Supply Chain Report: Achieving Control Over the Omnichannel Challenge

Q: How has the growth of e-commerce disrupted traditional supply chain models? What are the key ways in which consumer goods companies are addressing these issues?

The focus has changed from pure store delivery to store-plus-home delivery, and this has created a number of supply chain issues, largely because there are many more points of consumption to consider. Order quantity sizes are no longer limited to truckloads, so you have to be able to manage parcels and provide a higher level of service to meet consumer expectations.

Micro-order quantities create a need to optimize time and location to fulfill orders, as these quantities dramatically impact the standard truck load replenishment. Leveraging solutions such as digital network platforms and services makes this a non-issue. It doesn’t matter how many different channels, processes, order quantities or fulfillment strategies you use if your system naturally adapts.

Q: What tools are consumer goods companies adopting to improve supply chain visibility across the entire enterprise?

There is a big trend in the market around what are called “control towers.” However, as is true in all early-stage markets, confusion abounds; everyone wants to claim they offer a control tower. Transportation solution vendors want to claim that their transportation-only control tower is a control tower. Those who only do demand-type processes want to claim that there's is a control tower.

In reality, what the market and CPG companies need is a true multi-party control tower that fuses all demand, supply and fulfillment data into a single real-time, permissioned, multi-party network. A true control tower should manage everything from consumer demand to fulfillment, and match all demand and supply between all parties.

Besides providing a real time multi-party network, the benefit of a “true" control tower is the ability to leverage the rich data by taking advantage of artificial intelligence and machine learning capabilities. When AI/ML is combined with a real-time network, these autonomous processes can plan and execute at a new level of scale and accuracy, with or without limited human intervention. Hence the name, “control tower.”

There was a recent study by the University of North Texas that found the expected fixed-leads time across the U.S. for traditional dry groceries is about 18 days. The traditional CPG company runs upwards of 60 to 65 days of inventory, while the average in-store in-stock is 96%. If you run a promotion, that number drops as low as 80%. This suggests there's a real need to improve on these metrics.

CPG companies running on multi-party networks using AI/ML solutions have reached as low as 25 days of inventory, with in-store and in-stock as high as 99%. A Gartner case study on Del Monte proved that there is a real opportunity to digitize the supply chain and dramatically reduce inventory while significantly improving service levels and revenue sell-through. These kinds of results can only be realized when autonomous AI and ML systems have real-time access to data-spanning demand all the way back to supply on a network platform.