Global Pragmatica LLC®

I didn’t arrive at running an analytics and management consultancy by a straightforward path. I started out as a musician, getting degrees in horn performance and music history (and, oh yeah, math) and pursuing a career as principal horn of a major symphony orchestra. A Rottweiler bite along the way derailed me from my auditioning and freelancing track, and that’s when I started paying more attention to my Plan B career, where I was about to start my third and fourth roles in statistical software, as a tech writer and localization project manager for Abacus Concepts (makers of StatView, SuperANOVA, and MacSpin) in Berkeley, California, after my first two as a tech writer and then QA manager for SYSTAT (makers of SYSTAT, SYGRAPH, FASTAT, MYSTAT, and a bunch of specialized companion products like EzPATH and Mesosaur) in Evanston, Illinois.

When Abacus Concepts was acquired by SAS (makers of JMP and… duh… SAS) in Cary, North Carolina, a dozen of us were hired on at SAS. Initially I worked as the StatView product manager, which was kind of an odd sidestep for someone who’d always been in R&D, but I had writing and graphic design experience and was a good all-arounder, so it worked. Then I transitioned into yet another tech writing role, this time writing a brand new book about a brand new still-in-development feature in JMP 4 called the “JMP Scripting Language,” now more commonly known as JSL, because we digit-miners like three-letter abbreviations.

That role was really just a stopgap to use my skills while JMP R&D was finishing up its version 4 release, after which I began the role that they actually wanted me for, building up a localization program for a product that had never been translated and adapted for international markets before. I went from there into facilitative leadership and R&D program management, with side dishes of business management and sales/marketing management mostly by accident. And then I detoured yet again into content management/change management consulting, and as a result of that an in-house senior management position at Dolby Labs.

But 35+ years later, I’m still recognized as an expert in JMP Scripting Language, and custom statistical software development for Fortune 100 companies now makes up the bulk of Global Pragmatica® LLC’s revenue. And my goofy background in pretty much every role imaginable within tech companies, combined with early training and experience in leadership and management as a principal horn player, has amounted to this: I’m an all-arounder—and that’s probably why I “get” what my clients really need when they come to me asking at first for something pretty specific that soon turns out to be just the tip of the iceberg for the potential of JMP to drive innovation, quality improvements, and ultimately profits at their companies.

Go figure.

Mine is not a career path any sensible guidance counselor or career development coach would have designed! Maybe while dreaming. Or smoking crack?

But it’s worked out well for me. I’m one of those unusual people who doesn’t fear change. I thrive on change. It’s stasis that I can’t stand. Loving a variety of challenges that keep changing works out well in consulting. (And suddenly moving from a major coastal city to a small town in Montana. And adding a puppy to the office staff.)

My odd resume has also created perhaps the strangest niche offering of all the offerings at Global Pragmatica® LLC: StatView file conversion.

You see, not too long after SAS acquired StatView acquired JMP, it rolled most of StatView’s better ideas into JMP, converted most of its users to JMP, and then closed down StatView. StatView and JMP just weren’t different enough in mission or design to justify continuing two separate development tracks.

Since you can’t buy StatView anymore, and to my knowledge you can’t find StatView installers anymore even on those software-piracy sites that nobody in their right mind would ever get products from (hint: you’re also installing viruses and spyware if you do), and the now-ancient Mac versions won’t even run on modern Mac hardware, that creates a problem for researchers who are building on the long-ago work of researchers who used StatView and saved all their data and analyses in the now-defunct StatView file formats. It’s been quite a while since even JMP has supported StatView file import.

So every so often, someone in this predicament of trying to excavate ancient buried StatView data treasure will google themselves to me and Global Pragmatica. You don’t have to google StatView for very long before you find a review praising my documentation, or an old copy of a paper I wrote about applying Edward Tufte’s lessons from the Challenger disaster to better data analysis in StatView, or something like that. And somehow of all the people’s names you might run across when googling SYSTAT or StatView, mine is one of the few still in the stats software business.

And it just so happens I still have a handful of legit, properly licensed versions of StatView for Windows that will still run on a Windows 7 virtual machine that I keep around for testing JMP addins when I have a customer who’s still running Windows XP or 7. I also have a virtual machine that emulates an old PowerPC Macintosh running OS 9, with a copy of StatView 5.0 running on that, so I can also often rescue Mac StatView datasets and viewsets.

I’m not absolutely sure that this is a unique offering in the world, but to the best of my knowledge, Global Pragmatica is the only business in the world that offers StatView data conversion services.

But here’s the thing. It doesn’t take any particular talent to open data files in an old program and resave them in a newer file format. It doesn’t even take much time, once I’ve remembered where my StatView executables are. So I don’t feel right charging for this service. (I mean, sure, if someone comes along with gigabytes of StatView files, the complete lack of an automation option means that I will not be having any fun spending the next few days clicking buttons to rescue their data. I’ll feel just fine about charging them for doing that, and I guess I’ll catch up on a few podcasts while I’m at it.)

