Let there be no doubt, there are many reasons to advocate and use open-source software. What I care about in this post has nothing to do with open-source and closed-source software, but is about the value of using different statistical software in the same project. It may sound counter-intuitive, but research projects can benefit if different software packages are used to do the statistical analysis.
Why would this be the case? By doing the analysis in different software packages, we are forced to replicate the analysis, forced to think independently in terms of implementation and forced to understand. Obviously this could also be done by two teams working independently using the same software, but with different software packages there is no harm in sharing code. Having done the analysis twice, the influence of typos etc. that do not lead to errors or obviously wrong results will be spotted — leading to robust research results. At the same time, there will be fruitful discussions about methods, like whether the default values in a software package are the most useful ones for the particular problem at hand.