Analytics are for everyone! Well, not building analytics, no. That needs a high level of expertise in statistics, machine-learning, optimization, programming, database skills, a healthy does of domain knowledge for the problem being addressed and a pretty wide masochistic streak too. Using analytics, now that is for everyone, or at least it should be.
We all use analytics, and, I think, the best examples, we use without thinking about just how complex it is.
Is there anyone out there that hasn't used an electronic mapping service (GPS) for directions? Even ignoring the electronics, these are remarkable pieces of engineering! An extensive, detailed database of road systems and advanced routing analytics to help you find the best route from A to B without sending you backwards down one-way roads or across half-finished bridges.
Perhaps you're thinking it's not that hard? Could you build it? What if I got the data for you? No? But you can use it right? They are not perfect, mostly I think because of data cleanliness problems, but they are close enough that I don't travel far from home without one.
More examples. Anyone used a search engine? How about an on-line weather forecast? How about web-sites that predict house-values? Recommendation engines like those used by Amazon and Netflix? All heavy analytic cores wrapped in an easy to consume, highly usable front-end.
These are, I think, among the exceptions in analytic applications - good analytics AND good delivery.
I talked about pseudo-analytics in a recent post: shams with no basis in science wrapped in a User Interface with the hope that nobody asks too many questions about what's under the hood. This is not good analytics.
Unfortunately even good analytic tools get under-used if they have not been made accessible to the poor people that have to use them. Spreadsheet tools probably top the list for unusable analytic applications: unusable that is by anyone except the person that wrote them. Sadly though, I have seen many examples both in reporting and applications where so little effort was put in to User Experience that any good analytics is almost completely obscured.
Building new analytic capability is a highly skilled job. Delivering analytic results in an easy to consume format so that it gets used is also a highly skilled and, frankly, often forgotten step in the process. After all we do build analytic tools so that they get used. Don't we? Sometime I wonder.