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Lately, the marketing engines of several large statistical software companies have been hard at work trying to spread fear and desperately convince businesses why they should not switch to R – a free, open-source statistical computing technology that is taking the financial, healthcare, insurance, and other industries by storm.

Given our experience with both proprietary technologies like SAS, and the open-source competitor R, we wanted to unveil the other side of the coin that the major software firms don’t want people to see.  Below are 5 reasons to be concerned if your company is using licensed data and statistical computing software.

1. If you miss a renewal bill payment, all your work may… stop working.

Picture spending 2, 5, or 10 years developing on a language that is licensed annually.  Now imagine one day, you log into your workstation, only to find that all of the programs you have written suddenly stopped working!  This is a very true story and a risk companies face everyday when paying to license a software language. What happens if one day, your company runs into some troubled times and cannot afford to pay tens of thousands (perhaps hundreds of thousands) of dollars to renew a license for the software.  You are pretty much stuck.

2. Unexpected Licensing Cost Jumps

When a company develops using a licensed statistical computing technology, particularly one that requires annual renewal fees for continued use, the company has forced itself into a position where it needs to continue to pay these licensing fees in order to continue using what it built.  I’ve seen many cases where paying these fees becomes a lifeline for a company.  Particularly in cases where there has been vast development on top of a licensed language, the company’s only way of surviving may be to pay these fees.  What would happen if this “survival fee” were to jump 10%, 20% or 60% in a given year (the latter is what Netflix did to its customers according to Bloomberg)?  Can you afford to risk your existence on uncertain, increasing future licensing costs?

On this point, I know some may argue that this happens all the time in business; for example, a company may license a database system.  However, there is a big difference here.  In cases of database platforms, servers, routers, word processing programs, and other technologies, the technology is not serving as a critical building block.  Sure there is the cost of setup and training.  However, it would not be inconceivable for a company to replace one of these resources.  This is not the same as a statistical computing platform.  Once an organization begins developing in a particular language, it becomes a part of their DNA.  Everything that gets built and all the intellectual property that is brought into existence is now contingent of paying licensing fees.  Replacing an arm or a leg may be doable, but replacing a company’s DNA would be a substantial challenge.

3. Mergers and Acquisitions

In the field of data technologies, vendors are changing all the time, and the seniority of the vendor is little assurance of its future stability.  For example, SPSS, a 40-year-old-plus statistical computing vendor whose software was initially released in 1968, was acquired in 2007 by IBM.   While this may not seem like a big deal, such changes can be particularly worrisome in the field of statistical computing.  If you own a car and the auto manufacturer was to be acquired, perhaps the greatest question a current owner might face is whether his warranty would still be honored.  However, the implications of such a merger in statistical computing are far more troubling.  If you develop in a particular computing language that requires licensing, there is no telling what level of support a new owner for your recently-acquired vendor might provide you – if any.  It’s like building a house on a piece of land that is owned and traded by someone else.  The worst part is that you have no say in how the land is traded!

4. Bankruptcies

Major corporations that have shaped the world we live in are going out of business.  Boston Scientific and Eastman Kodak are just two examples of technology companies that are in risk of bankruptcy in the near future according to the Business Insider.   What would happen if the vendor of our statistical computing software that is at the root of our company development were to find themselves in financially-troubling times?  Is there any guarantee that the engine that drives our company will still be able to run tomorrow?

5. Limits Business Expansion and Scalability

A major challenge I’ve encountered with clients who use proprietary statistical computing software is difficulty they encounter when they want to put their developed products or services online and/or connect them with other technologies.  While the technology may be available to make this expansion possible, expect to pay an arm and a leg for it (possibly taken from item 2 above).  Particularly hard-hit are companies that wish to get paid to crunch other people’s data.  Generally, this capability falls under special licensing provisions that may be so pricey as to make any CEO/CTO keel over.  I’d estimate that 30% of the clients I’ve worked with have run into this issue, causing them to either abandon their expansion plans or to use a different technology (such as R) to make it possible.

In summary, the next time you hear a statistical computing vendor talk down about the risks of open-source technologies like R,  be sure to consider what the vendor is not telling you.

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