Thread regarding SAS Institute layoffs

"Montessori" (attitude) - I'll get around to it (or do it) when I feel like it. Don't hold me to standardized timelines. Leave me alone so that I can explore/play.

"montessori"?

Isn't this supposed to be a good thing (teaching)?

a_good_perspective <- c("The Power Broker", "Robert Caro", "1975", "Rating = 4.7")

sas_belief_structure <- c("omnipotent", "insular", "montessori")

"they failed to build a modern architecture compatible with their products"

That is the single largest reason explaining the rapidly increasing slide of SAS down the slopes of irrelevance. The name for that is Viya.

A fairy tale for the business school case study:

1. Once upon a time... a business promoted people whose main qualification was their ability to say “yes”.

2. As a result, they failed to transition from building Tools to building Solutions…


3. …and they failed to treat Open Source as a competitor, until it was too late…


4. …and they failed to build a modern architecture compatible with their products.


5. Former employees on TheLayoff recommended a salvage operation. But for a successful IPO, it was better to sell Viya as it stood.

6. They IPO’d 100% of the company, and lived happily ever after 😊.

@cdxl+1qk7UpRX cont.

By 2005, the phenomena of a micromanaged R&D acting primarily as a software manufacturing concern that added new features and products every year or two, is not inconsistent with the maturation of SAS’ then business model. By that time, annual revenue was approaching $2B. Seems like SAS significantly sacrificed the opportunity to not only remain relevant, but also capture the next wave of computing in favor of building products on top of an existing architecture that was already aging — all while adding employees to support the ever-bloating old paradigm.

This was shortsighted and resulted in adding R&D staff who would never be adequate to the task of moving the company forward to new computing paradigms.

@cubl+1qk7UpRX

Your comments FTW!

SAS, by ~2005 largely abandoned the kind of deep first principles R&D that made our software so highly optimized and successful across the range of host platforms in the 90’s and early 2000’s. The talent and drive of so many in the developer proletariat was redirected under the thumbs of a micromanaged hierarchy, led by a handful of mostly non-stellar VPs and Directors who consumed the majority of travel $$, went to most of the conferences and basically told the rest us what to do. All kinds of cr-p was hacked together in an attempt to make another $10M to $50 per year, while a clear, innovative and realistic architectural vision got blurry by the year. Lots of mediocre hiring to acquire testing (based on the updated QA) and other support staff thought to be necessary to keep the software manufacturing machine rolling along — all the while creating more bloat and enabling an aging srcman/build/test tool infrastructure to get even more entrenched.

Apparently this is what JG wanted and it’s pretty clear he didn’t have the patience or will to fund longer-term research/design efforts to truly capitalize on the explosive trends around cloud, exponential data growth, new machines/computing paradigms, etc.. Any idea that took longer than a week to conceive was laughed at.

The consequences of this are a major contribution to the decline witnesses today. It is indeed very sad.

'But others are just “losers”, not profitable, nor likely to be. And as @bdne+1qk7UpRX says, it's hard to see why they aren't cancelled, when their existence makes a sale or IPO more difficult."

Pure speculation of course....but perhaps losers are allowed to live on because getting rid of them would spotlight that one of the loser products is near and dear to one of the founders?? So just keep them all so a favorite can live on longer? If the books ever become complaint to generally accepted accounting principles and become known to the public, the answer will become clearer.

How can SAS ever compete with other AI powerhouses like Microsoft with SAS current management and staff. Just thinking about this makes me sad.
I wish it was SAS in the news for things like this news below instead of the competitors.

In the news, Microsoft used their Artificial Intelligence and High Performance Computing to whittle 32 million candidates of materials that can create a new kind of battery that uses less lithium and less likely to burst into flames to just 23 most promising material candidates in 80 hours. This piques the interest of Elon.

The HPC portion accounted for 10 percent of the time spent computing – and that was on an already-targeted set of molecules. This intense computing is the bottleneck, even at universities and research institutions that have supercomputers, which not only are not tailored to a specific domain but also are shared, so researchers may have to wait their turn. Microsoft’s cloud-based AI tools relieve this situation.

"Do JG and his executive teams and their divisions have the will and ability to do this in an optimal way that predicts SAS having healthy growth for the future?"

I hope so and wish so but deep down I think we all know the answer to that.

Much of the Viya architecture and infrastructure should be salvaged, along with corresponding innovation for effective integration with open source and other promising technologies (e.g. SingleStore). The objective for this effort should be bolstering existing successful solutions like Risk/Fraud and creating new AI and advanced analytics based niche solutions.

