Predictive Analytic Evolution of R

Have had a number of talks with industry leader about R and its potential. At least they have heard of it now, but are still nervous about how it fits into their needs, except in the most specialized of circumstances.  And how does it interact with common software solutions they already have?  Key questions for the promotion of analytics.   Information Management explores its evolution.

" .. R, the open source programming language for statistics and graphics, has now become established in academic computing and holds significant potential for businesses struggling to fill the analytics skills gap. The software industry has picked up on this potential, and the majority of business intelligence and analytics players have added an R-oriented strategy to their portfolio. In this context, it is relevant to look at some of the problems that R addresses and some of the challenges to its adoption.... " 

Decisions, Data and Predictive Models: Conversations

Letting Data be Your Compass:  by Rob F. Walker. Nicely thought out piece on data, decisions and predictive models. Using the word prediction brings your models directly into the decision making process.  I always emphasize this in engagements.

I like in particular how he says prediction is not stand-alone, but relates to a conversation:  " ... What is required is a next-best action, real-time decision making that inserts itself in the conversation every single time something changes: when the customer is acting, reacting, or getting upset. Any such change should cause a re-evaluation of the state of the conversation, and possibly a change of tack ... " 

I use the notion of establishing a story line to a decision interaction, and mapping it out that way in early interviews.   Stories modified then modify decisions using data.

Advanced Maths Win Wall Street

A view of what used to be called 'rocket scientists' in Wall Street.  I recall going to the Santa Fe Institute and hearing a talk about this phenomenon,  just before the crash.   Now its math, big data and analytics.  Its not that I do not believe in these methods, I just look at the predictive value with caution.  Note something new here, the use of forward-looking, unstructured data analysis to look for causal triggers.    As opposed to quant forecasting.

On Predictive Analytics

This piece makes the point that I often do ... that all analytics, all business decisions, are predictive. The word 'predictive'  includes the implication that the result may be imprecise, or even wrong. How do we manage that?