So here’s the policy I’ve arrived at: I do StatView data conversion as a pro bono service, where you tell me how much it’s worth to you and a charitable cause that you think we can both get behind, and once we reach agreement, you donate that amount to them, and Global Pragmatica® matches that donation to them, too.

StatView data conversion services have benefited the Humane Society in several cities, the Cat Town rescue café of Oakland, the Watson Children’s Shelter in Missoula, Wellbeing of Women in the United Kingdom, Planned Parenthood, Doctors Without Borders (US), Australia’s Foundation for National Parks & Wildlife, Montana Wildlife Federation, and I think I’m forgetting a few others.

Sound fair to you? Got data trapped in StatView? Get in touch.

I might be able to help with SYSTAT data, too, if someone needs that (even though SYSTAT is still a thing).

Statisticians and data analysts are in a kerfuffle about the recent remarks of AnnMaria De Mars, Ph.D. (President of The Julia Group and a SAS Global Forum attendee) in her blog that the open source statistical analysis tool R is an “epic fail,” or to put it in Twitterese, #epicfail:

I know that R is free and I am actually a Unix fan and think Open Source software is a great idea. However, for me personally and for most users, both individual and organizational, the much greater cost of software is the time it takes to install it, maintain it, learn it and document it. On that, R is an epic fail.

And oh, how the hashtags and comments and teeth-gnashing began!

Nathan Yau’s excellent FlowingData blog recaps the kerfuffle nicely, and his post has accumulated a thoughtful comments thread, as has Dr. De Mars’, to both of which I added my thoughts, expanded here:

To make my prejudices clear, I’ve spent several decades in commercial statistical software development (working in a variety of R&D roles at SYSTAT, StatView, JMP, SAS, and Predictum, and I now do custom JMP scripting, etc., for Global Pragmatica LLC.

I can say with hard-won authority that:

– good statistical software development is difficult and expensive
– good quality assurance is more difficult and expensive
– designing a good graphical user interface is difficult, and expensive
– a good GUI is worthwhile, because the easier it is to try more things, the more things you will try, &
– creative insight is worth a lot more than programming skill

Even commercial software tends to be under-supported, and I’ll be the first to admit that my own programming is as buggy as anybody else’s, but if I’m making life-and-death or world-changing decisions, I want to be sure that I’m not the only one who’s looked at my code, tested border cases, considered the implications of missing values, controlled for underflow and overflow errors, done smart things with floating point fuzziness, and generally thought about any given problem in a few more directions than I have. I want to know that when serious bugs are discovered, the knowledge will be disseminated and somebody’s job is on the line to fix them.

For all these reasons, I temper my sincere enthusiasm about the wide open frontiers of open source products like R with a conservative appreciation for software that has a big company’s reputation and future riding on its accuracy, and preferably a big company that has been in the business long enough to develop the paranoia that drives a fierce QA program.

R is great for what it is, as long as you bear in mind what it isn’t. Your own R code or R code that you find sitting around is only as good as your commitment to testing and understanding of thorny computational gotchas.

I share the apparently-common opinion that R’s interface leaves a lot to be desired. Confidentiality agreements prevent me from confirming or denying the rumors about JMP 9 interfacing with R, but I will say that if they turn out to be true, both products would benefit from it. JMP, like any commercial product, improves when it faces stiff competition and attends to it, and R, like most open source products, could use a better front end.

And now let me make my case for R being an epic success.

I like open source software. I use a bunch of it, and I do what I can for the cause (which isn’t much more than evangelism, unfortunately). For me, the biggest win with open source software is that it makes tools available to me, and others, who don’t need them enough to justify much of a price, but who can benefit from them when they’re affordable or free. When an open source tool gets something done for me, or eases some pain at least, I’m not that picky about its interface, and I’m willing to do my own validation (where applicable).

I can’t say that I love using Linux, but as a long-time UNIX geek and Mac OS X bigot, I am glad Linux is available, I use it for certain things, and I think it’s a whole lot better than Windows and other OSes, especially when Ubuntu builds work out. (I’ve had trouble getting JMP for Linux installed on Ubuntu, but that’s probably due to my own incompetence.) OpenOffice is kind of a pain, but it’s better than paying Microsoft for the privilege of enduring the epic fail that is Office, and it has much better support than Office for import/export of other formats. I love it that any number of open source projects are developing such fabulous tools as bzr version control, which I use daily, and that the FINK project is porting a whole bunch of great open source UNIX widgets to Mac OS X.

I think it’s wonderful that some of the world’s greatest analytical minds are using R to create publicly available routines for power-analysts. I love it that students and people who can’t afford commercial stats software, or who won’t use it enough to justify buying a license, have a high-quality open source option, if they’re willing to work at it a bit. I think it’s great that people who think Excel is good enough can’t make a price objection to upgrading to R.

I believe that democratizing innovation and proliferating analytical competence are good for us all. I count on projects like R and Linux to push commercial developers to make better products, and to force pricing and licensing of those products to remain reasonable. Monopolies are good for nobody, including monopolists.

Long live the proponents of R!

What do you think? Do you trust open source stats code? Do you think R’s interface is good enough? Is JMP’s any better? How heavily do you factor quality of documentation into decisions about software?