Retail Omnichannel

Most retailers understand that connecting to consumers via multiple selling channels will make them profitable, so learning how to execute on a cross-channel strategy is now a priority. This month, Jon Golovin, chairman, chief executive officer and co-founder of Retail Solutions Inc., explains how consumer packaged goods (CPG) suppliers can help omnichannel retailers achieve true fulfillment intelligence.


Define what fulfillment intelligence means and how does it relate to retail omnichannel strategies?

Golovin: Modern retailers must support their shoppers on a multitude of levels. From in-store shopping to online ordering and home delivery, to in-store or convenient location pick up. To be competitive with online-only retailers, traditional brick-and-mortar retailers need to leverage their local presence, both in terms of speed to access/delivery and order assortment and fulfillment. To do this successfully, retailers must consider how the mix of orders between delivery mechanisms are changing, so that they are staffed correctly to handle all orders. For example, if home delivery changes the way people are ordering (e.g., smaller or larger quantities) the latter could affect out of stocks, which could negatively impact customer service levels.  

What role does point-of-sale (POS) and retail downstream data play in fulfillment intelligence?

Golovin: Most CPG companies fail to forecast using real-time customer demand. Instead they use a lagged indicator, like previous orders. The lag time between the warehouse and when an item is available on the store shelf can only be reduced when real, accurate demand levels are identified — what shoppers are buying today, right now. With access to real-time POS data at the store level, CPG companies can reduce the uncertainty and, therefore, the safety stock required to meet the actual demand. This approach also applies to new product introductions and promotions. By leveraging retailer data in real time, CPG companies are able to increase shelf availability, correct distribution issues and revise forecasting on the fly.  


Can you provide real-world examples?

Golovin: I view fulfillment intelligence as a mix of customer intelligence, inventory availability and sales forecasts. A current example of fulfillment intelligence at work would be retailers who are tracking in-store sales, e-commerce sales and promotions. With downstream data available by store, retailers and their CPG partners can better forecast the response to a promotion from each channel by store or zip code — ensuring the correct amount of product is available both at the store and at the fulfilling distribution center where online orders are shipped from. Having this level of insight and granularity enables CPG companies to accurately determine whether a promotion both was in stock and executed correctly in each store. Downstream data can then be used to analyze past promotions and understand what makes a promotion successful — for each product, at each store. Retailers can then apply this knowledge to design future promotions with higher availability, better execution and more accurate goals in mind.


IDC defines a mature omnichannel fulfillment retailer to have inventory visibility, order capture and profitable order promising and distributed order orchestration. Do you agree?

Golovin: I would add that a mature, omnichannel fulfillment retailer must also monitor how the sales are moving from one channel to the other. For example, if shoppers are moving from in-store to online, this change in behavior will impact the planogram, or which product is placed in which area of a shelving unit and with which quality. This data will also prove useful for determining inventory levels, to staffing levels at the distribution center and at the retail stores. Setting the planogram once, or even twice a year, may not be sufficient if there are more rapid changes in the ordering mix between channels.