We use cookies and other similar technologies (Cookies) to enhance your experience and to provide you with relevant content and ads. By using our website, you are agreeing to the use of Cookies. You can change your settings at any time. Cookie Policy.


An Interview with John Sall, Co-Founder of SAS

Originally published October 5, 2009

John Sall is a co-founder and Executive Vice President of SAS, the world's largest privately held software company. He also leads the JMP (pronounced “jump”) business division, which creates interactive and visual data analysis software for the desktop. In this age of “rock star, bad-boy executives,” John exemplifies the alternative paradigm; his passions are coding and system architecture of the JMP product, reportedly initially meaning “John’s Macintosh Project.” He is an amazingly well-grounded, gracious and generous individual. In this case, generous with his time, as he sat down with Lou Agosta for a conversation after lunch at the Discovery 2009 / Innovators’ Summit in Chicago on Thursday, September 17, 2009.

Agosta: As you know, John, if I may, one of the keynote speakers at the conference is Malcolm Gladwell. His latest book Outliers contains a model of extraordinary individuals and, to a certain extent, debunks the myth of individual genius, pointing in the direction of context, environment and lucky breaks. You have certainly accomplished amazing things and, in Gladwell’s sense, are an amazing person – a statistical outlier. Apply Gladwell’s model to yourself.

Sall: I’m not really going to do that. However, I will say that we – myself, Tony Barr and Jim Goodnight – were at the right place at the right time in the mid 1970s. I’m really lucky to be in a field that really took off – to be in a position to join Goodnight and Barr. Statistics became important because agriculture depended on it. The background is that in 1941 Gertrude Cox at North Carolina State University was using statistics to manage agricultural results. The estimates on crops from the U.S. Department of Agriculture – and they are here at this conference, by the way – still drive vast dollar options and futures in market worldwide, but we [SAS] have obviously grown beyond that niche. In those days, computers were people performing calculations using adding machines. She [Professor Cox] came in and hired the others. This created openings for Stu Hunter and George Box1 to apply statistical methods to experimental design to optimize the knowledge gained from research. When I joined Jim Goodnight and Tony Barr in the 1970s, there was a growing network of statistical inquiry in place that presented extraordinary opportunities for those able to innovate and address unsatisfied needs in the market for usability, scalability and computational power. An early relationship with IBM – obviously a major player then and now – also provided a boost to our growing prospects at SAS. That commitment continues with JMP as we continue to innovate in the areas of visualization, algorithms and empowering the user literally to think, experiment and ask questions faster, deeper, more expansively both inside and outside the statistical box.

Agosta: So, fast forward all these years. IBM has now acquired SPSS, the last independent software company here in the Chicago geography where we sit and talk today. What is your take on this?

Sall: It [the acquisition] was natural, even predictable, given the rise of analytics. The major BI [business intelligence] players were acquired a year ago. So it was natural that those into analytics would want things that were more than just query and reporting. Of course, acquisitions are a game that SPSS has itself undertaken, for example, with the acquisition of Clementine. IBM has made a huge commitment to SPSS and its employees. The nice thing for SPSS is that an enterprise such as IBM will not necessarily stop at re-branding the products and can help make the tools fit together better, provided that’s what they do. On the other hand, you do not necessarily get best-of-breed software offerings with a single source. At JMP, we have got our hands full integrating all the functions of development and components and pieces and our own release schedule – especially the release schedule – which always seems to be getting tighter and more demanding. And please remember, I am heading up a small company, JMP, within a larger company. In addition to advanced and innovative algorithms, which I covered in my talk this morning, we are delving into the visualization and graphing areas. Within SAS, we are lobbying for resources along with other groups. JMP’s strengths are many, and we are delivering results especially in interactive visualization. When you require root cause analysis in advanced marketing, factory processes, financial analysis and supply chain analytics, then business intelligence reporting is not going to be enough. We are bringing the advanced statistical results to a wider audience of smart analysts.

Agosta: What are your thoughts on the advantages of not being traded publicly?

Sall: We are very happy the way we are. At both JMP and SAS, we are concentrating on listening to our customers and our employees. When you throw an additional third party into the mix, say, stockholders, then what is already a challenge becomes even more difficult. We have grown steadily and deliberately over the long term. I don’t necessarily know the details at SPSS, but a company gets bought or sold because of the need to pay off investors and venture capitalists. Here at SAS, we add employees – we grow – as revenue allows. We never needed external financing even in times of inflation – and even in the bubble economy – we resisted temptation – and, make no mistake, there was some temptation at times, though not recently.

Agosta: Could you share your thoughts on the September 2008 event when the economy blew up?

Sall: Even before the event, we at JMP and SAS have tried to scout out who had statistical insight into risk and was asking the right questions. Not enough attention was paid to the tail of the distribution. The work of Clark Abrahams of SAS on fair banking, credit and risk scoring is relevant. It turns out that the FICO score was being used to determine if someone was a risky bet for a mortgage loan. You can have a quite good FICO score if you have a high credit card balance and are paying it off on time, living paycheck to paycheck. Such an individual is not necessarily a good risk for a long-term mortgage. In addition, as the mortgages were collateralized and sold, there were numerous information separations – and asymmetries – that disguised the systematic risk with credit default swaps (CDSs). No one saw the big picture. In a sophisticated, complex system such as this where the challenge can be information overload – too much data – tools that enable modeling and capturing the big picture become more and more critical. That is part of what gets us up and inspires us at JMP.

Agosta: One of the disruptors in the various software markets is open source – open source operating systems, databases, BI tools…open source statistical packages? What is your take on this?

Sall: You know, open source has been common with statistical packages as far back as I can remember, at least in the sense of free packages. These tend to be targeted to academic environments where researchers are able to trade off effort and time for relatively limited budgets. Thus, there tends to be more pressure at the commodity layer where the user is willing and able to do more of the grunt work. I hasten to add that we have a role at JMP where we reach out to colleges and universities with discount versions of JMP; and, of course, students can take courses in Base SAS and more in many business schools and statistics departments. At the innovation layer, which is where JMP plays, there is less pressure from open source. The differentiator is that we at JMP are delivering highly visual, interactive insights by means of a point-and-click interface.

Agosta: Thank you for the conversation.

End Note:

  1. Everyone at the conference received a copy of Statistics for Experimenters, 2nd edition, by George E.P. Box, J. Stuart Hunter and William G. Hunter. New York: John Wiley Interscience, 2005.

  • Lou AgostaLou Agosta
    Lou Agosta is an independent industry analyst, specializing in data warehousing, data mining and data quality. A former industry analyst at Giga Information Group, Agosta has published extensively on industry trends in data warehousing, business and information technology. He is currently focusing on the challenge of transforming America’s healthcare system using information technology (HIT). He can be reached at LAgosta@acm.org.

    Editor's Note: More articles, resources, and events are available in Lou's BeyeNETWORK Expert Channel. Be sure to visit today!

Recent articles by Lou Agosta

 

Comments

Want to post a comment? Login or become a member today!

Be the first to comment!