The process for inventory and fulfillment planning has been consistent for nearly a century. Years of experience and insight by skillful fulfillment professionals elevated the science to more of an art that was honed through years of consistent experiences.

Until now.

Within the past five years, the consumer demand for fast and free delivery, the enablement of the store network as fulfillment activity nodes, and the subsequent margin pressures have rendered most of that knowledge obsolete.

Retailers are responding with omnichannel initiatives, and for those who are refining their unified distribution, exposing the right inventory to the right customer is not the end of the story. The ability to minimize markdowns and stock-outs, while maximizing the usage of return inventory balanced with historical store performance, current traffic, and resource load, requires real-time, intelligent optimization beyond what a human can do alone.

Adaptive Network Fulfillment (ANF) uses intelligent optimization to evaluate large numbers of parameters across fulfillment, transportation, stores, and customers in real time to maximize margins and profitability of digitally-influenced orders with minimal impact to in-store shopping experiences and store labor.

Adaptive Network Fulfillment is the final piece of the inventory puzzle for omnichannel retailers, adding optimized sourcing to global inventory visibility and dynamic availability views to make promises you can keep to your customers, profitably.

And because stores are on their way to becoming one of the most critical components in an omnichannel retailer’s fulfillment network, the complexities and differences of using a store as opposed to a distribution center for fulfillment must be reconciled. The store requires evaluation of additional considerations such as historical performance of fulfillment activities, staffing load, in-store traffic, and inventory levels.

Optimizing how stores are leveraged for fulfillment opens the opportunity for quicker delivery times by leveraging proximity to customer and optimal inventory utilization for profitability and service commitments. Merchants are able to expanding fulfillment capacity during sales, promotions, and other peak periods and increase order margins by leveraging local and/or marked-down inventories. In fact, retailers can enjoy reduced risk of markdowns and return-to-vendor situations by leveraging locations with deepest supply levels and increased customer satisfaction by saving a potentially lost sale if a product is not available at a DC but is available in a nearby store.

Features + Functions
Optimization
  • Define optimization strategies based on service levels, free shipping, clearance items, and customer classifications
  • Evaluate multiple fulfillment considerations holistically
  • Convert each consideration to a cost of fulfillment, including shipping/handling, capacity, rejection rate, inventory levels, days of supply, selling price, and proximity to customer
  • Balance fulfillment workload across facilities
  • Address surplus units and protect last units in-store Leverage historical rejections rates, accuracy, and workload
  • Ship from stores with price markdowns in addition to shipping and handling costs Use incentives or deterrents based on real-time data, such as surplus inventory or maximum fulfillment capacity
  • Prioritize fulfillment from facilities that are designed for volume, such as distribution centers and larger footprint stores
Understanding and Adapting
  • View every fulfillment decision, with overall cost breakdown, and decision parameters
  • See single order detail or real-time global network performance
Fulfillment
  • Route orders and track status in real time to a distributed network of DCs, stores, and suppliers
  • Support complex merge-in-transit fulfillment flows for a single delivery to the customer
  • Utilize vendor drop-ship order fulfillment
  • Handle fulfillment outages, capacity constraints, and inventory protection

Deliver On Your Promise to Customers