SAS is on the brink of…something.

Never underestimate the power of analyst relations. Each year, SAS invites industry analysts to a posh resort and shows them shiny things that most SAS users will never see. Steamboat Springs used to be the destination; this year, the Ritz-Carlton in Naples, Florida got the nod. Naples is so much nicer in February. The broiled branzino served in the Terrazza, though pricey, is tasty and fresh.

As night follows day, in the weeks that follow the event, analysts publish their reports about SAS. This year, Tony Baer writes that SAS “is on the brink of generation change.”

With the accession of Dr. Oliver Schabenberger from chief of research, product development, and most recently, CTO, to the post of COO (reporting only to Dr. Goodnight), SAS has completed a changing of the guard that began three years ago.

In other words, with Jim Davis’ departure.

With Dr. Schabenberger, SAS has promoted a product researcher with deep academic background (like Dr. Goodnight) to head product development, sales, and operations.

Readers ask me what I think about Schabenberger. I have no opinion. He may be the next Andy Grove, for all I know. I would simply note that everyone thought Jim Davis and Carl Farrell were heirs apparent until they weren’t.

SAS characterizes the newly created COO slot as a plan to “expand” the management team.

That’s nice. But SAS should consider focusing on quality rather than quantity. A management team consisting exclusively of SAS “lifers” lacks the diversity and depth to make smart moves.

In any case, executive succession is less important at this point than ownership succession. Goodnight and his wife own 80% of the company. Unless he has secretly donated his equity to a charitable trust, a sale of the company seems almost inevitable.

The challenge for SAS is that a market where it had unquestioned dominance for the lion’s share of the last 40 years is now getting quite crowded.

Do tell.

With (the) emergence of Viya over the past couple years, SAS smartly concluded that its value add was not in the SAS programming language…With Viya, SAS chose to coexist with the open source environment. Develop in R or Python, use a Jupyter notebook to compose and share your models, but at runtime, send them to Viya where the models run in SAS’s Cloud Analytic Services (CAS) in-memory engine.

Wait. Stop. This is just plain wrong. Viya has client APIs for Java, Lua, Python, and R. This does not mean that you can run Java, Lua, Python, and R code inside Viya.  It means that you can invoke SAS code from those languages.

That’s an important difference. Viya does not run Python; it runs SAS. You can connect to it from Python, run SAS commands, and use the Viya result set in a Python program. That’s fine. But if you want to write code that runs in Viya, you’re going to write SAS code.

Pro tip for analysts: read the manual.

SAS has a firm hold on its Global 2000 enterprise base, which isn’t going away anytime soon.

I wouldn’t be so sanguine. In fact, the most consistent message one hears from G2000 CDOs is “we want to reduce our SAS footprint.”

  • A top US bank has a project underway to convert its risk models from SAS to Python and Spark.
  • A leading US insurer (a “charter” SAS customer dating back to 1976) has migrated more than a hundred SAS users to open data science tools.
  • A multinational health information company (and SAS “reference” customer) expects to have a thousand analysts working with open source tools — most of them converts from SAS.
  • A trillion-dollar asset management company plans to convert most of its SAS user base to open data science tools
  • In the UK, a large government agency has reduced its SAS user headcount by half, all displaced by open data science tools.

The CDO of a Canadian bank wrings his hands in frustration over what he describes as “a $20 million SAS bill.” Right now, he thinks he’s stuck. How loyal will he be once he sees a way to reduce that number?

Two-thirds of recent growth in spending on machine learning software went to new vendors, according to IDC. Innovation drives the machine learning market. Vendor loyalty is dead.

But it is challenged to compete for the hearts and minds of the next generation of data scientists, data engineers, and business analysts who have become empowered by self-service and drawn in by open source.

To say the least. New grads entering the workforce universally favor Python and R over SAS. Organizations that still use SAS send new data scientists off to training, or set up a parallel open data science infrastructure.

This is one reason one shouldn’t count on SAS to hold on to those Global 2000 customers. Surveys show that SAS users skew significantly older than R or Python users. Many large organizations expect SAS headcount to decline, while R and Python headcount grows. Some are more aggressive about pushing for change, but for the rest, it’s only a matter of time.

There are ways for SAS to get cool again. We recall several years back, flying to a conference (actually, it was SAS), where we found ourselves sitting next to a high school senior who was on his way to UT Austin to check out their data science program. Self-taught, he was already proficient in R and Python, but preferred SAS because of the full-featured analytics environment. That’s the scenario that SAS wants to replicate.

Self-taught high school seniors proficient in Python who prefer SAS are as common as twentysomething women of color living on the Upper West Side who prefer Trump.

As for open source, as mentioned above, SAS interoperates with it, mostly through Viya. However, dealing the lack of perception about SAS and ML, SAS should start contributing to open source.

What, exactly, can SAS contribute to open source? To do so, a vendor has to either (a) distribute open source software, or (b) build something in open source software. SAS does neither. The company would have to donate the SAS Programming Language to open source or rebuild its end-user products on TensorFlow or Spark.

