage it.
The way to make money in Big Data is to produce an application that is simple enough for the average business’s IT team to handle. The way to save money is to implement these applications into your business to gain much needed insight that allows the company to be more efficient and make smarter decisions.
The successful businesses are the ones who have figured out how to use Big Data to set themselves apart, rather than let it steal the spotlight.
Let us know what you think, is Big Data just a tool or are Big Data companies worthy of a higher name?
Often times when the next big thing hits the market, people jump into it without careful consideration. Don’t be the company that dumps all your money on Big Data without first knowing how to use it. These three steps describe how to use Big Data smartly, allowing it to make you money.
Test and Learn
Make sure your IT team includes someone who’s responsible for testing your Big Data Model. Use the Test and Learn strategy to conduct quick, cheap tests frequently. This will enable you to expose variability, uncover needs and ultimately improve overall performance with fast insights.
Manage Data Processing Wisely
Those who have been successful in the Big Data industry are the ones who are most clever about how their data is processes Knowing how to ask the right questions allows data models to process and store the data more efficiently. When possible apply low cost methods to first, using cheap IT tools to fun queries.
Use New Data Types
Integrating new types of relevant data allows for more dynamic information. Companies who rely only on internal data collected will outperformed by companies who include other factors such as weather or traffic. The more relevant data collected, the better the information which allows us to analyze and make decisions more accurately.
Interested in how these methods save companies money? Learn More!
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