The briefing starts with the statement, “We are a DSR provider.” I then ask, “What does that mean?” And the fun begins….
In 2005, Kara Romanow (now at Consumer Goods Technology (CGT) http://consumergoods.edgl.com), and I coined the term Demand Signal Repository (DSR). We were colleagues at AMR Research. After the original report was published, it seemed like EVERYONE declared that they were a Demand Signal Repository (DSR) vendor. They came out of the woodwork. So much so, that I wondered if many of them had ever READ the original definition. I often laugh when I got to a conference and look at the DSR signage. The term is EVERYWHERE; but for me, the realization of the original concept is NO WHERE. In the words of the old Beatles song, I feel like I am a Nowhere Man. Remember the words?
He’s a real nowhere man,
Sitting in his Nowhere Land,
Making all his nowhere plans
Doesn’t have a point of view,
Knows not where he’s going to,
Isn’t he a bit like you and me?
Nowhere Man please listen,
You don’t know what you’re missing,
Nowhere Man, the world is at your command!
The original definition of the DSR was broad. A demand signal repository is an enterprise software application that cleanses, synchronizes, harmonizes and uses multiple forms of demand data to improve enterprise decision making. The original writings included the statement that it was to include all types of demand data: structured and unstructured data, point of sale transactional and syndicated data, ratings and reviews, and sentiment data. However, as the technology providers have used the definition, I am afraid that it has become a new way to spiff-up their old marketing. Not all companies using the term DSR are “enterprise applications”, and the development of the software to “use” downstream data has been disappointing.
The Good News
In December, I uncovered two technology advancements that give me hope. Here I share my insights on these market shifts and give advice to the buyer of demand sensing software.
SAP and HANA: SAP is finally getting into the DSR space. The push is to build a data model on their HANA architecture. They are being very deliberate. I am pleased to see the building of a DSR to be one of the HANA sponsored projects at the board level. I am also pleased that they have announced a partnership with NetBase. NetBase is a listening technology for multiple forms of social data. It is a Software as a Service (SaaS) technology that visualizes 52 weeks of data from Twitter and Facebook.
Recommendation: I am glad to see SAP move in the direction of demand sensing and translation, but I feel that SAP’s work on the Demand Signal Repository will take many years. The cycle of ERP enterprise application development is much SLOWER than the cycle for sentiment analysis. As a result, experiment with NetBase or other sentiment/listening tools (Bazzarvoice, Clarabridge, Netezza’s Sentiment Appliance, or SAS) outside of the SAP HANA environment first and work with SAP on co-development of the DSR strategy.
As you work with sentiment and listening tools, use these technologies to move from a marketing-driven to a market-driven process. Harness the power to listen to customer feedback with little data latency. I find it sad that most listening projects are in the digital marketing sectors of the business. Harness the power. Use these technologies to build outside-in listening processes that tie back to quality, R&D, and customer service.
Vision Chain and Market Execution: I was also pleased to see Vision Chain’s new product development last week. I am excited about two new developments: predictive analytics for market sensing (market execution) and a mobile application on the iPAD for sales teams to work with the data to improve shelf availability. This has been a long time coming, but is a step in the right direction. The predictive analytics has been developed in conjunction with Matt Waller of the University of Arkansas.
Recommendation: I think that Vision Chain’s predictive analytics module for shelf sensing should be on the implementation roadmap for all Vision Chain clients. I also think that the mobile application makes the data more relevant and offers the potential to streamline store audits.
Also, be wary, with SAP introducing a DSR strategy themselves, Vision Chain’s partnership with SAP will weaken.
The SO What?
For the DSR market to ever move out of the NOWHERE MAN state that it is in right now, we have to help companies USE the data. Both of these announcements are steps in this direction.
The SAP Net Base announcement will accelerate the consideration of enterprise listening tools within the installed base of SAP. It will push the question of how to best integrate structured and unstructured data for demand sensing. However, the complete answer will take time. The applications that use demand data will have to be redefined (e.g. trade promotion management, demand forecasting, replenishment/VMI), but companies can take baby steps now to use sentiment data in enterprise processes to more quickly respond to customer feedback.
The Vision Chain announcement will start a chain reaction for other “DSR” vendors to launch predictive analytics and mobile applications. As this happens, challenge the vendors to define “predictive analytics” and test the depth of the solutions in a bake-off. However, when the dust settles. This will be a good thing for all.
In summary, I am tired of being a NOWHERE MAN. I want this market to move along. I want to see companies move from a marketing-driven to a market-driven approach. Social for the sake of social is a bright and shiny object that dulls quickly in the halls of digital marketing. Sales teams and supply chain teams are frustrated that they are surrounded by data that they cannot use. I want demand data to help companies to build strong outside-in processes to drive true customer-driven supply chains. These are steps in the right direction. However, users need to push their vendors for quicker answers. Let’s hope that we see more and more….
So, what do you think? I look forward to getting your response.
For more on the usage of Downstream Data check out these blog posts: