[R] Entire Organization Switching from SAS to R - Any experience?

[Frank E Harrell Jr]

I differ with Marc in one way.  It is amazing what people can learn when 
  you create an emergency for them to do so.

Frank


Marc Schwartz wrote:
> On Jul 17, 2009, at 9:57 AM, Kelvin Lam wrote:
> 
>>
>> I should elaborate the situation a bit more.  We store our data in 
>> UNIX and
>> have been using UNIX SAS for our work.  My Biostat dept has 40 SAS users
>> from which at most 10 also use R.  The Epi/Grad Students/Investigators
>> combine for another 30-40 not-so-frequent SAS users let alone R.  So 
>> we are
>> talking about 80 folks/workhorses in the entire institute.
>>
>> One of my thoughts is to break up the Biostat group into two so that one
>> uses R solely to reduce the number of licences.   IMHO, the pro is to 
>> worry
>> a smaller group of users.  However, the cons will be who to be 
>> assigned to
>> respective group.
> 
> You have several business, human behavior and budgetary issues to 
> consider. It is not usually just a matter of making the business case 
> that saving annual license costs is the sole factor in making a decision 
> to switch to R.
> 
> You have to consider the receptivity of the existing base of SAS users 
> to changing to R. Are they open to it or are they not motivated to 
> change? In the latter case, is the organization in a position of forcing 
> change or not? Being a non-profit organization, you can simply say, due 
> to funding issues, we are going to have to eliminate some 'x' number of 
> SAS licenses to stay within our operating budget. That will have an 
> impact on how many users can in fact continue to use SAS.
> 
> However, if you compel wholesale change, are you at risk of losing 
> people who are resistant and decide to move on? Are they key people 
> where their loss would have substantive impact on the organization and 
> project commitments, at least in the short term? Yes, on one level, we 
> can all be replaced by somebody else, but at what short term cost to the 
> organization and it's customers?
> 
> If there is resistance amongst some proportion of the staff, an 
> incremental approach would be very appropriate. Balance your funding 
> issues with the number of staff that would be impacted in the near term. 
> Can you eliminate 'x' SAS licenses this year, 'y' more next year and so 
> on so that the transition is implemented over a multi year time frame 
> while still working within your funding constraints?
> 
> Solicit feedback from the staff to see who is open to using R and who is 
> not. Let that be a key factor in any decisions to partition the staff. 
> Get an idea as to the scale of the battle that you are facing with 
> respect to change. Identify the "low hanging fruit" to look for 
> incremental and consistent wins that you can build on. Those who are 
> resistant to R may simply need time to see that what they have done in 
> SAS can indeed be done in R with greater quality, speed, flexibility and 
> in time, at a lower cost. Once they get over that hurdle, they may come 
> on board with you and make subsequent transitions easier.
> 
> With an eye towards the future, be sure that new hires are skilled in R, 
> so that as you may need to deal with staff turnover or growth, you are 
> enabling the future use of R by a growing number of folks who have 
> pre-existing R skills. Set yourself up for future success.
> 
> Consider R related training and the costs associated with it. The costs 
> are not just what you may have to pay for training, but the opportunity 
> costs in the short term of getting people up to speed and the loss of 
> productivity short term, even though as Frank noted, you will realize 
> notable gains in the long term. Consider how your existing project 
> commitments would be impacted and how you may have to allocate or 
> re-allocate the workload during the transition.
> 
> Consider the costs and timelines associated with converting an existing 
> base of SAS code that has perhaps gone through a review and validation 
> process. What will it take to replicate that functionality in R with the 
> same level of reliability? What methodological issues will you face in 
> the transition from SAS to R, given the differing philosophies? How long 
> will it take, who will do it and what other tasks or projects may be 
> impacted during the transition?
> 
> In some environments (eg. Big Pharma), re-training and especially code 
> conversion/validation costs alone outweigh the savings of not paying for 
> SAS licenses. This is why there is a significant hurdle to using R in 
> that environment even though such companies may pay SAS millions of 
> dollars per year.
> 
> I don't know that there is a one size fits all approach to moving from 
> SAS to R. Each operating environment has its own characteristics 
> relative to budgets, politics, people and so forth. The points that I 
> raise above may be typical but only some may apply to your situation and 
> there may be others that I have not raised.
> 
> HTH,
> 
> Marc Schwartz
> 
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-- 
Frank E Harrell Jr   Professor and Chair           School of Medicine
                      Department of Biostatistics   Vanderbilt University