Hell will feature ice skating before either one of those things happens. Open sourcing the SAS Programming Language would gut 80% of SAS’ revenue. The dairy farm and rock collection would definitely have to go.

Viya is SAS’ fifth attempt to deliver a scalable platform. It’s possible that SAS has finally nailed it; I know of at least one customer that uses the software, and they seem happy with it.

But customers don’t seem to be voting with their pocketbooks. SAS launched Viya in 2016, and it was generally available for all of 2017. In a market growing at double digits, SAS barely managed 1% revenue growth in 2017. If customers bought Viya, they pulled the plug on legacy SAS rather than expanding the footprint.

Even if SAS can sell Viya as a departmental application, it’s not the enterprise machine learning platform of the future. That will be open source or hybrid open source. Commercial software will sit on top of the stack supporting the last mile to the end user with accessible user interfaces and business solutions. Think DataRobot on top of Python, R, XGBoost, and H2O; StreamSets on top of Spark, Kudu, Solr, and Drill; or Dataiku and Kogentix on top of Hadoop.

SAS has conceived an architecture that is upside down, with a commercial platform on the bottom and open source tooling for end users on the top. Few large organizations will adopt that architecture. It’s too expensive, inflexible, and subject to vendor lock-in.

But in the spa at the Naples Ritz-Carlton, you can purchase a Drift to Sleep massage for $245. And at $60, the dry-aged rib-eye available in The Grill is a bargain.


  • But Thomas, you’re just a mean “hater”. Dr. G. is a really nice person and a great leader. He recognizes talent and promotes it from within. That’s what makes him such a great leader and SAS such a great company to work for! Dr. G. recognized the talent in Dr. S. and why he’ll take SAS into the future.

    In fact, Dr. S. is just like Dr. G in many ways. He is tall, slender, and has a Ph.D in some Statistics-related area. He’s straight talking, and doesn’t mince too many words, just like Dr. G. Dr. S. believes in life long learning, and has already taken great steps to move SAS into the future. Last year was just a tough year, that’s all. But like a good Forester, Dr. S. has worked hard to till our soil and pull the weeds so that a bright new crop of Millennials can showcase the shine and polish of the new Viya platform!

    Just wait, Thomas. You’ll have to eat your words. Those institutions haven’t seen the power of Viya like Drs. G. and S. have. If Drs. G. and S. say that Viya is the future, then I believe them! Once our customers see the awesome power of Viya, the sales pipeline will be miles long! Just you wait and see, Thomas!

    SAS is such a great company! I’m looking forward to another 40 years of working here under the direction of Drs. G. and S! They are the greatest!

  • Gee, if you dig sarcasm, I would propose that in your role you are a much appreciated and completely unbiased and objective source of information!

    Fair disclosure on my own biases, I’ve been in the “data-something-or-other” line-of-work for a good 30 years, the last 3 very happily at SAS (the Kool-Aid is indeed quite tasty!).

    Anyway. fair enough, I liked your post, but struggle somewhat to parse the opinionated vitriol and rhetorical jabs from fact-based assertions here. Thus, a few mollifying observations to add icing to the dog-food layer cake put before me…

    For starters, SAS Base is not the core business – SAS solutions include packaged solutions addressing, among other things, ETL, data quality, Hadoop management & integration, high-speed data ingestion, bundled specialty suites (i.e. ops research, simulation, risk model management, ML model management, text analytics), in-memory analytics, and enterprise integration.

    As well, there are packaged industry analytics solutions for IoT, smart grids, fraud detection, cybersecurity, financial risk management, regulatory compliance/monitoring (i.e. GDPR, AML, Solvency II), etc. Beyond this, SAS code is validated and hardened to serve strict regulated industries and environments, for instance government, defense, pharma, and other GMP manufacturing.

    is an FDA-regulated biotech company REALLY going to control quality for GMP fermentation operations based on an R module some nutty professor in New Zealand patched together on some random weekend while schnockered on sherry? Yeah, no…

    In essence, SAS delivers on all those bits and pieces and requirements that are either overlooked, poorly formed, or completely missing from open-source solution stacks.

    Indeed, I really struggle to recall a single end-to-end open source stack project that produced lasting value on-time and within-budget, or even, for that matter, which has fully achieved the goals it set-out to solve. Journeying through the vast graveyard of open source vanity projects I come in on as a mop-up-agent on in any given month, one espies a dystopian wasteland of ruined towers and battered factories strung together with bubble-gum and tape.

    Anyway, I’ll step off the tired soapbox now. it was an amusing piece and I appreciate it and take it in the Japanese context that “our competitors do us the honor of showing us how to improve”! Keep them coming!

    • Scott,

      Hello. Hope all’s well in Amsterdam. Lovely city, really — I was there just a few months ago. Great pancakes. Love the canals. The bicyclists can kill you, though.

      As a rule, when SAS employees complain about vitriol, they actually mean “uncomfortable truths.”

