A recent question on one of the LinkedIn groups about the advantages of using R over commercial tools like SAS or IBM SPSS Modeller drew lots of comments for R. We like R a lot and we use it extensively, but I also wanted to balance the discussion. R is great, but looking at commercial organizations near the end of 2011 it is not necessarily the right choice to make.

Background

We have created and managed analytics teams in commercial organizations (mainly telecommunications) across Europe. The teams were using SAS or SPSS. Our company now has a commercial analytics as a service offering and we mainly use R.

The benefits of R is productivity. We want to spend time on the actions from the analytical insights, not the coding, and we choose our tool accordingly. Being a consulting type organization it is easier for us to attract and retain talent.

The advantages of SAS/SPSS in a commercial environment

1. You can buy the tool for money.

Big corporations have procurement departments who do not have a process for free software. Also software spend goes on the balance sheet in a way that the CFO prefers to people but something like R will take a little talent to set up initally. (And yes, we know the Revolutions guys well, but they are not really credible in Europe yet.)

This will change as (a) companies become more mature in their procurement and as (b) commercial support for R improves. (On the latter point, Oracle’s R integration to the database is great news.)

2. You can recruit for the commercial tool

1. Recruiters are familiar with SAS and SPSS but not with R so it is easier to brief them and to get good quality CVs. This will change and R becomes ever more popular and prevalent. [And yes, we could in theory change recruiters to someone clued in, but again in large corporations there are procurement processes to be followed and existing agreements to be honoured so it will all take months or years.]

2. There are recognised training programmes for SPSS and (especially) SAS which makes it easier to recruit the technical skills. How do you know what somebody knows when they say they “know R”? How do you even begin to quantify it from a CV? How do you separate the guy who downloaded the tool and just read “An Introduction to R” from the Frank Harrells of this world?

   Yes, I would argue (and in fact have argued in Commercial Analytics: The Capabilities) that technical skill is not the most important in an analyst (and can be learned anyhow) but it does help filter the CVs and, you guessed it, fits well with the corporation’s processes.

   (One reason we use R internally is that we find that it is, on average, a more interesting type of analyst who is proficient in that tool. It seems to encourage curiosity and love or learning in a way that menu-based tools do not.)

   I think the commercial R companies are really missing a trick here to provide recognised certification.

3. You can’t search for R. Seriously: try searching for R on LinkedIn (tip: there is another way). Much easier to find SAS / SPSS skills in a large CV database (like LinkedIn where this discussion started).

3. You can recruit for the commercial tool.

Yes I know I already said that but there is another reason why this is critical.

R takes talent to use. (That is kind of why we like it.) It takes talent to maintain.

My problem as the manager of a commercial analytical insights team is that it is very hard for me to retain that talent. Think about it: what can I offer in terms of career progression? If you are an analyst you might become a senior analyst but you will always be an analyst. There are no examples of a way up the organization (except perhaps out through IT and then up to CIO). [This too will change with time.] And new challenges: yes, some, but we are not a research university and it tends to be the same few problem types that we are always working on. So if you are an analyst looking for new challenges and more pay, the best thing – the logical and rational thing to do – is to get a new job. And your time with Big Corporation will look good on your CV and you will probably land the job easily.

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