The big problem, as already discussed ad nauseam, Is effective management and allocation of resources necessary to extract maximum revenue from the declining V9 stream, while creating what amounts to a new company with the talent level, intensity and passion of a hot start up — to build out on the after mentioned salvaged Viya, etc. technology base. The combined dynamics here would be a significant challenge for the best, most high energy technology executives, engineers, etc. on planet earth.

Do JG and his executive teams and their divisions have the will and ability to do this in an optimal way that predicts SAS having healthy growth for the future?

@cwxd+1qk7UpRX

True, some “loser products” are maintained with minimal staffs as long as they’re profitable. That makes good business sense.

But others are just “losers”, not profitable, nor likely to be. And as @bdne+1qk7UpRX says, it's hard to see why they aren't cancelled, when their existence makes a sale or IPO more difficult.

The best explanation I’ve seen is that the Majority Owner vetoes the idea. He hates laying people off. He insists on profitability, but does only the minimal layoffs necessary to achieve it. That's a blessing for our friends who remain 😊.

Much talent left for higher salaries during 2021-2022, when SAS failed to compete against the pandemic stimulus. But much talent remains -- enough to execute some of the Viya salvage operations recommended in this thread.

But Viya competes against open source (Spark, et.al.), just as V9 competes against open source (R, Python, et.al.). Therefore, Viya cannot be a solution to the revenue shortfall; it only duplicates the problem.

Viya should be salvaged, because that can slow the revenue decline. But the only long-term solution is to create new revenue streams. SAS must get good at building solutions instead of tools — must, as you say, “do things right” technically, instead of expecting Sales and Marketing to compensate for R&D.

That requires cultural change.

So true. I am always (still) amazed at the number of people who have been here 30+ years doing essentially the same job in the same department.

@bopz+1qk7UpRX

At least in the case of some of the legacy “loser products” … they are making $10M a year with each covered by one developer (who likely also works on other things) and require very minimal Tech-support. Perhaps this is why the majority owner will not ki-l them off. They are still highly profitable.

JG is first and foremost a businessman. The sad irony is, if his true passion were technology and doing things right from a software design/architecture/computer science perspective, SAS could be doing $10B a year and growing, while paying true top performers with world class skills (most have left R&D) a righteous and competitive wage.

One of the reasons top tech companies succeed over time is they not only hold employees accountable for substandard performance and ultimately terminate them, they also make the top performers wealthy enough to move on before they become stale and hang around for years hoping for a pot of gold at the end of the rainbow. Sound familiar?

Profitability? I think you mean revenue growth.

"keep doubling down on the loser products"

"Puzzling that it is tolerated as that only makes a sale or IPO more difficult."

It was stated on another thread that recommendations have been made to jettison "loser products", but have always been vetoed by the Majority Owner.

He has, historically, given "loser products" many years to become "winners", even after others have given up on them.

On the other hand, he has always insisted on profitability, and that's highly desirable for an IPO.

So my guess is that SAS will continue to lay off the minimum needed to make a profit, and eventually we will see some "loser products" cancelled.

"keep doubling down on the loser products"

More highways, Mr. Moses?

"keep doubling down on the loser products"

Puzzling that it is tolerated as that only makes a sale or IPO more difficult.

What is really strange about SAS is that they didn't and still don't know how to build good solution products but they built a lot of solution products that mostly made no money or even lost money but yet they do not get rid of them but keep doubling down on the loser products.

"Most did not know how to build consumer products, and some did not want to learn."

BI, Viya and a slew of solutions are the output of what you cited above. SAS lost their way a long time ago and a bounce back to glory does not appear in the cards. Sad...

@bcjv+1qk7UpRX

An excellent post on so many levels!

"And most managers wanted to keep building software in the old way they knew. Most did not know how to build consumer products, and some did not want to learn."

Yep, incompetent and arrogant managers.

"But in all these markets for consumer products, we aren’t building tools for people like ourselves. We must use modern techniques to put the customer first. For SAS, that requires cultural change."

Oof, even Archimedes isn't capable of moving that cultural change behemoth.

"...SAS missed a gigantic opportunity for that kind of "low code"… this kind of UI-based application is incredibly “sticky”… Seems like SAS never fully understood the category/opportunity…"

SAS made many efforts in this “low-code” UI-based category, going back decades. I worked on several of those products. Most of them failed.

Most of them failed because we failed to adapt. SAS was successful when it built programming tools for SAS programmers, or statistical tools for statisticians. As long as we built tools, for people like ourselves, we understood our users well.

But to build solutions — consumer products — is a harder problem. It requires understanding users who are not like us. It requires strong UI design and frequent customer feedback. It requires modern techniques for usability.

