“Sometimes the questions are complicated and the answers are simple.”
Now that we have that out of the way lets talk about what happing with data and analytics right now. Basically, in a nutshell it is hot, and everyone wants data, even if they don’t know it. As a result the buzz words and phrases are out with force.
“Big Data”, “Predictive Analytics”, “Democratization of Data”, “Visualizations”, “Gamification of BI”…
So I have been in the space for like 20 years and at this point I need a translator. But let me take a pass what all this means.
There are boat loads of data and I want it to be crazy simple for me to consume, with the goal of making faster and better decisions.
OK, that can make sense to me, and I am pretty sure that is what most end users of BI and Analytics want. To be clear I am not taking about analysts or data scientists or report authors. I am talking about the executives, line managers, road warriors, store managers, and more who are the people that need this data so they can make those quick decisions.
So what does this have to do with consumer apps? Well it seems to me that the consumer app providers have already solved this and now the enterprise needs to catch up. Lets look at a few simple examples.
Weather data is complex and there is a ton of it, also people are addicted to weather information, and for good reason. It helps them make some great decisions throughout their day or week.
“Should I wear a jacket?”
“Should I bring an umbrella?”
“ What about sunblock today?”
Talk about predictive!
So lets look at some weather data. Here is a sample of Quality Controlled Local Climatological Data (QCLCD) from one airport. This is a tiny fraction of what can be accessed for a single location.
There is no way I am going to comb through this on a daily basis to find out if I need a jacket or not. So consumer apps take all the complexity out of this and eliminate the need for me to do any exploration or the need for an ‘author’.
With an app in a few easy swipes or taps I get all the info I need am more. It is easy to read and the information I need to make my decisions are clear. This one is Yahoo! Weather and there are many other great options. (This one is my favorite because it is simple and beautiful.)
So lets think about my translation of all those buzz words. Clearly we are dealing with a lots of complex data but it is given to me in a simple clear way that allows me to make every day analytic decisions.
That makes sense.
Lets take a look at one more consumer craze, there are a bunch of great examples but fitness is one the resonates with me. Talk about another hot market. I am told that sitting is the new smoking and consumer purchase in this space are re-enforcing this. Just do a search on “Activity Monitors” and it will be clear that this is a hot consumer trend. The market is saturated.
One key point to the success and adoption of this is the data and analytics. So to simplify, here is how it works, the tracker (the thing you wear or your phone) collects the data and some app or site reports the data. It varies but it can collect everything, including steps, stairs, heart rate, location, sleep patterns, and more. Wow, we generate a ton of data! In fact here is an article on putting FitBit data in R. If you are not sure what that means then you are an end user, and you really don’t care about the how. That is a good thing!
The app is where the magic happens, all this data is presented to the user in a way that is simple and easily actionable. Things like:
You walked 9,000 steps and that is short of your daily goal.
You are ranked 5th among you friends today.
You woke up 6 times last night and compared to last week that is up 10%.
As a user you can easily translate all of these into actions like get off your butt, or stop with the Red Bull at 9pm.
There are more great examples of this but I would have to go on forever. Take a look at apps like Google Now, Human, Fitly, Strava and more.
Hmmm, maybe everyone is a consumer of BI??