The Data Myth

I love data. I am a self-professed data geek. If you know me, you know I measure my time at work, my time working out, my time learning, and even sleeping! I know that I spend 31% of my life sleeping (which makes me think – how can I get by with sleeping less?)

Yet, we see that data is not the end all, be-all. We all have data at our fingertips for almost anything in our lives. The problem is, as we all know, we have too much data and it’s not organized the way we need to see it to make decisions. Further, data can have holes and inconsistencies that the machine doesn’t realize it has. A machine always “thinks” it is perfect. That’s fine. The issue arises if we, as people, think the machine is perfect (hint: it ain’t, and it never will be!).

Then what’s the value of data and how do we get it and use it appropriately? Mobile Aspects is largely a data company providing great solutions to gather more data in hospital surgery. We ask this question every day in our Company. We have landed on two keys, that are startlingly simple to discuss, and often difficult to implement.

The first is: can you ask the question in a way your team can gather the data? Healthcare is too much abuzz with the words “Big data.” If you google around, you will see this means nothing. In fact, there are many articles discussing how hospitals have a big data initiative, and many are not making progress. This is because they need to start with a fundamental question – what exactly, specifically are they trying to do?

Then from there, we need to be involved in the design process to work with our teams. Otherwise, team members will come back with data overload, and frustration builds. In fact, as much of an “expert” that I think I am (“please, Suneil” says the World), I find most times in discussions with hospital executives and team members, I am in the position of providing the data overload. I have not parsed and made sense of data before giving analysis to our hospital partners – I just do not have the understanding oftentimes.

What I have found works well internally at Mobile Aspects, and working with our hospital partners, is to gather requirements and then set expectations that initial data sets will feel imprecise and often not make sense. This is just an initial filtering process. Really what is happening is the executive has years and years of expertise and knows exactly what they want, and then we try to distill this in a 45 minute meeting. It doesn’t work. It requires patience, knowing that the team is working for you, and will require a few sequences of back and forth. That’s ok! You are getting what you need, and you are setting yourself up for a better experience next time.

The second is: data requires a qualitative, human review with experts along with it. You may have paid $1billion for the systems you have in place. The unfortunate truth, there is a lot of holes in your data, and a lot of garbage. This is because people still often need to enter baseline level data and begin processes – and its hard and a lot of work. Therefore, ask your teams to look for things that don’t make sense and try to correct it before bringing it to you (and be patient when you find something in the first minute of the data review – believe me, you will).

Data analyses is hard work, and very important work. They require constant reviews to make sure data is being gathered and analyzed properly. Asking the question in a precise way, working with your teams on design, and then being patient as you go through various revolutions of data review are the key to success. If you can get into this mode, it will save your hospital six and seven figures in your analyses. It’s hard. It’s important. It’s worth it.