Announcing SAS for ‘Demand Signal Analytics’


From Gartner to IDC to the trade press, the watchwords in the supply chain for rest of this decade appear to be “resiliency” and “responsiveness”. It’s not going to be about promotion-based pull-through, and it’s most definitely not going to be about channel incentive-based push-through.  What it’s going to be about is demand sensing, and then effectively responding to those demand signals.

It is of course a cliché to talk about change and the increasing pace of change and how this or that role or function is changing, but the combination of globalization and the internet has in fact dramatically affected the pace of change in the consumer market over the past decade.  It’s no cliché to point out that replenishment-only-based supply chain strategies are a thing of the past.

Three significant factors come to mind when dissecting this increase in the rate of change.  The first is the rate of change on the supply side.  The speed of innovation has picked up.  New ideas sprout up more often and come to market more quickly than previously.  New competitors can enter the market more rapidly with fewer of the traditional barriers to entry impeding them.  The increasing adoption of 3D printing will only serve to accelerate this process further.

Secondly, the internet has provided for both more supply and more consumer channels.  Consumers are doing more product and price research on-line, affecting not just traditional supply-chain oriented segments of the economy like consumer goods, but also areas like health care delivery as well (confess – who hasn’t logged in online to make sure that that funny feeling wasn’t a sign of cancer or some deadly, infectious disease?)  Consumers are arbitraging the bricks against the clicks, while your competitors’ products, and sometimes even your own, are appearing in the most varied of on-line channel outlets.

Lastly, consumer trends emerge, morph and spread faster than ever before, which is saying something.  While social media gets most of the credit/blame, other media are becoming all pervasive too, with no escape from advertising anywhere.  Content-marketing based retail mobile shopping, texting you with an individualized 2-for-1 offer precisely when you are standing in front of that product in aisle 10, enabled by the GPS on your smartphone. Product placements in television and the movies, advertising in our cash-strapped public schools, naming rights not just for stadiums or even players but for individual player activities (‘… and that Barry Bonds Blast was brought to you by …’).  How soon before we start seeing paid advertising on Google Glass?  (I would think it likely that it’s already part of the business model)

If you are basing your forecast on shipment data alone, you don’t stand a chance.

Which is why the focus is increasingly shifting towards the analysis of early demand signals that can be translated back into production and supply chain actions that better sync up with a moving demand target that has lately found itself another gear.

Yesterday’s announcement of SAS for Demand Signal Analytics at the IBF Supply Chain Planning & Forecasting Conference in Scottsdale, AZ, is SAS’ response to your need to react faster to market changes.  Its foundation is a robust demand signal repository (DSR) upon which is layered the user-friendly analytical forecasting you are already familiar with from SAS, coupled with SAS® Visual Analytics, which in this offering incorporates the custom-built capabilities needed to address demand signal analysis.

Higher revenues and fewer stock-outs, close-outs and inventory write-downs come from better forecasting.  And better forecasting doesn’t come from doing the same you’ve always done – relying solely on your own shipment data.  Better forecasting comes from utilizing downstream data, syndicated scanner data, closer to the customer data, from your intermediate distribution channels and your retailers’ POS systems. Building your operational plans on consumer buying behavior as it occurs allows you to search for those early but weak demand signals that portend a new trend, increased competition, or the immediate effects of promotional efforts.

What if you could watch and analyze the effect of pricing or trade promotions as they occur at the retail level rather than waiting in arrears for quarter-end reports?  What if you could manage rather than just measure the effectiveness of your operational and supply chain planning? What if you could identify what really influences sales performance and recognize even subtle market shifts months earlier than if you had relied on after-the-fact shipment data alone?

Ultimately, a manufacturer with better vision into the true demand for its products can manage its suppliers and channels more efficiently and effectively. Lower operational, logistic and inventory costs, greater revenue from fewer missed opportunities, and happier consumers who got what they wanted, when and where they wanted it, are all part of the benefits of synching supply with demand by increasing your focus on the demand signal side of the equation.


About Author

Leo Sadovy

Marketing Director

Leo Sadovy currently manages the Analytics Thought Leadership Program at SAS, enabling SAS’ thought leaders in being a catalyst for conversation and in sharing a vision and opinions that matter via excellence in storytelling that address our clients’ business issues. Previously at SAS Leo handled marketing for Analytic Business Solutions such as performance management, manufacturing and supply chain. Before joining SAS, he spent seven years as Vice-President of Finance for a North American division of Fujitsu, managing a team focused on commercial operations, alliance partnerships, and strategic planning. Prior to Fujitsu, Leo was with Digital Equipment Corporation for eight years in financial management and sales. He started his management career in laser optics fabrication for Spectra-Physics and later moved into a finance position at the General Dynamics F-16 fighter plant in Fort Worth, Texas. He has a Masters in Analytics, an MBA in Finance, a Bachelor’s in Marketing, and is a SAS Certified Data Scientist and Certified AI and Machine Learning Professional. He and his wife Ellen live in North Carolina with their engineering graduate children, and among his unique life experiences he can count a singing performance at Carnegie Hall.

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