IT departments in large organizations have a reputation for being conservative. Despite the successes and widespread deployment of projects like Linux, Apache and MySQL, it can still sometimes be difficult to get IT to accept and support open-source applications.
Daniel Viar had such an experience, and asked on the r-help mailing list, "How do I get my IT department to 'bless' R?":
I currently use R at work "under the radar", but there's a chance I could lose that access. I'd like to get our company to feel comfortable with open source and R in particular. Does anyone have any experience with their company's IT department and management that they would be willing to share?
The question prompted more than 30 replies with suggestions, which Daniel helpfully summarized in a followup post. Below, I've selected some of the best arguments and information you can use to convince IT not only to accept R, but to understand its many benefits compared to other statistical software and even, perchance, to love it.
R is mainstream.
R is "the de-facto standard" for statistical computing and is regularly cited in peer reviewed journals of Statistics.
R was featured in the New York Times in January 2009. According to the article, "Companies as diverse as Google, Pfizer, Merck, Bank of America, the InterContinental Hotels Group and Shell use it."
The R Foundation, a not-for-profit organization supporting the R project, receives financial support from dozens of organizations including AstraZeneca, AT&T, Baxter Healthcare, Black Mesa Capital, Boehringer Ingelheim, British Columbia Cancer Institute, Saxo Bank, and Schröder Investment Management.
R is supported.
Third-party vendors across the globe, such as REvolution Computing, offer enterprise-level support and training services for R.
R users report that the technical support offered by the R community (through forums, email lists, etc.) is comparable if not better than that provided by commercial products. For instance: "We have been evaluating various commercial packages (SAS, SPSS, S-PLUS) and so far have had better responses to getting technical questions answers on the R-help list than through the help desks of companies trying to sell us their software. As another example, last night I posted "How do I get my IT department to 'bless' R" and so far I have received 12 replies."
There are dozens of books and publications about R, with more published each year.
R is high quality.
R is a major open-source project, not some small piece of freeware developed by an individual.
There are currently over 19 individuals responsible for the maintaining the source of R. These individuals are arguably some of the most talented in the field of Statistical Computing.
R's world-class build processes and development model make it suitable for use in validated environments, including FDA clinical trials. REvolution Computing, an independent third-party vendor, provides services to validate the use of R in regulated environments.
R leads commercial packages in innovation.
R benefits from external innovation that makes it able to have quick reaction time to new statistical ideas. It is not uncommon for a cutting-edge statistical technique to appear first in R and then make its way into a commercial package.
High-performance distributions of R are leading the charge in the fields of high-performance computing and distributed cloud computing.
R is cost-effective.
R is open-source software licensed under the GPL. Unlike commercial software, your ability to use R cannot be revoked for any reason.
Subscriptions to commercial distributions of R are cost-effective compared to licenses to commercial software.
Graduates from statistics programs are routinely skilled in R, reducing training costs.
R requires no more support from IT than a similar statistics package (e.g. SAS).
Experienced R users report being able to accomplish tasks in much less time than with other statistics packages (such as SAS), reducing labor costs.
And more...
Got any other suggestions for getting IT to accept and love R? Let us know in the comments.
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