Analytics make sense of data

Dogma is for dogs. And so who cares how we define "analytic"?  When we (at GE) recently shared of our work with a Canadian hospital executive he said: "you guys are ahead of anything we've seen in analytics."  We showed the same work to a consulting executive in Ireland and he said:  "Cool. But these aren't analytics."

Is analytic synonymous with analysis? Is an analytic advanced analysis? Is it persi
stent analysis? Is it business intelligence? Are there four levels of analytic maturity… or five?

Who cares?

We agree.

Nonetheless at GE we are, more and more every year, investing in "analytics" to help our clients. Every situation is different and so a common definition has not been important.

For some the focus is real-time; for others predictive or proscriptive. Here and there the focus is even retrospective (a four letter word?). The work ranges from strategic planning with discrete event simulation, to forensic analysis of patient flow, to less-is-more action-oriented decision-support using predicted trigger conditions... (Bored yet?).

So, no dogma.  But we do like simple statements:

1.  Analytics make sense of data.No point stressing over a better definition. 

The important bit is what problems are we facing and can our data help? If so, let's make sense of it in the most appropriate way. (We don't know who first said this. If it was you, let us know and we'll give credit).

1.  Analytics best built one question at a time.

A deceptively powerful statement. I first heard it from Chris Larkin and we've applied it in seven countries since. For example:  which medically-appropriate discharge is the most urgent to support tomorrow's anticipated ED arrivals, OR schedule, radiology schedule and their impact on critical care units and ED boarding?

Ooh. That's a good question.

How to make sense of it?