1010data Shelf Monitor Ensures High On-shelf Availability with Big Data Discovery


Sometimes those of us who watch the industry focus on the sensational instead of the practical. Big data is a case in point. Questions abound about tracking us “E”verywhere about “E”verything in order for retailers to build customer profiles for better, and supposedly more useful to us, “targeting.” Indeed, in light of the headlines about data breaches, this rightfully has grabbed headlines. It has also led many to believe that big data is ultimately the tool by which personal privacy will become obsolete, just because the stakes are so high and the value proposition seems irresistible.

No matter how one feels about analysis of personal data information by retailers of all stripes, the fact of the matter is that there are more practical uses of big data by retailers and a significant opportunity for vendors. This is exemplified by New York City-based 1010data, Inc., a provider of big data discovery and data sharing solutions. The company’s new 1010data Shelf Monitor, an on-shelf availability (OSA) analytical application, provides a look into one such use case that makes a lot of sense in terms of the time and money it can save and the insights it can provide. 

Put simply, the 1010data Shelf Monitor’s function is to alert retailers when products are running low on their shelves. As somebody who in one of my previous lives was a department manager and a buyer for a major national retailer, I appreciate the value here.  

Analyzing literally billions of data points the 1010data Shelf Monitor uses proprietary predictive analytics to determine real-time shelf stocking status so store managers can act on potential shortages. Current inventory management systems just do not provide this type of valuable information. Think of the challenges for companies like Walmart with hundreds of thousands of SKUs to track at thousands of stores.  The person power to do shelf checking is to say the least daunting.

Time is money and customers get frustrated

Aside from automating the manual process of shelf-checking, as noted in a 1010data study, “On Shelf Availability: An Examination of the Extent, the Causes, and the Efforts to Address Retail Out-Of-Stocks” by Daniel Corsten and Thomas Gruen, when customers do not find the specific products they want on-shelf:

  • 31 percent will buy at another store
  • 22 percent will substitute a different brand
  • 11 percent will not buy the item at all

The bottom line really is the bottom line here.  

While it has become almost a cliché, the actionable (proactive as well as reactive) insights provided by the 1010data Shelf Monitor are noteworthy. They include:

  • Alerts about OSA issues through active monitoring of discrepancies in sales patterns
  • Targeted lists pinpointing stores with shelf availability issues to enable quick updates to forecasting and store distribution plans
  • Lost sales analyses that examine the number of days OSA issues have occurred and total lost sales
  • Dashboard analytics on all OSA issues related to products, stores, and lost dollars
  • Day of week analyses highlighting specific days of the week when OSA issues are more likely to occur
  • Low availability product analyses showing which products have more OSA issues
  • Lost sales forecasts of potential missed sales opportunities

“Empty shelves mean lost sales and reduced customer loyalty, and in today’s competitive retail space, chains that solely rely on inventory management systems are at a competitive disadvantage and are potentially alienating customers,” said Jim Mattecheck, vice president of Retail Solutions at 1010data. “As a customer focused solution, 1010data Shelf Monitor leverages the power of Big Data and predictive analytics to allow retailers to capitalize on the data they already have. This will improve the shopping experience for customers, while bolstering sales and decreasing supply chain costs.”

In additional observations on the value of data available to retail management, 1010data points out that, “Inventory control is the holy grail of retailing.” Again, harking back to my own experience, I resonate with the observation, for example, that we are probably just at the tip of the iceberg in terms of additional value further automation of inventory control can provide. 

As someone who used to pour over lots of statistics, the one that always got me, especially when doing end of the year inventory, was validation of the fact that missed mark-downs cost retailers more in profits than shop lifting.  As 1010data points out, “Marrying OSA information to real-time pricing of and the history of what is on those shelves is another area of big data applicability on the vendor side, and making that information on pricing and availability transparent to customers while they are in the store or on the way is also something that hopefully is in our future.”

Off the shelf or off the rack may be a way for customers to get a discount, but that assumes it was on the shelf or rack in the first place.  As noted, there is more to big data than profiling people. It has a large and expanding role to play in the areas of workflow management, process automation, logistics, etc.  And, as this example points out, for retailers the practical use of big data is a big deal. 

Edited by Rachel Ramsey
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