“Big Data” is all the rage in healthcare. Just about everyone dreams of what it would be like to take huge amounts of data, slice it, dice it, and turn it into something good … better patient outcomes, greater energy efficiencies, bigger cost savings and more.
But, unfortunately, much of the good that Big Data was supposed to deliver is still in the dream stage.
That’s because a lot of people are “doing” Big Data backwards. They are gathering data points on a wide variety of both clinical and non-clinical matters and then trying to mine it for something valuable.
Start by using Big Data to solve simple questions
Over ten years ago, when we started gathering millions of data points about beverages on hospital campuses, we had very specific questions in mind:
- What are hospital systems across the country paying for beverages, and
- How much lower would those costs be if hospital systems engaged in exclusive pouring rights agreements with either Pepsi or Coke (similar to exclusive agreements already in place for years at colleges, universities, arenas, restaurant chains, hotel chains, etc.)?
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By collecting detailed beverage information from individual hospital campuses year-after-year, we were able to develop local, regional and national beverage cost metrics and back-end beverage rebate metrics by brand, package and channel. We were able to then use that intelligence to save hospital systems millions through exclusive pouring agreements with either Pepsi or Coke.
Our work with Big Data has never been sexy, never high-profile. In fact, it has always been kind of nerdy.
But, we have returned more than $26 million in savings to hospital systems. We’re awfully proud of that figure.
How do we do it?
We have a proprietary beverage spend calculator in which we plug your bed count, type and number of facilities, employee count, and some other relevant data points. At the outset of our engagement, this calculator gives us an estimated savings figure that is very reliable.
Then we begin the process of collecting actual beverage invoices from all your facilities. This specific data is compared to our estimate and our Big Data metrics, which allows us to identify and investigate seeming abnormalities in pricing, volumes, brand share, product categories, etc.
At the end of the day, as long as your hospital system has four or more acute care hospitals, 1,200 or more staffed beds and 6,000 or more employees, we can most likely generate savings similar to the money we saved these hospital systems.
Put our Big Data to work for you. Contact us today and find out how.
