Six skills for predictive analytics

Today, I participated in a webinar with Actuate on the skills needed for business analysts to perform predictive modeling.  This is a hot topic and there were hundreds of participants on the call.  In my part of the presentation, I outlined some major trends in predictive analytics (including the fact that the tools are much easier to use) as well as six different skills which I thought were important for business analysts building predictive models.  I grouped them into two buckets.  One was the skills needed to frame a problem.  The other group were the skills needed to explain/defend analysis.  These skills were:

• Critical thinking
• Domain expertise
• Data sense
• Understanding the tools
• Some level of understanding of the techniques
• Storytelling ability

I’m sure there are more than these six.  However, what was interesting was that we got a lot of questions from the audience around these skills –  thinking that the message of the webinar was that you don’t need to be quantitative to perform predictive analytics. We got questions about overfitting and other technical considerations in predictive analytics.  I think some people thought that we were advocating the complete dumbing down of predictive analytics and that anyone off the street could build a predictive model.

My point in the Q&A around this was as follows:  Statisticians and data scientists are a scarce resource.  I believe that there are some kinds of predictive analytics that business analysts can perform, hence freeing up the big guns for the more complex work.  I still think that business analysts should be trained in the tools and techniques so they can use them to their fullest and be able to defend their analysis.

Any thoughts?  To hear more about these skills and predictive analytics, register for the webinar to view the archived version!