      A few comments:

      “SAS Base is not the core business” — yeah, it is. Among customers surveyed by Gartner for its most recent MQ, two-thirds use Base, STAT, and Enterprise Guide only. The percentage is higher among actual users. SAS University’s most popular course remains Programming 1.

      “As well, there are packaged industry analytics solutions…” — yes, SAS offers solutions, as do most of the larger vendors in the market. Not sure how this matters. SAS revenue is flat as a pancake.

      “is an FDA-regulated biotech company REALLY going to…? — the FDA itself uses R. Big Pharma invests heavily in open data science, so don’t kid yourself. Genentech, one of your former employers, has a strong commitment to open source.

      “I really struggle to recall a single end-to-end open source stack project that produced lasting value on-time and within-budget, or even, for that matter, which has fully achieved the goals it set-out to solve.” — if that’s the case, you aren’t looking very hard. Deloitte, your former employer, bets big on open source.

      I sincerely hope that your job with SAS Cybersecurity is secure. Looking through this list of the top 500 vendors for cybersecurity, I can’t seem to find SAS..

    • Dotdotdotdashdashdashdotdotdot

      SAS seems to have lost touch with customers. Decisions made for good of SAS instead of for good of customers. Software touted as cool but arrives to market late. And sells sluggishly. Going in wrong diection on Fortune Best Place to Work ranking: 15th to 37th in just one year, ouch. Employees at work one day and gone the next. With no announcement….just gone. Seems that the ability to communicate has atrophied. Who is steering the ship, do they care, and are they even awake? Once great now merely good, please do something better.

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  • came to see what British Special Air Service was up to, left disappointed. maybe define SAS in the intro

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  • ‘Self-taught high school seniors proficient in Python who prefer SAS are as common as twentysomething women of color living on the Upper West Side who prefer Trump.’ Ahhh that had me in stitches… is also so very true! As an R/Python Data Science Manager who was dragged kicking and screaming into a governmental SAS platform for 3 years in the last job I could not agree more with this article. We got there, but it was expensive and it was difficult to find junior staff with the skills to work in the platform, which means more time and money training them.

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  • Googled “sas market share” to find out how the old dinosaur is doing – I owe my career to two, SAS and Matlab – found your post, and very much enjoyed it, thank you.

  • Thank you for writing this article, I’m an analytics manager for a large company who has a mixed environment including some SAS. You say “Vendor loyalty is dead” and to that I say “Nay-Nay!” In my experience SAS users are loyal… Very, very loyal; they don’t explore other technologies and never consider any alternatives. I confess we all have our favorites and maybe that’s all it is, but when looking at all that the industry offers I figure one of two things:

    –I’m not experienced enough to recognize SAS’ genius, or
    –SAS is the emperor with no clothes

    I’m open to either one of those but I can certainly admire how a company has managed to have such a loyal user base.

    • Max,

      Thanks for reading, and for your comment.

      Yes, I agree that there are many users and organizations that are loyal to SAS. However, I’m struck by the number of organizations that used to be completely committed to SAS and are now looking at other options.

      There is also an age and generational divide. Older SAS users tend to resist switching; young data scientists entering the workforce overwhelmingly prefer Python or R. That reality forces most organizations to implement SAS and open data science side by side.

      In my personal experience, the best analysts aren’t tied to any one set of software tools.

      — Thomas

      • Hi Thomas , very late indeed to the conversation but have found everything very interesting a still relevant. Having spend over 25 years using SAS in financial services I am now witnessing a change , but a change I’m struggling with. The move to open source and the capability it brings technically out performs SAS, just look at what Facebook have released in terms of forecasting code, SAS just can’t compete. Now the true issue which you have all missed, organisations will over the X years spend millions on converting complex legacy SAS code to Python, R etc especially when it comes to ETL processing , never mind the complexities in managing code versioning and release management The alternative is to use WPS which provides a true open source integration workflow at significantly reduced cost, while catering fir future proofing of data scientist requirements.

        I would appreciate your thoughts

      • WPS appears to have prevailed over SAS in UK courts. However, SAS continues to litigate successfully against WPS in the US. If you have US operations, proceed with caution; SAS has also sued WPS customers.

  • Base on my observation, the article understating the problem SAS has been facing. I had been a long term SAS user (>12years) in the Banking industry. I used SAS exclusively for model development. However, things start to change since few years ago. Due to high costs associated with SAS and the broad data science movement, banks started the process to migrate away from SAS. Not just one bank is doing it, as stated in the article, but ‘ALL’ banks I know are doing it. You name it: BOA, JPM, WF… Some just started, some has been doing it for few years already. It is an industry scale shift. They are all migrating to Python platform. I completed my migration last year. I no longer use SAS for model development, unfortunetly. SAS might already feel some pressure but the acutal impact to the revenue might come few years later after Banks complete the migration. SAS is a great company, but the future is dull…

  • I know this article is close to 3 years old now but interested to know your thoughts on Oliver Schabenberger leaving SAS now

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