We paid lip service to those modern techniques. We hired UI designers, but we did not let them make decisions. And most managers wanted to keep building software in the old way they knew. Most did not know how to build consumer products, and some did not want to learn.

They approached product design as a list of features. I often saw a release delayed for missing a feature — but never for failing a usability test.

Most products did not even run usability tests.



Some of us tried to introduce modern usability techniques. To say the least, this was not good for our careers. UI design was full of politics. It was like a young child’s soccer game. Everyone wanted the ball, but few of them knew what to do with it.

For all these reasons, we did not spend enough time on UI design, and we got little customer feedback before shipping. We threw the products out there and hoped that they would sell.

Our friends in Sales and Marketing said, wow, to develop software in such a way, those developers must have big egos. There were certainly some of those!

But the main problem was that developers weren’t using modern techniques. We were building solutions in the same way we built tools, and there was a deep-seated resistance to change.

In the BI market, products like PowerBI, Tableau, and QlikView easily achieved superior usability. These products were also highly competitive on both features and price. Not winning in any of these three areas, we lost what should have been one of our best markets.

Now, battling from behind on features, price, and usability, SAS will never catch PowerBI. Nonetheless, SAS should remain in this market niche — because it’s so large that even a small share can be profitable. There is also profit in other niches, such as Risk and Fraud.

But in all these markets for consumer products, we aren’t building tools for people like ourselves. We must use modern techniques to put the customer first. For SAS, that requires cultural change.

"They even hired a bunch of graphic design interns to make it look pretty."

OMG, SAS is such a cheapskate. Hired graphic design interns for VDMML instead of pros with lots experience?

"...SAS missed a gigantic opportunity for that kind of "low code" or mix of "visual" plus code (mainly just SQL) success. Even as the code-only approach is disrupted by open source, this kind of UI-based application is incredibly "sticky". SAS was competing very well in this area, but did not invest heavily enough. Seems like SAS never fully understood the category/opportunity..."

SAS made that VDMML thing. Last I knew, that was visual plus code. They even hired a bunch of graphic design interns to make it look pretty. It must not have been a success where you are at. R is still prettier, in my opinion.

SAS has been trying to get into the niche solutions by acquiring companies that already have a strong foothold in niche solutions (acquiring is easier than to compete with them). In 2022 SAS acquires privately held Honolulu-based Kamakura Corporation. Kamakura's specialized software, data and consulting help financial organizations across the spectrum – banks, insurance companies, asset managers, pension funds and more – manage a variety of financial risks.

In acquiring Kamakura, SAS aims to deliver an unparalleled suite of integrated risk solutions, particularly around asset liability management (ALM), and serve additional facets of the financial services industry.

JG himself said in 2022 :
“This acquisition is an extension of tremendous investments already made in SAS’ cloud-ready risk management platform and integrated solutions. It signals our intent to advance market-changing risk solutions to solve the most pressing challenges our financial services customers face. We foresee that the resulting strength of SAS technology, paired with Kamakura’s risk analytics and credit models, will prove far greater than the sum of its parts.”

I sincerely hope SAS can succeed in the niche solution areas, especially risks and fraud.
Don't squander this opportunity.

@6rrl+1qk7UpRX

Working at a large customer site now. We have most of the major analytics tools. Our current adoption trends are probably representative of most similar large sites:

BI: it's not just that Msft is selling us PowerBI. It's already bundled into our Office contract. So we have it "for free". We are seeing a rapid move away from Tableau to PowerBI. People complained mildly but then quickly realized it's very good. It's incredibly easy to share output to Teams. Easy financial win to drop Tableau asap.

End user data prep: using Alteryx. It seems clunky to me, but most people here like it. Every time management claims we will move on, the people will not allow it. It's as embedded as kudzu is on the side of the Georgia highways. SAS missed a gigantic opportunity for that kind of "low code" or mix of "visual" plus code (mainly just SQL) success. Even as the code only approach is disrupted by open source, this kind of UI-based application is incredibly "sticky". SAS was competing very well in this area, but did not invest heavily enough. Seems like SAS never fully understood the category/opportunity.

Advanced analytics/data science: Python the standard. SAS still used by soon-to-retire cohorts. Probably has 10 years left. R extremely niche: almost entirely dead already.

A niche solution: SAS is actually doing well here for us. Nobody using it cares or even knows about the above three categories of tools. They only care about solving certain business issues. SAS could also likely AI enable its solution over time. Seems like one still-promising area for investment. Hope they will do that.

@6rrl+1qk7UpRX
Excellent post. I agree with everything you said. Totally true!

