I have a confession: I am not very good at math. I know that will come as a terrible surprise and disappointment to some of you. You may even be astonished that SAS would hire someone who doesn't have a PhD in statistics. But math is not the only skill you need to make your analytic initiatives successful. You can be an Analytic Cheerleader!

Just because you're not a mathematician doesn't mean you can't be passionate about analytics – and as I’ll illustrate, there are opportunities for many different skillsets and roles. Early on in my career, I had the opportunity to build out my first business intelligence and analytics competency center at a large insurance company. Before I could get additional funding to build out my team, I needed to prove out the value of analytics before we could make additional investments.

SAS had just helped me install Enterprise Miner on our small server (there is a follow up anecdote that I call "Rachel, The Accidental SAS Server Administrator," that I may cover in a separate post), and while we were installing the technology that enables analytics, I lobbied the business to find a pilot project to prove out predictive modeling capabilities. I found a willing partner in our call center, who wanted to pilot predictive model triggering events in their call routing system. I took a couple of SAS's data mining classes and also hired a SAS statistical consultant as a mentor (I was lucky enough to work with Jay King, who now leads insurance R&D efforts in SAS's Advanced Analytic Lab).

It was very important to me to understand if this was a capability we could realistically develop and support in-house. I performed the data prep work and the modeling, and I would work with my mentor to ensure that I was making the correct assumptions. For those of you who have been following my posts, this is another perfect example of the importance of having a "SAS Buddy."

We implemented the model with great fanfare, and the success of this pilot led to several good outcomes:

1. I could leave the math behind and hire statisticians.
2. By actually doing the work myself, I really understood the process and the challenges.
3. I found my true calling in championing analytics in the organization.

After I built my team out, I found out how complementary these skills are. I'm going to generalize, but most statisticians prefer to spend their time on problem solving. An equally important skill is the ability to package the results up for consumption, make them explainable to senior leaders, and take those analytic success stories on the road, so to speak, within the organization. If analytics are new in your company, you will need to continuously educate and promote their value to your customers. Ultimately, we’re talking about putting a marketing and communications strategy around your analytic initiatives. Be a cheerleader!

Give me an "A"! Give me an "N"!!!!......