Last month the RSR team visited the SAS campus in Cary, North Carolina to participate in SAS Insight, the company’s annual analyst conference. It was a chance for us to hear what SAS is doing across all the businesses that the company serves. SAS is well established as a strategic technology provider in banking, government, insurance, health care, and life sciences, and it views manufacturing as a growth market.

But what about retail?

Some will remember that in the beginning of 2024, the company moved away from its vertical marketing focus (one of which was the retail industry) and moved towards a horizontal approach (spanning all the industries that it supports), counting on its partner network to address industry specific challenges. Retail is viewed as a target industry, along with utilities, telco, media, oil & gas, education, and travel. And SAS is actively promoting solutions that address four key focus areas in retail: Demand forecasting, intelligent planning, customer intelligence, and personalization.

So, to paraphrase a quote attributed to Mark Twain, “rumors of SAS exiting the retail market are greatly exaggerated” (undoubtedly, those rumors were spread by the company’s competitors).

The successes that SAS has racked up in many ways are emblematic of the rapid transition that is happening across all industries from a function-first systems orientation to a data-first orientation. I remember back when IT’ers were learning about entity-relationship modeling, the concept was articulated that while functions would come and go, the underlying data was relatively stable. A simple example is customer order orchestration: solutions providers are constantly improving the functionality associated with filling a customer order, but a customer is still a customer and an order is still an order. While that seems obvious now, thirty years ago systems created and managed their own data in their own siloes for their own purposes. That of course is why today, many retailers still grapple with the problems associated with siloed systems (more on that in a minute).

“SAS” is an acronym for “statistical analysis systems”, and the company was into data science before people who did that were called “data scientists”. Now the company is focused on bringing data science down to “street level” so that common mortals like me can take advantage of the underlying data science. That’s what SAS Viya is all about (the company defines Viya as “a cloud-native, high-performance AI and analytics platform … designed to transform raw data into insights through data management, advanced analytics, and machine learning capabilities.”).

One of the company’s big operational challenges is in migrating their existing customers from its legacy on-premise solutions to the new cloud-based capabilities. According to Gavin Day, EVP, the company’s approach is to help customers “move toward” Viya rather than forcing them to “move to” the new solution. The proof that the company is succeeding is in the numbers that the company shared with analysts; revenue growth related to Viya is significantly up while license renewals are dropping off.

SAS was all-in on AI enablement before the term became such as buzzword. At the meeting, EVP & CTO Bryan Harris pointed out that Viya is the only platform that offers the whole range of capabilities: data store, data management, synthetic data creation, data catalog, data model operations, business intelligence, automated decisioning, GenAI development tools, a coding environment, and governance. According to Harris, the objective of all of that is to offer solutions and models as a service.

In other words, SAS is making data science accessible to non-data scientists. That’s important, because most retailers will never have data scientists on hand – those people are simply too expensive.

“Models” and “governance” really interest me because no matter how accessible companies like SAS try to make AI enablement, it’s still esoteric stuff. For example, models (those things that help relate an event to a set of probable outcomes) are not static – they must be “trained” (improved to respond properly) with each occurrence of an event and the response to that event. Governance of the technical environment that offers AI-enabled capabilities is as important to companies as governance of a cloud-based computing environment is. I’m reminded of how companies like Microsoft and AWS offered Cloud “centers of excellence” for cloud computing, to help companies get up to speed on how best to manage those environments. It seems like a good idea for companies like SAS to offer similar consulting services now.

As if to underline the importance of models, SAS is preparing to offer a “data maker” capability that can synthesize data – either to create needed data or to fix existing data. The Data Maker solution was developed by a company called Hazy, which was acquired by SAS in 2024. According to Alice McClure, Senior Director of Product Marketing, SAS expects to have Data Maker ready for general availability in July 2025. This should interest retailers because while retailers have oceans of transactional data waiting to be analyzed, much of it needs to be cleaned up and improved to feed probabilistic models.

How SAS Can Help Companies With Diverse Technology Portfolios

SAS has positioned itself as a “stand-beside” platform. RSR had a chance to participate in a recent SAS webinar with Richard Widdowson, SAS VP of Global Retail & Consumer Goods Solutions, and he shared this chart (below) which shows how the company’s forecasting and planning solution is positioned to work with siloed operational systems like Relex, SAP, or others. The positioning is intended to augment, rather than replace functionality that those systems provide, hopefully to fast-track time to value for the investment.

Since Forecasting and Planning are such hot topics right now, and SAS hopes that retailers’ need to respond much more quickly to sudden changes in either demand or supply will trigger interest in the company’s offering.

We can certainly say this: the solution is timely. Retailers of all shapes and sizes are grappling with the need to not only respond in near real-time to changes in the marketplace, but to anticipate those changes in order to position assets and capabilities so that they are there and ready when the market does change.

When it comes to the retail world, it seems that the industry is catching on to SAS’s mission – “to provide knowledge in the moments that matter.”