That's a fair point and I have doubts if financial support would have a desired effect too. However, I think that in most cases the scientist is not forced to use one particular programming language as Python, R, SAS, MATLAB, Julia, Perl or something else. The problem is not that some particular tool is necessary or not. The problem is that PDL and other Perl modules are not known well enough as options and are not attractive enough for people that could use them. For example I only recently discovered that such thing as PDL exists and did not know this option before.
To summarize, I think that the need for usage of a particular programming language in data science is much more limited than its actual usage. The goal might be to make Perl a more attractive option not only for those who need it and cannot avoid it but also for those who do not need any particular option and are considering which of these to choose in order to achieve their goals.