The analytic market has completely shifted now and SAS is no longer a major player like it used to be. One of the biggest strength of SAS is the "SAS Programming Language" with the DATA step, Procs, and Macros. This is widely used in the production work in the field. However, SAS started deemphasizing the language about 8-10 years ago and promoted the low-code and no-code applications as the future of SAS. At the same time, Python and R was gaining popularity in the field and colleges.

Now, we are trying to play the catch up game but it seems like the effort is too-little-too-late. With Viya not gaining any traction in the market and SAS 9 development was put on the back burner for a while (and restarted now), things are not looking good for us.

The vacuum created by SAS in the analytic space was filled by Microsoft. They now have a complete end-to-end solution for the data science, machine learning, and AI space. They have already one foot in the door of major Fortune 500 companies with their corporate Office licenses, and now they are selling Power BI and Azure Machine Learning to them, which nicely integrates with the rest of the suite. It seems like Microsoft stole SAS's lunch because our leaders were sleeping at the wheel due to internal politics.

Despite this, SAS was able to sustain the revenue for the past few years because some market sectors like the Pharma, insurance, banking, and government were heavily invested in SAS and were renewing the SAS 9 licenses to keep their code running. The Pharma and finance sector have wised up now and the race is on to de-SAS'ify their sites and some of the major companies have been very successful with this effort. The last holdout is the government sector which moves at a snail pace and is the last one remaining loyal to SAS.

"People inside SAS have said that efforts are being made to make Viya more compatible with V9, and to port Fraud and Risk to Viya. So at least some of these opportunities are being targeted."

Show me the money. The proof is in the pudding.

This is the best thread I’ve seen on what could have been, and what still could be done. Let me try to summarize what I’ve learned on this forum.


These opportunities were missed:

1. The explosive growth of data driven by the Internet handed SAS a generational opportunity. When every company that analyzed data had the wind at its back, SAS revenues adjusted for inflation actually shrank. The people SAS promoted did not know how to seize this opportunity.

2. SAS could have made academic licenses always free. That would have delayed the loss of market share to R and Python. But in the long run, there’s not much SAS could do to compete with open source. As a data science programming language, SAS’ market share will continue to erode.

These opportunities were missed, but are still available:

1. SAS could have built commercial products on top of open-source software, as Databricks did. SAS could have built attractive products for data analysis, as Tableau did. Such products could still be built. At this late date, it would mean playing catch-up — but still playing to SAS’ strengths.

2. For Viya to succeed V9, it must be made a) more compatible with V9, and b) performant, at reasonable cost, on PCs and departmental servers. Both tasks are technically challenging.

3. For Viya to sell without succeeding V9, “it’s not too late to salvage pieces of CAS and the Viya micro services, etc. in support of new AI/advanced analytics-based enterprise software products.” Viya could also serve as a platform for financial products such as Fraud and Risk, whose customers will pay for fast performance.

People inside SAS have said that efforts are being made to make Viya more compatible with V9, and to port Fraud and Risk to Viya. So at least some of these opportunities are being targeted.

Most people don't care about the past. Only the current and future are important.

"Here's the curriculum for the 10-month Master of Science Analytics (MSA) program at NC State University. They teach "Advanced R Programming" and "Advanced Python". I do not see SAS in the curriculum for MSA."

That's a relatively recent ( 2019-ish?) development. It was heavily SAS-based for its first decade.

This is what people in the industry say about SAS on the internet:
"Prior to 2015, SAS used to dominate the data science industry, however, by 2017, it became a minority to Python and R."

How fast SAS got overtaken by open source. Sigh!

@wfa+1qk7UpRX You just dox’d yourself. You are clearly Walter Mitty.

@wqh+1qk7UpRX

I bought and read The Power Broker based on your recommendations in this forum.

If you had mentioned that it's over 1100 pages, I might not have had the courage :-)

But it is a great book. With, as you say, certain similarities...

@wfa+1qk7UpRX

This is more about your personal perception of what might have happened than it is about reality.

patients = patience

@gzt+1qk7UpRX

… And instead of building CAS, that venerable systems programming talent from SAS could have been re-purposed to build proprietary and/or license-restricted open source accelerators for the Spark, Python ecosystem.

It’s not too late to salvage pieces of CAS and the Viya micro services, etc. in support of new AI/advanced analytics-based enterprise software products. However, so doing will take a radical change in mindset at SAS and one that likely cannot occur while JG is still in charge. It’s also going to take a team of highly skilled/qualified software architects and master level infrastructure engineers with patients to design and do it right the first ti Fortunately, White is described in the previous sentence has not been in the DNA of SAS since the late 1980s to early 90’s.

If SAS has any hope for future success, it’s going to be as an AI-heavy niche enterprise software vendor and certainly not building data science programming tools.