The Big Problem With Big Data

What is big data’s big problem?

Too many companies think big data is one of two things; a big amount of data, or a really big number. It is neither of those.

Big data is a myth. A myth on which companies spend millions of dollars trying to convert big data into some form of information.

Big data; little information. ‘Big Data’ multiplied by ‘No Information’ equals no data.

And you can’t blame the data. It is inanimate.

Knowing how many people visited your website is not big data, it is counting. Two hundred people visited your website. Zero value added.

One thousand people liked you on Facebook. Cool. It’s almost as valuable as collecting US commemorative stamps. Only you can’t mail a letter with Facebook likes.

And so on and so forth.

For most companies, big data equals no data — at least no data that has any value.

Let’s look at a few companies that failed at using big data and those which succeeded. Does anyone remember MySpace? MySpace used to be a big deal. But then again, so did Sears. Firms that don’t know how to use big data had the half-life of a fruit-fly.

Facebook, that little start up, paid attention to big data. The adoption base of that little startup is connected to one of every two people on the planet.

And then there are Amazon, eBay, Netflix and LinkedIn.

If you belong to any of these sites, one thing will jump out at you. They know everything about you. They know what you did, and here’s the kicker — they know everything you may want to do next. Based on your prior behavior, Amazon recommends what book you may want to read, eBay recommends what product you may want to purchase next, and Netflix recommends what movies you may want to watch next. And, based on your prior connections, LinkedIn recommends who you may wish to connect with next.

One might infer that these sights are pretty prescient. They are not. These sites use Google Analytics to tell them, based on the behavior of their members, how to shape the next interactions of their members. They use data to determine what drove more adoption and what did not.

Amazon’s goal is not to sell you another book. eBay’s goal is not to get you to buy one more item. Netflix’s goal is not to get you to watch one more movie. And, LinkedIn’s goal is not to get you to connect to one more person.  The goal of each of these firms is to get their site to be your daily go-to site for everything they do.

They grow and maintain membership and adoption by making it valuable for their users to use their sites as often as possible.

This approach works in every industry except healthcare. Healthcare has lots of data about its patients. It has no data about its prospective patients. It knows nothing about the behavior of its prospective patients — its consumers — and it knows very little about the behavior of its patients.

It could. But it doesn’t.

It knows how many people go to its websites. It does not know if those people are patients, it does not know why those people went to those websites, or what they hoped to do. It does not know what they wanted to do when they used the app. It does not know what would make them come back to their websites or apps. It does not know how to shape their behaviors, or how to create value for their visitors. And worst of all, it does not have a clue how many prospective patients tried to access them using some form of digital media.

It could. But it doesn’t. Why bother having a digital presence that has no value?

Suppose a new patient goes to your website to schedule an appointment. They go and they leave because there was nothing to do.

But what if it worked like this. You could track the number of people who found your website through Yelp or Facebook. Then you could track what percentage of those people created a patient profile (since they are not in the EMR), how many of the people who created a profile searched for a doctor and scheduled an appointment, what type of appointment they scheduled, and what percentage of those people made it to their appointment. And you could track, by service, what the revenues were for those people.

If you did that, you would know where new patients came from. You would know if they set up a profile and scheduled an appointment, and you would know the revenues they generated. You would capture all kinds of data about prospective patients, and you could tie it to you legacy systems, systems like the EMR and billing and marketing. You would know about patient acquisition and retention.

You could, but you don’t. Instead, you rely on erecting billboards, advertising on NPR, and having a dysfunctional call center. Do you know what it costs to acquire a patient? Of course not. Do you know what services new patients buy? Of course not. Do you know what revenues new patients generate? Of course not.

Google Analytics and an integrated analytics platform would allow you to know all that. Those tools would give you free external data about all your consumers.

Google, Amazon, eBay, Netflix, and LinkedIn know how many people used their service. They know what made people use their services more frequently. They know what they did to shape behaviors that worked and what did not work. Using analytics, they change their platforms in real time to improve their ability to change the behavior of their users.

Search on the analytics for these firms and then search on the analytics for your firm. The number of hits differs by orders of magnitude. If 10,000 people go to your website, what do you have to show for it? If 10,000 people go to Amazon, Amazon knows to the penny the value of each of those visits. The same with eBay and Netflix.  They also know how many times those people went to their site each week, and they have a good idea how to increase that number week after week.

Healthcare can shape consumer behavior. Having the ability to do something and doing something are different things. Dorothy had the ability to go back to Kansas, she just didn’t know how to do it.

What healthcare needs is not more big data. It does not need a data warehouse. It needs a way to capture external data and marry it to internal data to shape and modify patient and consumer behavior.

It can do all of this by using a simple platform that collects external data and analyses it against its internal data.

Think of Uber. What does it know from its analytics? It has the most data of any firm on the planet about individual driving patterns and more data about who wants to go where and how often.

Healthcare does not even know how many new visitors went to their websites. Had those people created new profiles that would open the door to millions of pieces of big data that here-to fore did not exist.

That solution exists.

[This piece was originally published on Paul Roemer’s blog, Disrupting Patient Access & Experience. To follow him on Twitter, click here.]