Direct POS Data Sharing

Retailer point-of-sale (POS) data sharing has been around for more than 20 years, but the availability and robustness of these valuable data streams evolved very slowly over time. Mass merchants have been more forth coming with the data compared to grocers or department stores, while privately-held retailers tend to guard data more closely than publicly-held competitors. For decades, syndicated data providers filled the gap of POS data analytics but they didn’t (and still don’t) cover inventory. Retailers didn’t initially share inventory data until they turned the corner about six years ago. Now, more retailers than ever are sharing not only store-level POS, but also inventory on a daily or weekly frequency at the store/SKU level. This month, Jennifer Beckett, vice president of Sales & Marketing at Vendor Managed Technologies, Inc. (VMT), reveals how this has drastically changed the collaborative analytics environment for retailers and suppliers.


What are the biggest demand sensing and inventory optimization opportunities by channel and category?

Beckett: We believe the biggest opportunities today are in the food and health and beauty aid (HBA) categories in the grocery and drug channels. Over the last 20 years, mass retailers were the early adopters in sharing robust and timely POS data with their suppliers. As a result, suppliers in specific categories, such as hardlines, were early adopters in leveraging direct POS data to drive collaboration efforts around reducing out-of-stocks and optimizing sell-through. Bear in mind that the grocery and drug channels had shared data early on, but it was to a very small group of tier one suppliers.


Why are food and HBA manufacturers joining this journey now?

Beckett: Mass retailer early adopters, such as Walmart, Target, Kmart, Meijer, etc., have large hardlines departments. Since syndicated data providers didn’t fully cover the hardlines categories, consumer packaged goods (CPG) companies looked toward the retailers’ direct POS streams to feed analytics engines and DSRs.  As a result, they have been leveraging direct POS and inventory data as their baseline for fact-based selling strategies for over a decade. However, food manufacturers have been reliant on syndicated data as the sole source of sell-through analytics with market share being one of their guiding KPIs.   

But many food manufacturers are starting to realize the value in integrating syndicated data with direct POS data, especially when the inventory component can be incorporated. They also understand that managing and measuring the success of an account shouldn’t be done solely on market share but should also take into account whether or not the inventory was there to support it. Retailers’ replenishment orders are driven off the reported inventory in their system. So right or wrong, the inventory needs to be clean and accurate to maximize your reorders and minimize out-of-stocks with the retailer. Properly mining POS and inventory data to improve the quality of a retailer’s replenishment process can provide massive gains in incremental sales volume. We saw this when one of our Fortune 100 clients documented an 8 percent growth in incremental sales just by closely monitoring and collaborating with its retailer partner to improve the quality of replenishment processes and eliminate out-of-stocks.


Where is the biggest ROI with demand sensing within the organization?

Beckett: Being involved with CGT’s Downstream Data Share Group has taught us that there are quantifiable and unquantifiable values associated with demand sensing and downstream data. For account managers, share group members have stated a fact-based selling approach that is specifically actionable elevates them to “trusted advisor” roles for the category. Anything less than that only invites the competition in to take shelf space. Marketing teams gain value from understanding the lift from TV ads, mailers, coupons or other investments. Trade promotion managers understand their exact lift and P&L from specific promotions and can improve execution success but insuring the right inventory is in place to support their trade investment. Demand forecasters can more accurately predict sales and eliminate out-of-stocks when they understand their inventory positions and sales trends not only at the distribution center but also at store level.

The bottom line is that success is achieved when the entire organization runs on a “universal source of truth” platform that generates data-driven insights needed to ensure the consumers have the products they demand. This is not a simple task and involves careful orchestration of hundreds of user requirements and multiple data streams, like direct POS, syndicated data, internal ERP data, census, trade promotion events, etc. The key is selecting the right solution providers with industry experience to help with this orchestration to ensure the analytics are impactful, actionable and measurable.